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[center][img][Hidden Content]] [center][b]Full AWS Security Course | Udemy[/b] English | Size: 6.5 GB Genre: eLearning[/center] Complete guide to mastering security in the AWS Cloud. [b]What you'll learn[/b] Cloud Security AWS Security Threat Detection in the Cloud AWS Welcome to the Full AWS Security Course - your complete guide to mastering security in the AWS Cloud. Whether you're a security analyst, cloud engineer, solutions architect, or just starting out in cloud security, this course is designed to take you from the fundamentals to advanced techniques used by professionals in the field. You'll learn how to secure real-world AWS environments using best practices, hands-on labs, and deep dives into key services such as IAM, VPC, GuardDuty, Security Hub, AWS WAF, and more. We'll cover everything from the Shared Responsibility Model to multi-account security strategies, threat detection, incident response, secure networking, and identity management. This course is not just theory. You'll gain practical, job-ready skills to detect misconfigurations, respond to threats, implement zero trust, and build secure cloud architectures. Whether you're preparing for AWS Security Specialty certification or working toward becoming a Cloud Security Engineer, this course provides a solid foundation. By the end, you'll be able to confidently assess and harden AWS environments against real-world attacks - just like top security teams do in enterprise and regulated environments. Learn from cybersecurity expert Hacker Loi, a cloud security leader with all 14 x AWS certifications. With real-world experience and hands-on demos, he breaks down complex AWS security concepts into practical skills you can use to secure your cloud like a pro. [b]Who this course is for:[/b] Solutions Architect Cloud Engineer Cloud Security Engineer [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Touch Typing for Success - Master the Art of Speed | Udemy [Update 05/2025][/b] English | Size: 649 MB Genre: eLearning[/center] Master Touch Typing to Skyrocket Your Words Per Minute in 2025 [b]What you'll learn[/b] Eliminate bad typing habits and significantly increase your words per minute (WPM) rate. Improve typing accuracy and fluency in real-world situations. Type with confidence and ease without relying on the keyboard for reference. Become a faster typist, maximizing your efficiency for work or personal projects Unlock the power of touch typing with 12 meticulously crafted lessons designed for all skill levels. This course guides you from mastering individual keys to typing full sentences, numbers, and uppercase letters with confidence. Each lesson is structured to enhance your speed and accuracy, enabling you to type fluidly without looking at the keyboard. Why choose this course? - Structured progression: Move from beginner to advanced through guided exercises tailored for steady improvement. - Practice notes: Reinforce learning with lesson-specific typing notes to solidify your skills. - On-screen keyboard aid: A visual keyboard display simplifies practice, keeping you focused. - Flexible learning: Type along in a notepad while following audio instructions for an interactive, real-time experience. Your path to success: Consistent practice is key. The course's slow-paced, repetitive lessons build a strong foundation, allowing speed to develop naturally. Prioritize accuracy early on, and watch your proficiency soar. By the end, you'll type emails, reports, or even novels with precision and speed, supercharging productivity. Ideal for professionals, students, or writers seeking efficiency in 2025, this course equips you with skills to excel in any typing-intensive task. Enroll now to transform your typing abilities and stay ahead in a fast-paced digital world. Boost your career today. [b]Who this course is for:[/b] Beginner typists who have never learned proper touch typing. Anyone who wants to increase their typing speed and accuracy for personal or professional use. Students and professionals who need to type faster and more efficiently for work, study, or creative projects. [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Generative AI for data analytics | Udemy [Update 01/2025][/b] English | Size: 2.2 GB Genre: eLearning[/center] Learn how to use ChatGPT to analyze data, and to build expertise in data science, math, coding, and statistics [b]What you'll learn[/b] How to access ChatGPT Using ChatGPT to help learn data science ChatGPT to help debug your code ChatGPT to interpret statistical results Using ChatGPT to help communicate data science results How ChatGPT can help you with machine learning What AI-assisted data science means Artificial Intelligence (AI) is Increasingly Dominating Technology and Has Major Implications for Society Artificial Intelligence (AI) has emerged as a key driving force behind technological advancements in the 21st century. From voice assistants to self-driving cars, AI is transforming industries and revolutionizing the way we live, work, and communicate. The rapid development of AI technologies has far-reaching implications for society, with the potential to reshape the global economy, job market, and ethical considerations. As AI continues to dominate the tech landscape, it is essential for individuals and organizations alike to stay informed about the latest advancements and understand the impact AI can have on various aspects of our lives. You Need to Understand AI-Assisted Data Science Data science is at the heart of the AI revolution, and understanding AI-assisted data science is crucial for professionals who want to excel in this domain. By harnessing the power of AI-driven tools like ChatGPT, data scientists can automate routine tasks, uncover hidden patterns in data, and generate actionable insights more efficiently. AI-assisted data science empowers professionals to make data-driven decisions, optimize business processes, and drive innovation across industries. By mastering AI-assisted data science techniques, you'll not only enhance your skill set but also future-proof your career in this fast-evolving field. Introducing ChatGPT: a groundbreaking AI technology that's revolutionizing the way we learn and implement data science Imagine having access to a virtual assistant that not only understands complex data science concepts, but also helps you apply them in real-world scenarios. ChatGPT (produce by OpenAI and based on deep learning) offers exactly that, enabling users to ask questions, generate code from prompts, and communicate their findings effectively. By harnessing the power of ChatGPT, you can accelerate your learning, enhance your problem-solving and data visualization skills, and become a more proficient data scientist. Get ready to embark on an exciting journey that will open up new possibilities in the world of data science, making the learning process more engaging and efficient than ever before. Course Overview Welcome to this comprehensive course on using ChatGPT (sometimes written Chat GPT or chatgpt) to enhance your data science abilities. Discover the power of AI-assisted learning to elevate your understanding of machine learning, business analytics, and statistics. This course is carefully designed to provide you with the knowledge and practical skills needed to stay ahead in the rapidly evolving world of data science. In this course, you will learn how to: Utilize ChatGPT to improve your coding abilities in data science and machine learning projects Maximize your learning potential with AI-assisted guidance in the fields of business analytics and statistics Communicate complex data-driven findings effectively using ChatGPT's natural language processing capabilities Adapt to the emerging trends in data science and navigate the age of AI with confidence Use prompt engineering to get the best results from ChatGPT Course Structure The course is divided into four main content sections, each focusing on a different aspect of harnessing ChatGPT for data science mastery: ChatGPT for Coding - Learn how to leverage ChatGPT's AI-generated code to enhance your programming skills, streamline your workflow, and improve the efficiency of your data science projects, especially those involving big data, data mining, modeling, and feature engineering ChatGPT for Learning - Discover how AI-assisted learning can help you absorb new concepts, techniques, and tools in data science, machine learning, business analytics, and statistics ChatGPT for Communicating - Master the art of communicating complex data-driven insights to both technical and non-technical audiences using ChatGPT's natural language generation capabilities Data Science in the Age of AI - Explore the future of data science in the context of AI advancements and understand how to stay ahead of the curve in this rapidly evolving landscape Unique aspects of this course Pioneering approach: The course presents a groundbreaking perspective on using ChatGPT for data science, offering learners a chance to stay ahead of the curve in this rapidly evolving field. Comprehensive coverage: The course covers a wide range of topics, including ChatGPT for coding, learning, communicating, and understanding the broader implications of data science in the age of AI. Hands-on learning: The course provides students with practical examples and exercises that showcase how ChatGPT can be effectively used in real-world data science applications. Accessible to diverse audiences: Whether you're a student, a data science professional, or someone simply curious about AI, this course caters to various learning needs and backgrounds. Expert instruction: Learn from an experienced data scientist who understands the potential of ChatGPT and can effectively guide you through the nuances of AI-assisted data science. Future-proofing your skills: By mastering the use of ChatGPT in data science, you'll not only elevate your current skill set, but also ensure that you're well-prepared for the ongoing AI revolution in the job market. Active community: Engage with like-minded learners and professionals through course forums, fostering collaboration, networking, and the exchange of ideas related to ChatGPT and data science. Who is your instructor? I am Mike X Cohen, a former neuroscience professor (I left that job to teach online full-time). I'm a bestselling and highly rated instructor on Udemy. I've taught over 250,000 students the foundations of scientific programming, data analysis, and applied mathematics, and I've written several textbooks on programming and data analyses. I've also been studying and using deep learning for 20 years, and I've thought a lot about how to use AI-assistance, and ChatGPT in particular with prompt engineering, to optimize and customize teaching people about data and coding. I worked really hard to make this course a great learning experience for you. Check out what some of my students have said about my other courses: ** 'Best teacher ever. I am a psychologist and I didn't have mathematical training as an undergrad, but the books and lectures of Dr. Cohen have been life saving' ** 'What I REALLY like about Mike's style is that not only clear and direct, but he mixes in appropriate amounts of foreshadowing . to make it easier for me to connect the dots.' ** 'Mike X Cohen's courses are by far the best ones I've done in Udemy.' Why Choose This Course? By enrolling in this course, you will gain a competitive edge in the data science field by learning how to harness the power of ChatGPT. Stay ahead of the curve and boost your data science skills with AI-assisted learning. Enroll now and start your journey towards data science mastery with ChatGPT. What Should You Do Now? Check out the free preview videos, and the reviews of this course. Join the course to start your new life in AI-assisted data science. [b]Who this course is for:[/b] Students who want to use ChatGPT to learn more, faster Data science professionals who want to up their game Business leaders who want to know about AI-assisted data approaches Clients who want to know how ChatGPT will benefit them AI enthusiasts who want to learn about the potential impact of AI on data Data science enthusiasts who want to learn how to code with ChatGPT [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Bash Script Flow and Basic Utilities | Pluralsight[/b] English | Size: 113.91 MB Genre: eLearning[/center] Scripting is a command line force multiplier. Think note taking, but with executable notes! Bash has all the basics: control flow, loops, and commands to dissect data. [b]What you'll learn[/b] Stop digging through command history and/or internet searching to rebuild the commands you lost. In this course, Bash Script Flow and Basic Utilities, you'll learn how to build simple, reusable scripts! First, you'll explore control flow to conditionally execute commands. Next, you'll discover looping over data with for, while, and until loops. Finally, you'll learn how to dissect text files with commands including grep, cut/sort, head/tail, and tr. When you're finished with this course, you'll be confident writing Bash scripts that make your command-line work faster, more reliable, and reusable. [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Angular: Making HTTP Requests | Pluralsight[/b] English | Size: 185.11 MB Genre: eLearning[/center] Connect Angular to REST APIs with ease. This course will teach you to master HTTP requests, perform CRUD operations, handle errors, and use interceptors for authentication and logging in Angular applications. [b]What you'll learn[/b] Connecting Angular applications to REST APIs can be challenging without a solid understanding of HTTP communication. In this course, Angular: Making HTTP Requests, you'll gain the skills needed to integrate APIs seamlessly into your Angular applications. First, you'll explore how to configure Angular's HttpClient to interact with REST APIs. Next, you'll learn to perform GET, POST, PUT, and DELETE operations for effective data management. Finally, you'll discover how to handle errors using HttpErrorResponse, retry failed requests, and implement HTTP interceptors for tasks like authentication and logging. When you're finished with this course, you'll have the knowledge and hands-on experience with Angular's HTTP features needed to build reliable, API-driven applications. [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Black Box Model Explainability | Pluralsight[/b] English | Size: 147.33 MB Genre: eLearning[/center] Do you ever wonder why your AI makes certain decisions? This course demystifies black box models, teaching you practical explainability techniques like LIME and SHAP to build transparent, trustworthy AI. [b]What you'll learn[/b] Complex AI models often function as "black boxes," creating real challenges for debugging, stakeholder communication, and ethical deployment. In this course, Black Box Model Explainability, you'll begin to understand why your AI makes particular decisions, shedding light on these intricate systems. First, you'll explore the characteristics and inherent challenges of black box models like SVMs and neural networks, and grasp why explainability is absolutely critical in today's AI landscape - from building trust to ensuring fairness. Next, you'll discover the different approaches to making models understandable, differentiating between intrinsic and post-hoc techniques, and see why the latter are essential for the complex models we often rely on. Finally, you'll learn to apply and evaluate key explainability techniques -- specifically LIME for intuitive local insights and SHAP for robust, game theory-backed explanations of your model's behavior. When you're finished with this course, you'll have the foundational skills and knowledge to choose and apply appropriate explainability methods, enabling you to understand, debug, and communicate how your complex AI models make decisions. [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Write Reliable and Reusable T-SQL Code | Pluralsight[/b] English | Size: 104.08 MB Genre: eLearning[/center] SQL Server is one of the most popular database systems out there being used by enterprises of all sizes, verticals, and regions. This course will teach you how to improve your T-SQL code by making it reusable and more reliable. [b]What you'll learn[/b] Complex business requirements in SQL Server often require individual code so they can be fulfilled in an efficient and performant way. In this course, Write Reliable and Reusable T-SQL Code, we'll look into ways how you can make your T-SQL code more stable. First, you'll explore what ways of creating reusable code exist in T-SQL. Next, you'll discover the difference between functions and stored procedures and when to use which. Finally, you'll learn how to handle errors in your code, making it more reliable. When you're finished with this course, you'll have the skills and knowledge of the basics on writing reliable and reusable T-SQL code. [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Windows Server 2025 Virtualization and Hyper-V | Pluralsight[/b] English | Size: 262.12 MB Genre: eLearning[/center] Learn to deploy and manage Hyper-V and containers in Windows Server 2025. This course covers Virtual Machine (VM) setup, container management with Docker, and creating highly available VMs with clustering to streamline server and app virtualization. [b]What you'll learn[/b] IT administrators have many issues with deploying and managing many physical servers and applications. The solution is to utilize Windows Server 2025 Hyper-V and containers. In this course, Windows Server 2025 Virtualization and Hyper-V, you'll learn to deploy Hyper-V and containers on a Windows 2025 server. First, you'll explore installing Hyper-V on a virtual machine host, including installing virtual machines and replicating them. Next, you'll discover how to install containers on a Windows server and manage them using Docker and Docker Desktop. Finally, you'll learn how to deploy highly available virtual machines using failover clustering. When you're finished with this course, you'll have the skills and knowledge to determine the advantages and readiness needed to manage virtual machines and containers on a Windows 2025 server. [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Proxmox Hands-On Masterclass - From Beginner to Expert | Udemy [Update 08/2025][/b] English | Size: 4.79 GB Genre: eLearning[/center] Master Virtualization: Proxmox VE & Backup Server, VMs & Linux Containers, Clustering, Ceph, Command-Line & Automation [b]What you'll learn[/b] Understanding Proxmox VE: Concepts such as virtual machines or Linux containers Installation of Proxmox VE - Setting up a lab environment Managing Virtual Machines, Linux Containers & Docker Containers Mastering Clustering & High Availability Administrating Proxmox Backup Server Mastering Ceph Storage Understanding and Configuring Software Defined Networking (SDN) Automation of tasks via the Command-Line, API, Ansible & Terraform Security Hardning: Practical Tips for Operation Migration from VMware ESXi to Proxmox Hands-On Exercises Welcome to the "Proxmox Hands-On Masterclass - From Beginner to Expert"! Are you a sysadmin, DevOps engineer or starting out in the IT industry? Do you want to learn how to deploy and manage a complete virtualization environment from the ground up? Or do you already have basic knowledge of Proxmox VE and want to take your skills to the expert level? Then this course is just right for you! This course is all about Proxmox VE, the open source solution for virtualization. We will teach you Proxmox VE from beginner to expert in an understandable and practical way. No dry theory, no endless presentations - we focus on the essentials and demonstrate Proxmox VE within live demos. Our agenda includes topics such as: Understanding Proxmox VE: Concepts such as virtual machines or Linux containers Installation of Proxmox VE - Setting up a lab environment Managing Virtual Machines, Linux Containers & Docker Containers Mastering Clustering & High Availability Administrating Proxmox Backup Server Mastering Ceph Storage Understanding and Configuring Software Defined Networking (SDN) Automation of tasks via the Command-Line, API, Ansible & Terraform Security Hardening: Practical Tips for Operation Migration from VMware ESXi to Proxmox Our Hands-On Exercises and practice-oriented videos will help you to put what you have learned into practice. You will understand how to efficiently provision virtual resources and automate individual tasks. You will master advanced features including Clustering & High Availability, Ceph Storage, Proxmox Backup Server, and Software Defined Networking. Be it via the command line, via API, or with automation tools like Ansible and Terraform. Take this time to master the entire Proxmox ecosystem. Get started with our course today and expand your skills in the world of VM and container management. Upon completion, you will be able to use Proxmox VE confidently and effectively, whether for your own home lab or for complex IT projects in an enterprise environment. Are you ready to master the world of virtualization? Then enrol now and learn Proxmox in an easy-to-understand and practical way! [b]Who this course is for:[/b] Anyone who wants to learn Proxmox from scratch. IT technicians who would like to get to know an alternative to their existing virtualization solution. Proxmox VE users who want to get to know Proxmox Backup Server. Proxmox VE users who want to get to know the topic of "Clustering & High Availability". IT technicians who want to expand their Proxmox knowledge. [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Coding a C compiler in Javascript | Udemy [Update 08/2025][/b] English | Size: 8.5 GB Genre: eLearning[/center] Learn all steps of compiler design in one course, and learn to write a C compiler in Javascript. [b]What you'll learn[/b] Learn how to write a lexer which turns the C code into tokens, the smallest atomic parts of a programming language. Learn how to write a code generator, which takes your AST as input and emits a complete Assembly program that you turn into an executable .EXE or .ELF file. Learn to write a parser which parses the C code, through the tokens, and turning it into a data structure your program understands. Extra: Learn to create your own regular expression library that works not just with strings, but with any datatype as input. Learn to create an abstract syntax tree (AST), the primary data structure of any compiler. Extra: Learn how to write a transpiler (or pre-compiler) which adds functionality to Javascript itself. Extra: You will also learn the basics and intermediates of Typescript, a popular Javascript add-on. Everything you learn about compilers in this course, will work with any languages, not just Javascript and C. Coding a C compiler in Javascript In this exciting new project we'll be coding a real C compiler in Javascript. The first version will be able to parse a few commands and when all the steps are done (lexing, defining grammar, parsing, generating an AST, emitting code and writing the compiler driver) we will add new functionality, one command at the time. You will learn every step of compiler design in this 15 episode course. In addition to this, you will also learn how to build your own, datatype-independent regular expression library and also a transpiler/pre-compiler for JS/TS code. Prerequisites To follow along in this project you need a basic understanding of Javascript. That's it. Everything Node- or C or Typescript related will be explained at every step. Operating systems This project will work equally well in Windows, Mac OS X or Linux. All you need is Node.js and Nasm. Just follow the instructions from the intro. Happy coding! About the author Dr. Jonas is an experienced instructor who's been coding for 25 years and teaching for almost ten years. His popular Youtube channel has almost 50 000 subscribers and he's also running his own web TV channel with programming content. He's an appreciated teacher with stunning reviews and several programming courses of different kind. Enroll Today! Or check out the two hours of free previews. [b]Who this course is for:[/b] This course is for Javascript developers who wishes to learn compiler design. This course is also for C developers who wishes to learn compiler design. [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]LLM Fine-Tuning Mastery: Basic to Advance & Cloud AI [2025] | Udemy [Update 07/2025][/b] English | Size: 4.4 GB Genre: eLearning[/center] Professional LLM Fine-Tuning: LoRA, QLoRA, RLHF -DPO Techniques,Hugging face + Azure, AWS, GCP Cloud Deployment [b]What you'll learn[/b] Use LoRA and QLoRA adapters to fine-tune BERT, GPT, Llama, Mistral and DeepSeek with minimal GPU memory. Run RLHF Direct Preference Optimization workflows to align model outputs with human feedback. Perform supervised instruction tuning to build domain datasets and update weights for task-specific accuracy gains. Compress large teachers into efficient students via knowledge distillation, transferring soft targets and hidden-feature signals. Master the complete spectrum of Large Language Model fine-tuning with the most comprehensive hands-on course available today. This intensive program transforms you from foundational concepts to enterprise-level deployment, covering cutting-edge techniques across multiple architectures and cloud platforms. What You'll Learn Advanced Fine-Tuning Methodologies: Master LoRA (Low-Rank Adaptation) for parameter-efficient training that reduces computational costs while maintaining model performance23 Implement QLoRA (Quantized LoRA) for memory-optimized fine-tuning in resource-constrained environments Deploy RLHF (Reinforcement Learning ) to create aligned AI systems that follow human preferences Apply DPO (Direct Preference Optimization) for improved model behavior without complex reinforcement learning pipelines Apply Model Distillation for Knowledge transfer from a large model to a smaller model Multi-Architecture Model Training: Fine-tune BERT models for specialized text understanding and classification tasks Customize Mistral models for domain-specific applications requiring efficient performance Adapt GPT architectures for conversational AI text generation systems Optimize LLaMA models for professional-grade applications Configure Cohere models for production-ready natural language processing workflows Deploy on Hugging Face Hub: Master model uploading, versioning, and sharing using push_to_hub() functionality for seamless model distribution Enterprise Cloud Platform Mastery: Azure AI Foundry: Build, deploy, and manage enterprise-grade AI applications with integrated development environments AWS Bedrock: Implement scalable fine-tuning workflows using S3, Lambda, and API Gateway for AI-powered applications GCP Vertex AI: Leverage parameter-efficient tuning and full fine-tuning approaches with supervised learning methodologies Key Learning Outcomes Transform your AI expertise through hands-on projects that simulate real-world enterprise scenarios. Experience comprehensive dataset preparation, from raw data to production-ready training formats. Master performance optimization techniques including hyperparameter tuning, model evaluation metrics, and cost management strategies across cloud platforms. Build end-to-end deployment pipelines that scale from prototype to enterprise production environments. Course Journey Begin with transformer architecture fundamentals before progressing through parameter-efficient training methodologies. Each technique is reinforced through practical coding sessions using industry-standard datasets and real-world use cases. Experience comprehensive cloud platform integration across Azure, AWS, and GCP ecosystems, learning platform-specific optimization strategies and cross-platform migration techniques. Who Should Enroll Designed for intermediate to advanced AI practitioners, including machine learning engineers, data scientists, AI researchers, and software developers seeking specialization in LLM customization. Basic Python programming knowledge and familiarity with machine learning concepts are recommended. [b]Who this course is for:[/b] Fine tune LLMs [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Master Pandas and Python for Data Handling [2025] | Udemy [Update 08/2025][/b] English | Size: 7.95 GB Genre: eLearning[/center] Learn to Master Python, Pandas and Advanced Data Handling for Data Analysis, Data Science, and Machine Learning [b]What you'll learn[/b] Master Python programming with Python's native data structures, data transformers, functions, object orientation, and logic Master the Pandas library for Advanced Data Handling Perform Advanced Data Handling Manipulate data and use advanced multi-dimensional uneven data structures Use Python's advanced object-oriented programming and make your own custom objects, functions and how to generalize functions Use the language and fundamental concepts of the Pandas library and to handle all aspects of creating, changing, modifying, and selecting Data from a Pandas D Use file handling with Pandas and how to combine Pandas DataFrames with Pandas concat, join, and merge functions/methods Perform advanced data preparation including advanced model-based imputation of missing data and the scaling and standardizing of data Make advanced data descriptions and statistics with Pandas. Rank, sort, cross-tabulate, pivot, melt, transpose, and group data [Bonus] Make advanced Data Visualizations with Pandas, Matplotlib, and Seaborn Use and design advanced Python constructions and execute detailed Data Handling tasks with Python incl. File Handling [Cloud computing]: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources. Option: To use the Anaconda Distribution (for Windows, Mac, Linux) Option: Use Python environment fundamentals with the Conda package management system This two-in-one video course will teach you to master Python 3, Pandas 2-3, and Data Handling. Python 3 is one of the most popular programming languages in the world, and Pandas 2 and future 3 is the most powerful, efficient, and useful Data Handling library in existence. You will learn to master Python's native building blocks and powerful object-oriented programming. You will design your own advanced constructions of Python's building blocks and execute detailed Data Handling tasks with Python. You will learn to master the Pandas library and to use its powerful Data Handling techniques for advanced Data Science, Statistics, and Machine Learning Data Handling tasks. The Pandas library is a fast, powerful, flexible, and easy-to-use open-source data analysis and data manipulation tool, which is directly usable with the Python programming language. You will learn to: Master Python programming with Python's data structures, data transformers, functions, object orientation, and logic Use and design advanced Python constructions and execute detailed Data Handling tasks with Python incl. File Handling Use Python's advanced object-oriented programming and make your own custom objects, functions and how to generalize functions Manipulate data and use advanced multi-dimensional uneven data structures Master the Pandas library for Advanced Data Handling Use the language and fundamental concepts of the Pandas library and to handle all aspects of creating, changing, modifying, and selecting Data from a Pandas DataFrame object Use file handling with Pandas and how to combine Pandas DataFrames with Pandas concat, join, and merge functions/methods Perform advanced data preparation including advanced model-based imputation of missing data and the scaling and standardizing of data Make advanced data descriptions and statistics with Pandas. Rank, sort, cross-tabulate, pivot, melt, transpose, and group data [Bonus] Make advanced Data Visualizations with Pandas, Matplotlib, and Seaborn Perform Advanced Data Handling [Cloud computing]: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources. Option: To use the Anaconda Distribution (for Windows, Mac, Linux) Option: Use Python environment fundamentals with the Conda package management system and command line installing/updating of libraries and packages - golden nuggets to improve your quality of work life. And much more. This course is an excellent way to learn to master Python, Pandas and Data Handling! Data Handling is the process of making data useful and usable for data analysis. Most Data Scientists and Machine Learning Engineers spends about 80% of their working efforts and time on Data Handling tasks. Being good at Python, Pandas, and Data Handling are extremely useful and time-saving skills that functions as a force multiplier for productivity. This course is designed for anyone who wants to: learn to Master Python 3 from scratch or the beginner level learn to Master Python 3 and knows another programming language reach the Master - intermediate Python programmer level as required by many advanced Udemy courses in Python, Data Science, or Machine Learning learn Data Handling with Python learn to Master the Pandas library learn Data Handling skills that work as a force multiplier and that they will have use of in their entire career learn advanced Data Handling and improve their capabilities and productivity Requirements: Everyday experience using a computer with either Windows, MacOS, iOS, Android, ChromeOS, or Linux is recommended Access to a computer with an internet connection Programming experience is not needed and you will be taught everything you need The course only uses costless software Walk-you-through installation and setup videos for Cloud computing and Windows 10/11 is included This course is the course we ourselves would want to be able to enroll in if we could time-travel and become new students. In our opinion, this course is the best course to learn to Master Python, Pandas, and Data Handling. Enroll now to receive 25+ hours of video tutorials with manually edited English captions, and a certificate of completion after completing the course! [b]Who this course is for:[/b] Anyone who wants to learn to Master Python 3 from scratch or the beginner level Anyone who wants to learn to Master Python 3 and knows another programming language Anyone who wants to reach the Master - intermediate Python programmer level as required by many advanced Udemy courses in Python, Data Science, or Machine Learning Anyone who wants to learn Data Handling with Python Anyone who wants to learn to Master the Pandas library Anyone who wants to learn Data Handling skills that work as a force multiplier and that they will have use of in their entire career Anyone who wants to learn advanced Data Handling and improve their capabilities and productivity [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Complete Python with AI Skills to Get Your Dream IT Job | Udemy [Update 08/2025][/b] English | Size: 12.5 GB Genre: eLearning[/center] Master Python for Data Science, AI, Machine Learning, Web Development, Game Development, Cybersecurity, and GUI! [b]What you'll learn[/b] You will acquire the fundamental Python skills required for roles in data science, web development, AI, and cybersecurity. You will gain a solid understanding of object-oriented programming, which is the foundation of building scalable and reusable Python applications. These core Python skills will help you explore advanced fields like machine learning, deep learning, blockchain development, and ethical hacking. By completing this course, you'll be able to build projects using Flask, Django, Tkinter, and even create games with Pygame. You will learn how to work with databases, build REST APIs, and scrape real data from websites using Python web scraping tools. You will also gain hands-on experience in creating AI models using TensorFlow, PyTorch, and Neural Networks, and learn how to apply them in real-world problems. You will prepare for real-world job success with guidance on portfolio building, resume writing, and technical interview readiness. Welcome to the Complete Python with AI Skills to Get Your Dream IT Job - your all-in-one learning experience designed to take you from a beginner programmer to a highly skilled Python developer, equipped for real-world careers in data science, machine learning, artificial intelligence, web development, cybersecurity, and more. Whether you're looking to write your first line of Python code or expand your skills into advanced topics like deep learning, blockchain, or cloud computing, this course provides the training, tools, and projects to help you succeed. You'll start with programming fundamentals and object-oriented programming using Python, and then advance through hands-on projects in data analytics, neural networks, Python game development using Pygame, GUI development with Tkinter, and web development with Flask, Django, and custom-built Python APIs. You'll gain practical experience using NumPy, TensorFlow, and PyTorch, and apply your knowledge to real-world projects like AI prediction tools, secure login systems, portfolio websites, and even your own Python blockchain. If your goal is to enter the world of cybersecurity, you'll also learn ethical hacking, secure coding, encryption, and how to monitor system logs using Python for cybersecurity. You'll build your understanding from the ground up while working on engaging use cases like brute-force simulators, file encryption tools, and real-time web scrapers. Beyond coding, this course helps you build a professional portfolio, write a strong resume, and prepare for job interviews with confidence. We'll guide you through showcasing your best projects on GitHub, explaining your code clearly, and answering key technical and behavioral questions during interviews. By the end of this course, you'll not only master complete Python programming - you'll be ready for roles in AI, data science, web scraping, ethical hacking, cloud development, and more. Whether you're aiming for a promotion, a new career, or to become a full stack Python developer, this course will help you get there. Why Enroll in This Course? Lifetime Access: Learn at your own pace with unlimited access and free updates forever. Project-Based Learning: Build real apps in AI, games, web, GUI, and cybersecurity. All-in-One Python Path: Covers data science, machine learning, APIs, and full stack. Career-Ready Skills: Get tools for portfolios, resumes, and technical interviews. Community Support: Ask questions and get help from instructors and fellow learners. No Prior Experience Needed: Start from zero and go to expert - step by step. Versatile Use Cases: Code for automation, web scraping, blockchain, and more. Updated for Today's Jobs: Aligned with industry trends and hiring needs. Get ready to learn, build, and transform your future. Enroll now in the Complete Python with AI Skills to Get Your Dream IT Job and take the first step toward your dream IT job. [b]Who this course is for:[/b] Anyone who wants to start a career in Python programming This Python course is designed to take you from a beginner to an expert level Anyone who wants complete Python training to get a job in IT, AI, or Web Development Anyone who wants to master Python for data science, machine learning, cybersecurity, or game development Anyone who wants help and guidance in resume building and job interview preparation [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Master System Design & Software Architecture: Basic-Advanced | Udemy [Update 08/2025][/b] English | Size: 4.24 GB Genre: eLearning[/center] Learn Software Architecture, System Design, Microservices & AWS to build scalable, reliable, secure systems. [b]What you'll learn[/b] Master System Design Principles & Software Architecture Concepts - Learn Scalability, Reliability, Availability, Performance, Security to Build Resilient System Dive into Architectures + Microservices Architectural Patterns. Deep into Protocols/Implementations: gRPC, GraphQL, AMQP, RabbitMQ, Kafka, SQS, SNS, Streaming Leverage AWS: Hands-on practicals with EC2, S3, RDS, Lambda, VPC, IAM, CloudFront CDN and More, to implement cloud-based architectural solutions with resilence Learn Important Architectural Concepts - Stateful/stateless, Load Balancers, Fault Tolerance, Redundancy, Replication, Sharding, Partitioning, Consistency etc. AWS and Node.js Examples for Protocols/Implementations: REST, gRPC, GraphQL, RabbitMQ, Kafka, SQS, SNS etc. Are you ready to advance your career from a developer to a software architect and transition from coding applications to architecting large-scale, high-performance systems? This Software Architecture Course provides a complete journey, from mastering the fundamentals of software architecture and system design for developers to leveraging AWS cloud-native services in real-world scenarios. This hands-on, in-depth software architecture online course equips you with the technical skills, architectural mindset, and cloud expertise needed to design scalable, resilient, and cost-effective systems that meet modern enterprise needs. What You'll Learn: Roles and Responsibilities: Understand the key differences between Software Architect vs. Solutions Architect. Explore Software Architecture vs. System Design. Learn how to build and maintain an Architectural Vision. AWS Cloud-Native Services: Amazon IAM: User creation, role policies, and enabling MFA. Cost Management: AWS Pricing Calculator, Budgets, and Free Tier usage. Amazon EC2: Instance Types, EBS, Pricing Models (On-Demand, Reserved, Dedicated, and Savings Plans). Storage Services: Amazon S3, S3 Storage Classes, Access Policies; EBS Volumes; and Amazon EFS. Networking: Amazon VPC, Subnets, IGWs, and Availability Zones. Load Balancing: ALB, NLB, and ELB with EC2 integration and cost analysis. Databases: Amazon RDS (MySQL, Aurora), DynamoDB setup, and real EC2 connections. Serverless: Build AWS Lambda functions with S3 triggers and CloudWatch logging. API Gateway: Create and manage REST APIs and explore integration options. Important System Design Concepts: Stateful vs. Stateless Architectures Load Balancer vs. Reverse Proxy Fault Tolerance, Redundancy, Replication Failure Detection & Recovery, Rollback vs. Roll Forward Retry Mechanism, Timeouts, Health Checks, Fallback Mechanism Rate Limiting Database Redundancy, Partitioning, Sharding Database Consistency Models, Consistent Hashing Communication Protocols & Messaging: HTTP Versions, REST, gRPC, GraphQL AMQP, RabbitMQ, Apache Kafka Event-Driven & Data Streaming Systems Amazon SQS, Amazon SNS, Amazon EventBridge WebSockets Architectural Styles & Patterns: Client-Server, Layered (n-tier), Component-Based, Monolithic, Service-Oriented Architecture (SOA), Microservices Architecture Domain-Driven Design (DDD) Microservices Core Concepts: Service Discovery, Load Balancer, API Gateway Service Mesh, Configuration Server, Database Per Service Circuit Breaker Pattern, SAGA Pattern, CQRS, Event Sourcing Choreography Pattern, Aggregator Pattern, Backend for Frontend (BFF) Comparison: Monolith vs Microservices SOA vs Microservices Migration Techniques: Decomposition Strategies Strangler Pattern Serverless Architecture Design Patterns and AWS Compute Services Security: Authentication vs Authorization Multi-Factor Authentication (MFA), Single Sign-On (SSO) Role-Based Access Control (RBAC) AWS IAM Policies - Identity, Resource, and Session-based Shared Responsibility Model JWT (JSON Web Tokens) - Creation and Validation Amazon Cognito, OAuth 2.0 vs OpenID Connect (OIDC) Scalability: Vertical vs. Horizontal Scaling Auto Scaling with Amazon EC2 and ELB AWS Application Auto Scaling Relational Database Scalability: Challenges and Solutions Scalability with Amazon RDS, Aurora, and DynamoDB Best Practices for Scalable Design Reliability: Purpose, Benefits, and Trade-Offs Measuring MTBF (Mean Time Between Failures) and MTTF (Mean Time to Failure) Building a Business Continuity Plan (BCP) and Disaster Recovery Strategy Ensuring Network Reliability and Security Availability: Impacts and Challenges of Availability Response Time Optimization Active-Active vs. Active-Passive Clustering Availability Implementation Using: Amazon EC2, Amazon S3 Amazon RDS, Amazon Aurora Amazon DynamoDB Globally Distributed Applications Multi-Region Deployment CDN via Amazon CloudFront Performance: Understanding Metrics: Speed, Latency, Throughput, Bandwidth Using CloudWatch Metrics for Monitoring Concurrency vs. Parallelism Load Shedding, Request Batching Lazy Loading vs. Eager Loading Deployment Considerations AWS-Specific Performance Tuning: EC2 Placement Groups Millisecond Latency Techniques By the end of this Software Design and Architecture Course, you'll be equipped with the expertise to lead architecture decisions, design scalable cloud solutions, and deliver high-performing software systems for enterprise needs. Who this course is for: Developers or Senior Developers, who are passionate about advancing their careers in technology and want to learn System Design and Software Architectures. Developers who want to gain hands-on experience with cloud-native services in the AWS platform. [b]Who this course is for:[/b] Developers or Senior Developers, who are passionate about advancing their careers in technology and want to learn System Design and Software Architectures. Developers who want to gain hands-on experience with cloud-native services in AWS platform [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b][NEW] Building Microservices with Spring Boot & Spring Cloud | Udemy [Update 08/2025][/b] English | Size: 15.29 GB Genre: eLearning[/center] Build Microservices using Java, REST API, Spring Boot 3, Spring Cloud, React JS, Kafka, RabbitMQ, Docker & IntelliJ IDEA [b]What you'll learn[/b] Learn REST API Fundamentals - REST API, Resource, Sub-resource, URI, HTTP methods, HTTP status codes, Design REST APIs, Best Practices, and REST API Differences Build REST API's using Spring Boot Build CRUD REST API's using Spring Boot, Spring Data JPA and MySQL Database Using DTO (Data Transfer Object) Pattern in Spring Boot App Using Mapping Libraries - ModelMapper and MapStruct Exception Handling in Spring Boot App Spring Boot REST API Validation Spring Boot Actuator - Production-Ready Features Building Spring Boot Microservices in IntelliJ IDEA Microservices Communication using RestTemplate, WebClient and Cloud OpenFeign Centralized Configurations using Spring Cloud Config Server Create Service Registry and Discovery using Spring Cloud Netflix Eureka Create API Gateway using Spring Cloud Gateway Load balancing with Eureka server and Open Feign using Spring Cloud LoadBalancer Auto Refresh Config Changes using Spring Cloud Bus Distributed Tracing with Spring Cloud Sleuth and Zipkin Resilience4J: Circuit Breaker, Retry and RateLimiter Patterns How to Add Step by Step New Microservice to Existing Project Create React Frontend Microservice and Integrate with Backend Microservices Dockering Spring Boot Application Step by Step Dockering Spring Boot MySQL CRUD Application Step by Step Docker Compose for Dockering Spring Boot Application Step by Step Learn How to Use Apache Kafka in the Spring Boot App Spring Boot + Apache Kafka Real-World Wikimedia Project Event-Driven Microservices using Spring boot and Kafka Learn How to Use RabbitMQ in the Spring Boot App Event-Driven Microservices using Spring boot and RabbitMQ REST API Documentation using SpringDoc OpenAPI (Swagger) Library Migrate Existing Microservices Project into Latest Version Build Spring Boot React JS Full-Stack CRUD Web Application Learn Functional Programming in Java Disclaimer: "This course requires you to download Docker Desktop from the official Docker website. If you are a Udemy Business user, please check with your employer before downloading software." In this course, you will learn to build Microservices using Java, Spring Boot, Spring Cloud, React, Kafka, RabbitMQ, Docker, and REST API (REST Web Services). Important Note: This course supports the latest Spring Boot 3 and Spring Cloud 2022.0.0. In this course, we will follow the real-time industry-standard project development approach. This course covers Spring Boot REST API development from scratch. This course covers the REST API fundamentals from scratch. Microservices: A Microservice is a service built around a specific business capability that can be independently deployed. So, to build large enterprise applications, we can identify the sub-domains of our main business domain and build each sub-domain as a MicroService using Domain-Driven Design (DDD) techniques. But in the end, we need to make all these microservices work together to serve the end user as if it were a single application. Why are Spring Boot and Spring Cloud good choices for MicroServices? Spring Boot is the most popular and widely used Java framework for building Microservices. These days, many organizations prefer to deploy their applications in a Cloud environment instead of taking on the headaches of maintaining a data center themselves. However, we need to take good care of the various aspects of making our applications Cloud-Native. There comes the beauty of Spring Cloud. Spring Cloud is essentially an implementation of various design patterns for building Cloud-Native applications. Instead of reinventing the wheel, we can simply take advantage of various Spring Cloud modules and focus on our main business problem rather than worrying about infrastructural concerns. What you'll learn Build RESTful web services using Spring Boot - Learn Important Spring MVC Annotations. Build CRUD REST APIs using Spring Boot, Spring Data JPA, and MySQL Database. Building Spring Boot Microservices in IntelliJ IDEA Microservices Communication using RestTemplate, WebClient, and Spring Cloud OpenFeign Create Service Registry and Discovery using Spring Cloud Netflix Eureka Load balancing with Eureka server and Open Feign using Spring Cloud LoadBalancer Create an API Gateway using Spring Cloud Gateway Centralized Configurations using Spring Cloud Config Server Auto Refresh Config Changes using Spring Cloud Bus Distributed Tracing with Spring Cloud Sleuth and Zipkin Resilience4J: Circuit Breaker, Retry, and RateLimiter Patterns Adding a Step-by-Step New Microservice to an Existing Project Create React Frontend Microservice and Integrate with Backend Microservices Learn How to Migrate Existing Projects to the Latest Version Learn How to Generate REST API Documentation Dockering Spring Boot Application Step-by-Step Dockering Spring Boot MySQL CRUD Application Step-by-Step Docker Compose for Dockerizing Spring Boot MySQL CRUD Application Step-by-Step Event-driven Microservices using Spring Boot and Kafka Learn how to use RabbitMQ in the Spring Boot app. Learn how to use Kafka in a Spring Boot app. Kafka Spring Boot - Real-World Wikimedia Project Development Event-driven Microservices using Spring Boot and RabbitMQ Build a Spring Boot React JS Full-Stack CRUD Web Application Learn Functional Programming in Java Tools and technologies used: 1. Java 17+ 2. Spring Boot 3. Spring Cloud 4. Microservices 5. React 6. Resilience4J framework 7. Maven 8. IntelliJ IDEA 9. MySQL database 10. Postman 11. Kafka 12. RabbitMQ 13. Docker Sample amazing feedback from students on this course: Francis Dahryl N: " One of the best learning videos. Ramesh, the instructor, will guide every student until the end." Juan Paulo L: "Amazing course, well structured, well documented, resourceful, if you really want to learn about microservices, spring boot and spring cloud you have to take this course now!" Tirtha S: "One of the best course for Microservices. Extraordinary explanations to the point. Thank you for providing us such a great course and helping us to gather the knowledge which we are required to know about microservices architecture. You are the best and Thank you once again." Lakshman M: "I always admire you sir. You are an Inspiration & Guide to many Java Developers. Keep Doing More Udemy Courses Sir. Thank you" Furkan P: "This course teaches everything you need to start with microservices. You need a Java/Spring Boot background to follow up well! Great one!" Harsh S: "it is very good course if you want to get your hand dirty in the spring boot microservices" Vivek Yuvraj Pawar: "In this course the explanation is above my expectations. in this course all concepts are deeply explained" Sagar Talagatti: "Instructor explains the concepts very well and demonstrates with appropriate examples. Thank you for such a good course." ds r: "I have no words to describe how amazing this course is. Ramesh has explained everything in such an easy to understand manner. This course covers tremendous amount of great content at one single place. After building the Restful APIs, CRUD operations, building different microservices, spring cloud features etc., he included a step to create docker file and run everything in container. Also, two other projects about Spring Kafka and RabbitMQ are included as bonus! My only suggestion would be to include another video that shows how everything can be deployed on AWS EKS. This is the best microservices course on Udemy. Period." Priya Chondke: "its all good covered all topics in easiest way thank you for such an excellent course" Check out all the reviews/ratings for this course in the Reviews section of this course. [b]Who this course is for:[/b] This course for Java programmers who want to learn building RESTful Web services and Microservices using Spring Boot, Spring Cloud, Kafka, RabbitMQ and Docker. [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Event Driven Microservices Architecture with .NET and Docker | Udemy [Update 08/2025][/b] English | Size: 7.5 GB Genre: eLearning[/center] Learn how to build scalable and resilient systems like big companies do with Terraform, Azure, Docker, .NET | SQL |NoSQL [b]What you'll learn[/b] Understand the fundamentals of event-driven microservices architecture Design and implement infrastructure in Azure with Terraform to deploy scalable and secure microservices. Develop microservices in .NET using patterns such as CQRS and SAGA, applying dependency injection principles and event-based communication. Implement security and authentication in microservices using Microsoft Entra ID, ensuring secure access through tokens and API Gateway. Implement asynchronous communication between microservices using topics to ensure a decoupled and resilient architecture. Apply fault management and compensation strategies to microservices, ensuring consistency in distributed transactions using the SAGA pattern. Monitor and analyze microservices observability using telemetry, centralized logs, and metrics in Azure. Do you feel like your career as a .NET developer has stalled in the creation of APIs and CRUDs? Do you see job postings for Software Architects or Technical Leaders and know you're missing that "something" to take the leap? That "something" is the ability not only to write code, but also to design complete, scalable, and resilient systems that large companies demand today. It's the difference between being an implementer and being a leader or architect. This course is the bridge that will take you to that next level. You don't come here just to learn theory; you come here to Build. Together, we will implement a complete and functional event-driven Microservices system from scratch, simulating a real-world use case. At the end of the course, you will have a project deployed in the cloud that you can proudly display in your portfolio, demonstrating your experience with cutting-edge technologies. What will you learn? You will design modular and scalable architectures with .NET, leaving behind the problems of monoliths. You will implement asynchronous and resilient communication between microservices using a message broker. You will master the SAGA pattern to manage distributed transactions and ensure data consistency in the event of failures. You will automate cloud infrastructure (Azure) like a pro, using Terraform to define your environment as code. You will containerize and deploy your applications efficiently using Docker. You will strengthen the security of your microservices with modern authentication and authorization using Microsoft Entra ID. You will implement observability with metrics, logs, and traces to monitor and diagnose your production systems. Why choose this course? 100% Practical and Project-Oriented: Forget about isolated theory. Everything you learn can be directly applied in a comprehensive project. Cutting-Edge Technology: We work with the most modern and in-demand stacks: .NET, Docker, Terraform, Azure, Service Bus and more. Architect's Vision: I'll teach you not only how to write code, but also how to make design decisions, consider trade-offs, and defend your technical proposals. If you're ready to make the most important investment in your professional future and differentiate yourself from the rest, this is your moment. I'll be waiting inside so we can start building! [b]Who this course is for:[/b] .NET developers with a few years of experience who feel stuck and want to take the next big step in their career. Professionals aspiring to pursue a position as a Software Architect, Cloud Engineer, or Technical Leader. [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Ultimate DevOps to MLOps Bootcamp - Build ML CI/CD Pipelines | Udemy [Update 08/2025][/b] English | Size: 6.34 GB Genre: eLearning[/center] From Data to Deployment - Learn MLOps by Building a Real-World Machine Learning Project with MLflow, Docker, Kubernetes [b]What you'll learn[/b] Build end-to-end Machine Learning pipelines with MLOps best practices Understand and implement ML lifecycle from data engineering to model deployment Set up MLFlow for experiment tracking and model versioning Package and serve models using FastAPI and Docker Automate workflows using GitHub Actions for CI pipelines Deploy inference infrastructure on Kubernetes using KIND Use Streamlit for building lightweight ML web interfaces Learn GitOps-based CD pipelines using ArgoCD Serve models in production using Seldon Core Monitor models with Prometheus and Grafana for production insights Understand handoff workflows between Data Science, ML Engineering, and DevOps Build foundational skills to transition from DevOps to MLOps roles This hands-on bootcamp is designed to help DevOps Engineers and infrastructure professionals transition into the growing field of MLOps. With AI/ML rapidly becoming an integral part of modern applications, MLOps has emerged as the critical bridge between machine learning models and production systems. In this course, you will work on a real-world regression use case - predicting house prices - and take it all the way from data processing to production deployment on Kubernetes. You'll start by setting up your environment using Docker and MLFlow for tracking experiments. You'll understand the machine learning lifecycle and get hands-on experience with data engineering, feature engineering, and model experimentation using Jupyter notebooks. Next, you'll package the model with FastAPI and deploy it alongside a Streamlit-based UI. You'll write GitHub Actions workflows to automate your ML pipeline for CI and use DockerHub to push your model containers. In the later stages, you'll build a scalable inference infrastructure using Kubernetes, expose services, and connect frontends and backends using service discovery. You'll explore production-grade model serving with Seldon Core and monitor your deployments with Prometheus and Grafana dashboards. Finally, you'll explore GitOps-based continuous delivery using ArgoCD to manage and deploy changes to your Kubernetes cluster in a clean and automated way. By the end of this course, you'll be equipped with the knowledge and hands-on experience to operate and automate machine learning workflows using DevOps practices - making you job-ready for MLOps and AI Platform Engineering roles. [b]Who this course is for:[/b] DevOps Engineers looking to break into the field of MLOps Platform Engineers and SREs supporting ML teams Cloud Engineers wanting to understand ML workflows and productionization Developers transitioning into ML Engineering or Data Engineering roles Anyone curious about how real-world ML systems are deployed and scaled [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Maven - Building Gen AI Agents for Enterprise: Beyond the Hype [Update 05/2025][/b] English | Size: 3.8 GB Genre: eLearning[/center] Build Production-Ready SaaS Agents that work You're drowning in AI vendor promises and overlapping tools, wondering: "Which of these actually solves our problems?" After working with organizations across fintech, supply chain, and manufacturing, we've seen the same pattern: businesses know AI matters but can't identify use cases that deliver measurable ROI. This course cuts through the noise. You'll build production-ready GenAI SaaS Agents using no-code and low-code approaches-without needing a programming background. You will build full-scale websites with an AI backend. Two-Part Approach: No-code tools for building AI agents Low-code approaches for complex agent systems What Makes This Different We focus on the "what" before the "how"-use case identification, business value assessment, and strategic deployment over technical implementation. 7 Modules: From Concept to Demo Module 1: GenAI landscape and Industry impact Module 2: No-code agent building blocks (loveable & n8n) Module 3: Enterprise RAG with production guardrails Module 4: Vertical AI Agents and Orchestration Module 5: Deploying a production-ready website with an AI backend Module 6: Capstone workshop with peer feedback Module 7: Demo day-present your working system What you'll learn Master the what, why, and how of Generative AI by building Enterprise-Grade Agents that go beyond the basics and actually move the needle Deploy Your First Production Agent in 7 Weeks (with enterprise grade template) Get hands-on with use case identification workshops and business value scorecards Analyze real case studies from fintech, manufacturing, and consulting to recognize patterns of successful vs. failed implementations Use No-Code tools to build your first AI Agent Build NoCode AI Agents That Handle Real Business Workflows Master AgentPro and similar platforms to create multi-step agent workflows with memory, reasoning, and tool integration Implement guardrails and safety controls that meet enterprise compliance standards Deploy agents that can handle customer inquiries, data analysis, and document processing at scale Design Enterprise RAG Systems That Actually Return Relevant Results Apply advanced chunking strategies and embedding techniques to optimize information retrieval accuracy Build RAG systems with feedback loops that continuously improve relevance and user satisfaction Deploy AI Systems with Enterprise-Grade Safety and Scalability Configure monitoring dashboards that track system performance, costs, and user satisfaction metrics Implement multi-layered safety controls, including content filtering, output validation, and escalation protocols Design deployment architectures that scale efficiently while maintaining response quality Present and Defend Your AI Solution to Stakeholders Structure presentations using the Problem-Solution-Impact framework to communicate clearly to non-technical executives Develop implementation roadmaps with timeline, resource requirements, and success metrics for organizational buy-in Demo live systems during our capstone showcase, receiving feedback from peers and industry mentors [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Cursor AI: Web Design with AI Coding for Total Beginners | Udemy [Update 06/2025][/b] English | Size: 3.8 GB Genre: eLearning[/center] Create websites with Cursor without knowing how to code. Tell the AI what you need and watch how Cursor builds it! [b]What you'll learn[/b] Create and launch a fully functional website using AI and best design practices. Learn how to use AI tools like Cursor to build websites and applications without writing code Set up essential development tools (like Python, Node.js, GitHub, Vercel) to enable smooth AI-assisted project workflows. Troubleshoot common setup and AI output issues using logic, search, and prompt refinement strategies. Identify real-world use cases for vibe coding and begin building simple tools, landing pages, or startup ideas. Imagine building real websites and apps-without writing a single line of code. This isn't science fiction. It's vibe coding. And it's the most practical, future-proof skill you can learn today. What is Vibe Coding? Vibe coding means creating fully functional websites and apps using AI. You describe your idea in plain English, and powerful AI tools write the code for you. No programming experience needed. No technical jargon. Just results. In this course, you'll learn vibe coding using Cursor, one of the most advanced AI-powered development platforms available. It's like having a 24/7 team of senior developers at your fingertips-ready to build whatever you dream up. Why This Course? Beginner-friendly - No coding skills? No problem. We start from scratch. Hands-on approach - We build together. You'll create your own portfolio website in the first few lessons. Real-world outcomes - Build apps, websites, plugins, SaaS tools, and more-without hiring developers. AI as your co-pilot - Learn how to prompt, guide, and refine AI outputs to turn ideas into real products. Why Now? You're not just learning a skill-you're **gaining a first-mover advantage**. This space is exploding. The companies building these tools are already worth billions. But it's still early. The best time to dive in is now. Think of it like investing in Apple or Bitcoin at the beginning. It might be a bit messy, things might break-but that's where the opportunity is. If you wait until it's mainstream, you'll be one of thousands. Start now and lead the pack. What You'll Learn How to use Cursor to build apps from start to finish How to work with AI models like GPT-4, Claude, Gemini How to launch and host your website on your own domain How to turn small ideas into useful tools, apps, and businesses How to troubleshoot and adapt in a fast-moving AI ecosystem What Can You Do With This Skill? Freelance: Offer websites and tools to local businesses Get hired: Companies are looking for people who can build fast using AI Start a business: Launch your own product or SaaS platform Save money: Build what you need without hiring a developer We'll show you examples of regular people making thousands per month with simple ideas-like compressing images, renaming photos, or building niche WordPress plugins. It's Not Magic This course is real. It's not about shortcuts. You will get stuck. There will be bugs. You'll need patience. But that's the price of being early. If it were too easy, everyone would be doing it already. That's also what makes it such an incredible opportunity. Ready to Level Up? If you're serious about your future, if you want to gain an edge in a rapidly changing digital world, **this is your course**. You don't need to know how to code. You just need to be curious and committed. Learn vibe coding. Launch real projects. Join the future. Enroll now. Your future self will thank you. [b]Who this course is for:[/b] Designers who want to bring their ideas to life without needing to learn traditional coding. Aspiring entrepreneurs and freelancers looking to build websites, apps, or SaaS tools quickly and affordably with AI. Career changers and tech-curious beginners who want a future-proof skill without spending years learning to code. Marketing and business professionals who want to build landing pages, tools, or side projects without relying on developers. Students and self-learners interested in AI, web development, and digital creation who want to start building fast. [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]The RED Teaming Training Course | Udemy [Update 07/2025][/b] English | Size: 29.75 GB Genre: eLearning[/center] Learn Ethical Hacking to a Highly Advanced Level and Become Qualified to Get Certified [b]What you'll learn[/b] Advanced Ethical Hacking Techniques Red Team Operations Vulnerability Assessment and Exploitation Network Penetration Testing Disclaimer: Please be aware that this course consists of recordings from the live workshop titled "The RED Teaming Workshop (Exam & Labs)" as such the video may contain periods of inactivity or what appear to be "empty moments." Red Teaming, Ethical Hacking, and Penetration Testing play a pivotal role in cybersecurity. These activities mimic the tactics of malicious hackers to find system vulnerabilities, thereby bolstering an organization's defenses against cyber threats. While every aspect of cybersecurity is vital, the role of offensive security is especially critical in preventing hacking incidents. The in-depth Penetration Testing with Kali Linux (PWK/PEN-200) course provides comprehensive training in penetration testing methods, tools, and strategies, offering hands-on learning at your own pace. The OSCP (Offensive Security Certified Professional) certification, known for its technical depth, is unique in its requirement for demonstrable practical penetration testing skills, unlike many other ethical hacking certifications. Additionally, this program introduces Red Teaming methods essential for conducting effective Red Teaming operations. Participants to engage directly with real-world scenarios, enhancing their skills in identifying and exploiting security gaps. This course goes beyond theoretical knowledge, focusing on the practical application of penetration testing techniques within various environments. Designed to cultivate a deep understanding of how to assess, penetrate, and secure networks and systems using the comprehensive toolkit provided by Kali Linux. The OSCP certification, a key component of this course, sets a high standard in the field of cybersecurity. It demands not just knowledge, but the ability to apply that knowledge effectively in practical situations. This requirement distinguishes it from other ethical hacking certifications, emphasizing hands-on and real-world skills over theoretical understanding alone. Furthermore, the course’s introduction to Red Teaming offers an invaluable perspective on advanced offensive cybersecurity strategies. Students learn how to think and act like sophisticated cyber attackers, enabling them to anticipate and counter complex cyber threats. This approach is crucial in preparing cybersecurity professionals to conduct thorough, effective Red Teaming operations, a skill increasingly in demand in the rapidly evolving digital landscape. Who this course is for: Cybersecurity Professionals IT Professionals [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Build and Deploy a SaaS AI Agent Platform | Code With Antonio [Update 07/2025][/b] English | Size: 2.5 GB Genre: eLearning[/center] Build and Deploy a SaaS AI Agent Platform In this video, we're building an AI-powered video call app from start to finish. You'll learn how to set up real-time calls with custom AI agents, generate summaries and transcripts using background jobs, and integrate a full post-call experience including video playback, transcript search, and an AI chat that understands the meeting context. We'll also cover authentication, subscriptions, mobile responsiveness, and a full Git workflow with AI-assisted code reviews. [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Make 20 Advanced Level Applications in C++ | Udemy [Update 08/2025][/b] English | Size: 12.3 GB Genre: eLearning[/center] Turn Theory into Practice with 20 Full C++ GUI Stunning Projects Everyone needs to make [b]What you'll learn[/b] Anyone who wants to go beyond console applications and create powerful desktop tools and utilities. Engineers transitioning to C++: Professionals from other programming languages who want to master C++ application development. Problem solvers: Those who enjoy tackling complex challenges and building elegant solutions from scratch. Project-based learners: If you learn best by doing and enjoy seeing tangible results from your coding efforts. Innovators: Anyone with an idea for an application and wants to learn the practical steps to bring it to life using C++. Make 20 Advanced Level Applications in C++ is a hands-on, project-based course designed to transform you from a C++ programmer into a C++ application developer. Forget endless theoretical lessons and trivial examples. This course is about building real, functional software that you can use, share, and showcase in your portfolio. In a world where C++ is the backbone of high-performance applications, from gaming engines to financial trading platforms, mastering its practical application is essential. This course bridges the gap between knowing the C++ syntax and using that knowledge to create production-ready software. You won't just be writing code; you'll be building tools. We'll dive deep into modern C++ features and libraries to create a diverse portfolio of 20 applications. Each project is a complete, standalone program that challenges you to solve real-world problems. By the end of this course, you will have a tangible collection of advanced applications, a profound understanding of software development principles, and the confidence to tackle any C++ project. This course is your entry point to becoming a proficient C++ application developer. Rather than just going through theory and simple exercises, you'll immediately get hands-on experience building 20 advanced, practical applications. Each project is a complete, standalone program that challenges you to apply what you learn to solve real-world problems. This is a comprehensive, project-based course. We will dive deep into modern C++ features and libraries, transforming your foundational C++ knowledge into a robust skillset. This course bridges the gap between understanding C++ syntax and being able to create production-ready software. You'll build a diverse portfolio of applications, giving you the practical experience needed to stand out in a competitive job market. Course Highlights: Project-based Learning: Focus on hands-on application development with 20 unique projects. Modern C++: We will utilize modern C++ features and libraries. Practical Experience: Gain valuable experience building real, functional software that you can use, share, and showcase in your portfolio. Portfolio Ready: Finish the course with a tangible collection of advanced applications and the confidence to tackle any C++ project. Let's Get Started! [b]Who this course is for:[/b] Anyone who wants to go beyond console applications and create powerful desktop tools and utilities. Engineers transitioning to C++: Professionals from other programming languages who want to master C++ application development. Problem solvers: Those who enjoy tackling complex challenges and building elegant solutions from scratch. Project-based learners: If you learn best by doing and enjoy seeing tangible results from your coding efforts. Innovators: Anyone with an idea for an application and wants to learn the practical steps to bring it to life using C++. [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Learn Active Directory Pentesting for RedTeaming - Part 1 | Udemy [Update 06/2025][/b] English | Size: 5.5 GB Genre: eLearning[/center] Learn and Practice the Techniques of Active Directory Pentesting and go from Beginner to Intermediate Level. [b]What you'll learn[/b] Learn the Theory behind the Attacks Lab Setup for AD Pentesting Unofficial prep for exams like OSCP, PNPT, CPTS, CRTP, CRTO Local Enumeration Local Privilege Escalation Domain Privilege Escalation Lateral Movement Domain Enumeration Post Exploitation Persistence Techniques BloodHound PowerView Rubeus Impacket Tools Mimikatz File Transfer Techniques Metasploit This course is aimed at beginners who want to learn windows pentesting from basics. This course teaches Persistence and Lateral Movement techniques in-depth. After this course , you will have good understanding of how to approach a Windows machines from a Red-Team's Perspective. This course covers AD enumeration, privilege escalation, persistence, Kerberos attacks like delegation attacks, silver ticket, golden ticket, diamond ticket etc. The course simulate real world attack and we go from a normal user account in the domain and escalate privileges to Domain admin. The focus is on exploiting the different types of attacks that most malicious hackers in the world follow. This course is designed to provide security professionals to practice in a Windows 10 machine. The course is beginner friendly and will be suited for both students and experienced professionals. We will go from the port enumeration and understand how to enuemrate the ports. When it comes to AD security, there is a large gap of knowledge which security professionals and administrators struggle to fill. Over the years, I have taken numerous world trainings on AD security and always found that there is a lack of quality material and specially, a lack of good walkthrough and explanation. [b]Who this course is for:[/b] Students who wants to become a Good-Red Teamer. Students who already know windows pentesting but want to understand better about the theory behing the attacks. Students who are starting/aspiring to become a Red Teamer. Students who want to do learn about windows security [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]Master Agentic AI with Google ADK and MCP [2025] | Udemy [Update 07/2025][/b] English | Size: 7.7 GB Genre: eLearning[/center] Master autonomous AI agents with Google ADK & MCP: From basic tools to multi-agent systems [b]What you'll learn[/b] Build YouTube Shorts Automation Agents Using Google's ADK Framework Design Multi-Agent Systems with ADK and Standardized MCP Communication Protocols Implement Advanced Agent Orchestration with Tools, Memory, and External API Integrations Create multi-agent Website researcher with ADK and MCP Transform your development skills by building cutting-edge AI agents that revolutionize YouTube Shorts creation and multi-agent collaboration. This comprehensive, project-driven course takes you from ADK fundamentals to production-ready MCP implementations through hands-on projects-including an autonomous YouTube Shorts creator and sophisticated multi-agent systems powered by the Model Context Protocol. What You Will Learn Master Core ADK Technologies Build intelligent agents with Google's Agent Development Kit and advanced reasoning capabilities Create production-ready YouTube Shorts automation agents that generate, edit, and publish content autonomously Implement secure MCP message flows for seamless multi-agent communication and coordination Design modular ADK architectures with memory management, error handling, and contextual reasoning Deploy agents with robust monitoring, logging, and continuous integration workflows Develop Multi-Agent Expertise Construct sophisticated multi-agent systems using MCP protocol Orchestrate agent-to-agent communication patterns Engineer YouTube Shorts agents that research trends, generate scripts, create videos, and manage publishing Integrate external APIs and databases for real-world functionality Optimize agent performance using concurrency models and advanced debugging Build Real-World Projects Develop an autonomous YouTube Shorts creator handling research, scripting, video creation, and automated publishing Create a multi-agent MCP system for coordinated content planning, production, and distribution Implement intelligent workflow orchestration via standardized MCP protocols Test agent behavior in production-like environments with comprehensive error handling Document your solutions for a professional portfolio Perfect for Ambitious Developers Whether you're a software engineer, content creator, or a technical professional preparing for the multi-agent systems revolution, this course empowers you with practical skills and portfolio-worthy projects. Only basic Python knowledge and API familiarity are required-everything else is taught from scratch with clear explanations and hands-on, real-world exercises. Start building the future of intelligent automation and multi-agent systems today! [b]Who this course is for:[/b] Agentic AI ADK MCP [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]

[center][img][Hidden Content]] [center][b]n8n The Ultimate Course | Udemy [Update 07/2025][/b] English | Size: 7.7 GB Genre: eLearning[/center] Efficiency Redefined: Seamless Automations, AI, & API's with n8n. Hosting at home and in the cloud. n8n database reports [b]What you'll learn[/b] Understand low-code programming concepts, including variables, conditions, and data types for building efficient workflows. Master N8N's core functionalities to automate tasks using triggers, actions, and various nodes effectively. Learn to create and manage API workflows, integrating external services and handling data transformations seamlessly. Explore advanced features like error handling, debugging, and optimizing workflow performance for real-world applications. Advanced Administration, hosting and database understanding not found elsewhere online or in books An entire robust section dedicated to AI, RAG, Chat, Workflow AI, including VIBE front end programming, and MCP sse *** Stop paying - Memberships of $20, $40, $80 and $100+ EACH Month! *** Pay one time here on Udemy! Welcome to "The Ultimate n8n Course," where we embark on a journey through the world of low-code programming and the powerful capabilities of n8n. This course begins by introducing foundational low-code programming concepts, allowing learners to grasp the essential principles that will enable them to make the most of n8n. By understanding these concepts, participants will be well-prepared to explore the n8n interface. As we delve into the n8n interface, learners will discover how to navigate the dashboard effectively. This module highlights the key features of n8n, guiding students in creating their first workflow with ease and confidence. The next phase of the course focuses on the core nodes that constitute n8n. Participants will gain a comprehensive overview of built-in nodes, learning how to work with HTTP request nodes and utilize data transformation nodes to manipulate and manage data efficiently. This knowledge is crucial for developing dynamic workflows. Moving into more advanced topics, we will explore flow nodes, emphasizing flow control and error handling. This module teaches best practices for optimizing workflows, ensuring that students can create robust and efficient automations. Throughout the course, we will also discuss various use cases for n8n. From chat AI processing to agentic AI applications, traditional workflows, and APIs, learners will understand the diverse applications of n8n in real-world scenarios. A significant highlight of this course is the administrative section, where we cover essential topics that are often overlooked in other classes. Students will learn how to install and run n8n locally using Node.js or Docker, as well as in the cloud. We will also introduce easy panel hosting for quick deployments, making the process accessible for everyone. Finally, we'll dive into database management, showing participants how to access the default SQLite database and providing SQL queries for extracting data from PostgreSQL databases. This comprehensive approach ensures that students are well-equipped to leverage n8n for any workflow they envision. Join us in "The Ultimate n8n Course" to unlock the full potential of this dynamic tool and elevate your automation skills to new heights. [b]Who this course is for:[/b] Beginners looking to dive into low-code development and Agentic AI automation. Developers wanting to enhance their skills in Agentic AI workflow automation with N8N. Business Analysts aiming to streamline business processes without extensive coding knowledge powered by AI. Entrepreneurs seeking efficient ways to automate tasks and improve productivity with AI and Agentic AI. Tech Professionals wanting to implement agentic AI solutions for enhanced task automation. AI Enthusiasts eager to explore the integration of AI and automation in workflows. [center][img][Hidden Content]] [b]DOWNLOAD FROM RAPIDGATOR[/b] [Hidden Content] [b]DOWNLOAD FROM TURBOBIT[/b] [Hidden Content] [b]If any links die or problem unrar, send request to[/b] [hide][Hidden Content]]