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Oreilly – Red Hat OpenShift 2024-10 7 Feb at 4:27 pm Video Tutorial Course Microsoft Active Directory Online Training, Download course Microsoft Active Directory Online Training, Download Microsoft Active Directory Online Training, Free download Microsoft Active Directory Online Training, Free Microsoft Active Directory Online Training, Sander van Vugt Description Red Hat OpenShift Course. This comprehensive course teaches you how to deploy your own containerized applications using OpenShift. With Red Hat’s vision for technology change in mind, you’ll learn the basics of working with OpenShift. You’ll also learn about ROSA (Red Hat OpenShift on Amazon). Red Hat OpenShift is a great introduction for new students to container orchestration, as it covers all the steps needed to run scalable and reliable applications on OpenShift. You’ll learn how to work with containers in an OpenShift environment and understand all the key aspects of working with containers on OpenShift. You’ll also learn how to start an OpenShift workflow from the source code of any application and transform it into a managed and scalable container on OpenShift. What you will learn: OpenShift Fundamentals: In-depth understanding of the core concepts of OpenShift and how to work with it Running containerized applications: Learn how to deploy and manage containerized applications in OpenShift. ROSA: Introduction to Red Hat OpenShift on Amazon and how to use it OpenShift Workflow: Creating a complete workflow from source code to deployment in OpenShift Scalability and Reliability: Building scalable and reliable applications on OpenShift This course is suitable for people who: Looking to learn the basics of container orchestration Want to work with OpenShift and Kubernetes Looking for a way to deploy their applications in the cloud Looking for a comprehensive introduction to OpenShift? Red Hat OpenShift course specifications Publisher: Oreilly Instructor: Sander van Vugt Training level: Beginner to advanced Training duration: 5 hours Course headings Part 1. Deterministic search algorithms Introduction Red Hat OpenShift: Introduction Lesson 1: Understanding OpenShift Learning objectives 1.1 Containers 1.2 Containers in Cloud 1.3 Kubernetes 1.4 OpenShift 1.5 OpenShift Solutions Lesson 2: Using OpenShift Learning objectives 2.1 OpenShift Cluster Components 2.2 OpenShift Local 2.3 OpenShift Sandbox Lesson 2 Lab: Using an OpenShift Lab Environment Lesson 2 Lab Solution: Using an OpenShift Lab Environment Lesson 3: Red Hat OpenShift Amazon (ROSA) Learning objectives 3.1 Understanding ROSA 3.2 Getting Started with ROSA 3.3 Running Applications in ROSA Lesson 3 Lab: Exploring ROSA Lesson 3 Lab Solution: Exploring ROSA Lesson 4: Running Applications in OpenShift Learning objectives 4.1 OpenShift Console and CLI 4.2 Finding Images 4.3 Running Simple Applications 4.4 Understanding ImageStream 4.5 Running Applications the Declarative Way 4.6 OpenShift Container Security Lesson 4 Lab: Running Applications in OpenShift Lesson 4 Lab Solution: Running Applications in OpenShift Lesson 5: Resources Learning objectives 5.1 Why Resources are Needed 5.2 Common Kubernetes Resources 5.3 API Extensions 5.4 OpenShift Resources Lesson 5 Lab: Exploring OpenShift Resources Lesson 5 Lab Solution: Exploring OpenShift Resources Lesson 6: Scalable Applications Learning objectives 6.1 Deployments and ReplicaSets 6.2 Namespaces and Projects 6.3 oc new-app 6.4 Stateful Applications 6.5 DaemonSet 6.6 Managing Scalability Lesson 6 Lab: Running Scalable Applications Lesson 6 Lab Solution: Running Scalable Applications Lesson 7: Storage Learning objectives 7.1 Container Storage 7.2 Pod Volumes 7.3 Persistent Storage 7.4 Storage Autoprovisioning Lesson 7 Lab: Providing Persistent Storage Lesson 7 Lab Solution: Providing Persistent Storage Lesson 8: Configuration Learning objectives 8.1 Variables and ConfigMap 8.2 Configuration Files 8.3 Sensitive Values and Secrets Lesson 8 Lab: Configuring Applications Lesson 8 Lab Solution: Configuring Applications Lesson 9: Accessing Applications Learning objectives 9.1 OpenShift Networking 9.2 Services 9.3 Routes Lesson 9 Lab: Providing Application Access Lesson 9 Lab Solution: Providing Application Access Lesson 10: Application Templates Learning objectives 10.1 OpenShift Templates 10.2 The Helm Package Manager 10.3 Operators Lesson 10 Lab: Installing Applications from a Template Lesson 10 Lab Solution: Installing Applications from a Template Lesson 11: GitOps and OpenShift Learning objectives 11.1 What is GitOps 11.2 Source to Image 11.3 Tekton Lesson 11 Lab: Using Source to Image Lesson 11 Lab Solution: Using Source to Image Lesson 12: Managing Applications Learning objectives 12.1 Monitoring Applications 12.2 Probes 12.3 Quota 12.4 Application Security Lesson 12 Lab: Configuring Application Security Lesson 12 Lab Solution: Configuring Application Security Lesson 13: OpenShift Virtualization Learning objectives 13.1 What is OpenShift Virtualization 13.2 Installing OpenShift Virtualization 13.3 Running a VM in OpenShift Virtualization Lesson 13 Lab: Running a VM in OpenShift Virtualization Lesson 13 Lab Solution: Running a VM in OpenShift Virtualization Summary Red Hat OpenShift: Summary Download : [hide][Hidden Content]]

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Mastering Ai: Basics To Aws Certified Ai Practitioner Published 7/2025 Created by Banking and Finance School MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 57 Lectures ( 5h 32m ) | Size: 3.7 GB Unlock the future with AI — from foundational concepts to practical AWS deployment in one comprehensive course. What you'll learn History, ethics, and societal implications of AI Core AI concepts: logic, reasoning, search, probability Machine learning techniques: supervised, unsupervised, reinforcement learning Deep learning architectures including CNNs, RNNs, and generative models Practical implementation of AI with AWS services like SageMaker, Lex, Polly, Rekognition Preparation for AWS Certified AI Practitioner exam Real-world case studies and ethical AI deployment strategies Requirements Basic understanding of mathematics (algebra, probability, statistics) Familiarity with programming (preferably Python) Interest in AI/ML concepts and technologies No prior AI experience required — this course starts from scratch Description Artificial Intelligence (AI) is transforming the world at an unprecedented pace — revolutionizing industries, reshaping how we work, and unlocking powerful tools that once existed only in science fiction. This course is your gateway to becoming a confident AI practitioner. Whether you're a student, developer, or business professional, you'll gain a solid foundation in AI, machine learning, deep learning, and AWS-based AI services, preparing you for real-world implementation and certification.Section 1: Introduction to Artificial IntelligenceThis section lays the groundwork for understanding AI by exploring its definition and historical evolution. You'll learn how AI evolved from rule-based systems to modern-day intelligent agents. We then highlight AI's growing importance and diverse applications — from healthcare to finance to autonomous vehicles. The section concludes with a thoughtful discussion on AI ethics, societal impact, and the moral responsibilities of building intelligent systems.Section 2: Foundations of Artificial IntelligenceHere, we dive into the core building blocks of AI. Beginning with an overview, you'll study logic and reasoning systems that enable machines to make decisions. You'll then explore probability and statistics as a backbone for uncertainty handling in AI. Important AI problem-solving strategies like search algorithms are introduced, followed by knowledge representation and reasoning — enabling machines to 'think' and 'understand' their environment.Section 3: Machine Learning in Artificial IntelligenceMachine Learning (ML) is a core component of modern AI. This section starts with an introduction to ML and delves into supervised and unsupervised learning paradigms. Concepts such as clustering, distance metrics, and dimensionality reduction are explained with real-world analogies. We also explore association rule learning, reinforcement learning, and its types. By the end, you'll understand how machines learn from data and improve over time.Section 4: Deep LearningDeep learning powers today's most advanced AI applications. This section begins with the basics of neural networks, followed by an introduction to deep learning architectures. You'll gain insights into CNNs used for image recognition, RNNs used for sequential data, and generative models for AI creativity. Topics like transfer learning and fine-tuning are also covered to show how pre-trained models can be leveraged for better performance.Section 5: AWS Certified AI PractitionerThis final section prepares students for AWS AI certification and practical industry applications. It starts with a comprehensive introduction to AWS AI and ML tools, such as SageMaker, DeepLens, Lex, Polly, and Rekognition. Students will learn to build, train, and deploy models using AWS infrastructure. We also explore AI services in NLP and computer vision, model evaluation, ethical AI development, prompt engineering, and best practices. The section includes case studies, exam prep, and continuous improvement strategies to reinforce learning.Conclusion:By the end of this course, you'll not only understand the theoretical foundations of AI but also gain hands-on experience with powerful tools used by industry professionals. Whether you're looking to apply AI in business, pursue a technical career, or pass the AWS Certified AI Practitioner exam, this course equips you with the knowledge and confidence to move forward. Who this course is for Students and professionals seeking a career in AI and machine learning Data scientists and developers wanting AWS certification Business leaders and product managers exploring AI implementation Educators and researchers aiming to understand or teach AI fundamentals Anyone curious about how AI works and how to use it responsibly and effectively [Hidden Content]

Master Aigp From Zero To Pass (suits Isaca Aaia) Last updated 6/2025 Created by Prof. Ksenia Laputko MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 21 Lectures ( 7h 7m ) | Size: 5.5 GB New course for preparing for Body of Knowledge 2.0 active February 2025 What you'll learn Prepare fully for AIGP Body of Knowledge 2.0 Understand the foundations of AI governance Understand how privacy, intellectual property, non-discrimination, consumer protection laws apply to AI Understand the key elements of the first AI regulation in the world- EU AI Act Understand which industry standards and tools apply to AI (NIST AI RMF, ISO, HUDERIA, NIST ARIA, etc) Understand how to do AI governance at all stages of AI model development. You would be fully prepared to actual work as AI Officer in business Requirements No prior AI knowledge required. You would learn everything from scratch. Description Are you looking for truly easy AIGP course? Here it is! My experience with previous course allowed me to craft this easy-one-stop-shop for everyone! Its specifically done to help you master BoK 2.0 of 2025. Want to grab a discount ? Visit my Linkedin page, the discount codes are posted there or via private messages. This course is your ultimate preparation tool for the new AIGP certification exam, updated to align with the 2025 Body of Knowledge launching in February. Designed for easy and digestible learning, it aims to fully equip you with the knowledge and skills to pass the exam with confidence. Unlike other courses that overwhelm you with irrelevant or AI-generated content, this course draws from a rich variety of trusted sources, including authoritative books, articles, and real-world insights from experienced AI officers. We've meticulously crafted this course to explain every detail of the Body of Knowledge without contradictions or unnecessary complexity.Why chose us: Structured to match the exam domainsEach domain from the Body of Knowledge is covered in dedicated video lectures, packed with essential information, flowcharts, and practical advice.Domain I: Understanding the foundations of AI governance I.A Understand what AI is and why it needs governanceI.B Establish and communicate organizational expectations for AI governanceI.C Establish policies and procedures to apply throughout the AI life cycleDomain II: Understanding how laws, standards and frameworks apply to AI II.A Understand how existing data privacy laws apply to AIII.B Understand how other types of existing laws apply to AIII.C Understand the main elements of the EU AI ActII.D Understand the main industry standards and tools that apply to AIDomain III: Understanding how to govern AI development III.A Govern the designing and building of the AI modelIII.B Govern the collection and use of data in training and testing the AI modelIII.C Govern the release, monitoring and maintenance of the AI modelDomain IV: Understanding how to govern AI deployment and use IV.A Evaluate key factors and risks relevant to the decision to deploy the AI modelIV.B Perform key activities to assess the AI modelIV.C Govern the deployment and use of the AI model2. Comprehensive course materialsReceive detailed course notes to make your revision stress-free and effective. 3. Interactive learningEngage with tasks and tests specifically designed to reinforce your understanding and assess your progress.4. Targeted reading materialsEach section includes carefully selected resources to deepen your knowledge. Acts, guidances, books pieces and articles. 5. Expert guidanceThe course is led by a seasoned university lecturer and practitioner, ensuring you receive expert support and have all your questions addressed personally unlike other on-demand courses. Who this course is for Students and researchers preparing for IAPP AIGP exam Privacy professionals expanding their knowldege to AI Managers, founders planning to implement AI in their companies individuals pursuing career of AI Officer in business Homepage [Hidden Content] [Hidden Content]

Computer Network Security & Incident Response With Gen Ai Published 7/2025 Created by Skills Marathon MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 62 Lectures ( 9h 10m ) | Size: 2.6 GB Master modern network security, incident response & Gen AI for threat detection, log analysis, SIEM, and cyber defense. [Hidden Content]

Cisco CCIE Security – Umbrella Course | Orhan Ergun English | Size: 258.78 MB Genre: eLearning You will learn all the necessary topics for Cisco Umbrealla in the CCIE Security v6.1 exam! Overview of Cisco CCIE Security – Umbrella Course Discover the unparalleled CCIE Security v6.1 Umbrella course, where theory meets practical implementation. Gain hands-on experience deploying Umbrella as both a Virtual Machine and Roaming Client, mastering Cisco’s latest security solutions. Led by industry-certified experts, this course equips you with comprehensive knowledge and real-world skills to confidently secure networks against evolving threats. Whether you’re pursuing CCIE Security certification or aiming to advance your cybersecurity career, seize this opportunity to elevate your expertise and stand out in today’s competitive landscape. Enroll now and transform your understanding of secure networking with Cisco Umbrella! Enrolling in this course gives you exclusive access to our vibrant study group, where you can engage in enriching technical discussions, collaborate on labs, and get answers to your questions from peers and experts. This collaborative environment sets us apart from other training providers, who often offer solitary, independent study options. By joining our study group, you’ll enhance your learning experience through collective problem-solving, hands-on lab work, shared insights, and a supportive community. Elevate your learning journey with us and thrive in a network of like-minded learners! DL: [Hidden Content]

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ITPro.TV | Nmap | Download Free 368×450 32.7 KB ITPro.TV - Nmap Course details This course begins with a straightforward guide to installing Nmap, ensuring that you have the software ready to use. Next, we cover the fundamentals of Nmap, providing a solid foundation for beginners. As you progress, you will delve deeper into host discovery, learning various techniques to identify active hosts on your network. Each step is carefully explained to build your confidence and understanding. The journey continues with an in-depth exploration of port states and port scanning. You’ll gain insights into different port states and their implications for network security. Detailed videos on port scanning techniques will teach you how to identify open ports, understand service versions, and recognize vulnerabilities. Advanced port scanning methods, such as IP ID Idle Scan and FTP Bounce, are thoroughly covered, offering you sophisticated tools to enhance your scanning capabilities. Throughout the course, practical examples and hands-on exercises ensure that you can apply what you’ve learned immediately. By the end, you will possess a comprehensive skill set that enables you to use Nmap effectively for network security and troubleshooting. This course is designed to transform you into a proficient Nmap user, capable of tackling complex network challenges with confidence. What you will learn • Install and configure Nmap on various operating systems • Understand and utilize basic Nmap commands • Perform effective host discovery to identify active devices • Conduct thorough port scans to identify open and vulnerable ports • Apply advanced scanning techniques for deeper network analysis General Details: Duration: 7h 6m 38s Updated: 04/2025 Language: English Subtitle: .SRT Included Source: [Hidden Content] MP4 | Video: AVC, 1280x720p | Audio: AAC, 44.100 KHz, 2 Ch | 12 Lectures Magnet Link: [Hidden Content] Happy learning!

Automate the Boring Stuff with Python Programming Free Download What you’ll learn Automate tasks on their computer by writing simple Python programs. Write programs that can do text pattern recognition with “regular expressions”. Programmatically generate and update Excel spreadsheets. Parse PDFs and Word documents. Crawl web sites and pull information from online sources. Write programs that send out email notifications. Use Python’s debugging tools to quickly figure out bugs in your code. Programmatically control the mouse and keyboard to click and type for you. Description If you’re an office worker, student, administrator, or just want to become more productive with your computer, programming will allow you to write code that can automate tedious tasks. This course follows the popular (and free!) book, Automate the Boring Stuff with Python. Automate the Boring Stuff with Python was written for people who want to get up to speed writing small programs that do practical tasks as soon as possible. You don’t need to know sorting algorithms or object-oriented programming, so this course skips all the computer science and concentrates on writing code that gets stuff done. This course is for complete beginners and covers the popular Python programming language. You’ll learn basic concepts as well as: Web scraping Parsing PDFs and Excel spreadsheets Automating the keyboard and mouse Sending emails and texts And several other practical topics By the end of this course, you’ll be able to write code that not only dramatically increases your productivity, but also be able to list this fun and creative skill on your resume. DOWNLOAD LINK : [hide][Hidden Content]]

3 hours ago Machine Learning, Data Science, and Generative AI with Python Download For Free What you’ll learn Build generative AI systems with OpenAI, RAG, and LLM Agents Build artificial neural networks with Tensorflow and Keras Implement machine learning at massive scale with Apache Spark’s MLLib Classify images, data, and sentiments using deep learning Make predictions using linear regression, polynomial regression, and multivariate regression Data Visualization with Matplotlib and Seaborn Understand reinforcement learning - and how to build a Pac-Man bot Classify data using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naive Bayes, and PCA Use train/test and K-Fold cross-validation to choose and tune your models Build a movie recommender system using item-based and user-based collaborative filtering Clean your input data to remove outliers Design and evaluate A/B tests using T-Tests and P-Values Description Unlock the Power of Machine Learning, Data Science & AI: Master the Art of Turning Data into Insight Discover the Future of Technology with Our Comprehensive Machine Learning & AI Course - Featuring Generative AI, Deep Learning, and Beyond! In an era where Machine Learning (ML) and Artificial Intelligence (AI) are revolutionizing industries across the globe, understanding how giants like Google, Amazon, and Udemy leverage these technologies to extract meaningful insights from vast data sets is more critical than ever. Whether you’re aiming to join the ranks of top-tier AI specialists, with an average salary of $159,000 as reported by Glassdoor, or you’re driven by the fascinating challenges this field offers, our course is your gateway to an exciting new career trajectory. Designed for individuals with programming or scripting backgrounds, this course goes beyond the basics, preparing you to stand out in the competitive tech industry. Our curriculum, enriched with over 145 lectures and 20+ hours of video content, is crafted to provide hands-on experience with Python, guiding you from the fundamentals of statistics to the cutting-edge advancements in generative AI. Why Choose This Course? Updated Content on Generative AI: Dive into the latest in AI with modules on transformers, GPT, ChatGPT, the OpenAI API, Advanced Retrieval Augmented Generation (RAG), LLM agents, langchain, and self-attention-based neural networks. Real-World Application: Learn through Python code examples based on real-life scenarios, making the abstract concepts of ML and AI tangible and actionable. Industry-Relevant Skills: Our curriculum is designed based on the analysis of job listings from top tech firms, ensuring you gain the skills most sought after by employers. Diverse Topics Covered: From neural networks, TensorFlow, and Keras to sentiment analysis and image recognition, our course covers a wide range of ML models and techniques, ensuring a well-rounded education. Accessible Learning: Complex concepts are explained in plain English, focusing on practical application rather than academic jargon, making the learning process straightforward and engaging. Course Highlights: Introduction to Python and basic statistics, setting a strong foundation for your journey in ML and AI. Deep Learning techniques, including MLPs, CNNs, and RNNs, with practical exercises in TensorFlow and Keras. Extensive modules on the mechanics of modern Generative AI, including transformers and the OpenAI API, with hands-on projects like fine-tuning GPT, Advanced RAG, langchain, and LLM agents. A comprehensive overview of machine learning models beyond GenAI, including SVMs, reinforcement learning, decision trees, and more, ensuring you have a broad understanding of the field. Practical data science applications, such as data visualization, regression analysis, clustering, and feature engineering, empower you to tackle real-world data challenges. A special section on Apache Spark, enabling you to apply these techniques to big data, analyzed on computing clusters. No previous Python experience? No problem! We kickstart your journey with a Python crash course to ensure you’re well-equipped to tackle the modules that follow. DOWNLOAD HERE : Part 1 [hide][Hidden Content]] Part 2 [hide][Hidden Content]]

Download The Complete Python Bootcamp From Zero to Hero in Python Course For Free What you’ll learn You will learn how to leverage the power of Python to solve tasks. You will build games and programs that use Python libraries. You will be able to use Python for your own work problems or personal projects. You will create a portfolio of Python based projects you can share. Learn to use Python professionally, learning both Python 2 and Python 3! Create games with Python, like Tic Tac Toe and Blackjack! Learn advanced Python features, like the collections module and how to work with timestamps! Learn to use Object Oriented Programming with classes! Understand complex topics, like decorators. Understand how to use both the Jupyter Notebook and create .py files Get an understanding of how to create GUIs in the Jupyter Notebook system! Build a complete understanding of Python from the ground up! Description Become a Python Programmer and learn one of employer’s most requested skills. This is the most comprehensive, yet straightforward, course for the Python programming language! Whether you have never programmed before, already know basic syntax, or want to learn about the advanced features of Python, this course is for you! In this course we will teach you Python 3. With over 100 lectures and more than 21 hours of video this comprehensive course leaves no stone unturned! This course includes quizzes, tests, coding exercises and homework assignments as well as 3 major projects to create a Python project portfolio! Learn how to use Python for real-world tasks, such as working with PDF Files, sending emails, reading Excel files, Scraping websites for informations, working with image files, and much more! This course will teach you Python in a practical manner, with every lecture comes a full coding screencast and a corresponding code notebook! Learn in whatever manner is best for you! We will start by helping you get Python installed on your computer, regardless of your operating system, whether its Linux, MacOS, or Windows, we’ve got you covered. We cover a wide variety of topics, including: Command Line Basics Installing Python Running Python Code Strings Lists Dictionaries Tuples Sets Number Data Types Print Formatting Functions Scope args/kwargs Built-in Functions Debugging and Error Handling Modules External Modules Object Oriented Programming Inheritance Polymorphism File I/O Advanced Methods Unit Tests and much more! Download Complete Python Bootcamp Free : Part 1 :[hide][Hidden Content]] Part2 : [hide][Hidden Content]]

BUG BOUNTY COURSE 2025 Topic 1 Introduction To Bug Bounty 2 Our Virtual Lab Setup 3 Website Enumeration & Information Gathering 4 Introduction To Burp suite 5 HTML Injection 6 Command Injection Execution 7 Broken Authentication 8 Brute force Attacks 9 Sensitive Data Exposure 10 Broken Access Control 11 Security Misconfiguration 12 Cross Site Scripting - XSS 13 SQL Injection 14 XML, XPath Injection, XXE 15 Components With Known Vulnerabilities 16 Insufficient Logging And Monitoring 17 Monetizing Bug Hunting 18 Bonus - Web Developer Fundamentals 19 Bonus - Linux Terminal 20 Bonus - Networking 21 Where To Go From Here" [hide][Hidden Content]]