Category: Tutorials

Free Download Ai Mastery Chatgpt, Machine Learning & Automation
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.65 GB | Duration: 1h 42m
Learn ChatGPT, Machine Learning and automation to build real world AI solutions from beginner to advanced
What you’ll learn

Understand the fundamentals of AI and Machine Learning
Use ChatGPT effectively for real-world tasks
Build simple ML models without coding complexity
Automate business and marketing processes using AI
Apply AI in real-life scenarios (business, freelancing, productivity)
Requirements
This course is designed to be beginner-friendly, so no prior experience in Artificial Intelligence or Machine Learning is required. However, to get the best results, students should have: Basic computer skills (using a browser, typing, navigating websites) Access to a computer, tablet, or smartphone A stable internet connection Basic understanding of English (for following lessons and instructions) Willingness to learn and practice Tools Needed: Access to ChatGPT (free or paid version) Google account (for accessing some tools and resources) Optional: Notebook or digital document for exercises
Description
This course contains the use of artificial intelligence.AI Mastery – ChatGPT, Machine Learning & Automation for Beginners to AdvancedUnlock the power of Artificial Intelligence and transform the way you work and think.This course takes you from zero to advanced, guiding you step-by-step through the fundamentals of AI, with a strong focus on ChatGPT and Machine Learning. You will learn how to use AI tools effectively, create powerful prompts, automate tasks, and apply AI in real-world situations.As the course progresses, you will be introduced to the core concepts of Machine Learning, including data handling, model training, and basic algorithms. You will also explore real-world use cases, helping you understand how AI systems are built and applied in business, technology, and everyday life.You’ll also gain a clear understanding of Machine Learning concepts, giving you the foundation to build smarter solutions and stay ahead in today’s digital world.What you’ll gainractical skills to use ChatGPT like a proUnderstanding of key AI and Machine Learning conceptsAbility to apply AI in business, studies, or daily lifeHands-on knowledge with real-world examplesA strong foundation for advanced AI learningNo prior experience is needed. This course is perfect for beginners, professionals, and anyone who wants to stay relevant in the age of AI.Start your journey into AI today and turn knowledge into real results.
This course is designed for anyone who wants to understand and use Artificial Intelligence in a practical and profitable way. It is especially valuable for: Beginners with no prior experience in AI or Machine Learning Entrepreneurs and business owners who want to automate tasks and improve productivity Digital marketers looking to create content, generate leads, and optimize campaigns using AI Students who want to learn modern, in-demand skills Freelancers who want to offer AI-powered services Professionals who want to save time and work smarter using tools like ChatGPT
Homepage
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https://www.udemy.com/course/ai-mastery-chatgpt-machine-learning-automation/

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Free Download AI Literacy Masterclass ChatGPT and Prompting
Published 3/2026
Created by Laurence Svekis
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 124 Lectures ( 4h 35m ) | Size: 5.3 GB

Learn prompt engineering, AI workflows, and real-world skills to boost productivity, automate tasks and grow your career
What you’ll learn
✓ Use AI tools like ChatGPT effectively with structured prompting techniques to get accurate, useful, and consistent results
✓ Build AI workflows and systems to automate tasks, improve productivity, and solve real-world problems
✓ Evaluate AI outputs, identify errors or bias, and make better decisions using critical thinking frameworks
✓ Understand how AI works in simple terms and apply it confidently in business, work, and everyday scenarios
Requirements
● No prior AI or technical experience needed. Basic computer skills and curiosity to learn how AI works are enough
Description
Please note This course contains the use of artificial intelligence.
AI Literacy Masterclass ChatGPT and Prompting
Learn prompt engineering, AI workflows, and real-world skills to boost productivity, automate tasks, and grow your career
What You Will Learn
• Understand how AI works and how tools like ChatGPT generate responses
• Write powerful prompts that produce accurate, useful results
• Build real-world AI workflows to automate tasks and save time
• Use AI for content creation, coding, research, and productivity
• Think more effectively with AI to improve decision-making
• Avoid common mistakes and limitations when using AI tools
• Apply AI skills immediately in your job, business, or daily life
This Course Includes
• 130 plus on-demand video lessons
• able PDF workbook for every section
• Extended book-style learning guides for deeper understanding
• Exercises, prompts, and reflection activities
• Real-world examples and practical use cases
• Lifetime access
Course Description
Artificial Intelligence is rapidly changing how we work, learn, and create.
The difference today is not access to AI. It is how effectively you use it.
This course is designed to give you practical, real-world AI literacy skills that you can apply immediately.
You will learn how to use tools like ChatGPT not just for simple tasks, but to
• Solve problems faster
• Automate repetitive work
• Generate high-quality outputs
• Build repeatable workflows
This is not a passive course. It is a structured learning system.
Each section includes
• A downloadable PDF workbook to follow along
• An extended learning guide for deeper understanding
• Exercises to help you apply what you learn
You will move from basic understanding to real-world application, step by step.
Why This Course Is Different
Most courses focus on showing tools.
This course focuses on building skills.
You will learn
• How to think with AI, not just use it
• How to structure prompts for consistent results
• How to design workflows that save time and increase output
This approach ensures you gain long-term, transferable skills that stay relevant as AI evolves.
Who this course is for
■ This course is designed for beginners, professionals, students, and entrepreneurs who want to understand and use AI effectively in real-world situations.
■ It is ideal for anyone looking to improve productivity, make better decisions, and build practical AI skills without needing a technical background. Whether you’re using AI tools like ChatGPT for work, business, content creation, or personal projects, this course provides a clear and structured approach to help you move from confusion to confidence.
■ If you want to go beyond basic prompts and learn how to think, build workflows, and apply AI strategically-this course is for you.
Homepage
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https://www.udemy.com/course/ai-literacy-masterclass

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Free Download AI Literacy for Librarians & Library Management
Published 4/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 6m | Size: 2.37 GB
Artificial Intelligence for Librarian Skills and Library Management in the Digital Age

What you’ll learn
Understand the core concepts of AI and its role in modern libraries, including how machine learning and automation support information management.
Identify key AI tools used in research support, enabling faster and more accurate information retrieval for library users.
Explain how AI improves cataloguing processes by automating metadata creation and classification systems.
Analyse how AI enhances knowledge organisation, making library resources more accessible and searchable.
Recognise ethical and legal considerations when using AI in library environments, including data privacy and bias risks.
Evaluate how AI can improve user engagement through personalised recommendations and intelligent assistance systems.
Understand strategies for integrating AI into library services while maintaining quality and consistency.
Develop awareness of managing AI adoption within library settings, including planning, implementation, and monitoring.
Requirements
The course will provide beginner to intermidate level knowledge. No prior skill or experienced needed for enrollment.
Description
This course contains the use of artificial intelligence.
Transform your library into a future-ready knowledge hub powered by AI-driven efficiency and smarter services.
Why Artificial Intelligence is Required in Library Management Today
AI helps libraries manage growing digital information faster and more accurately than traditional methods. It improves user experience by delivering personalised search results and instant support. It also allows librarians to focus on strategic roles instead of repetitive manual tasks.
Over 70% of libraries in the US are adopting or planning to adopt AI-based systems for information management.
Artificial Intelligence is changing how libraries operate, organise knowledge, and serve users. As information continues to grow at an unprecedented rate, traditional library systems struggle to keep up with the demand for speed, accuracy, and accessibility.
This course, AI Literacy for Librarians & Library Management, introduces a structured approach to understanding how AI integrates into modern library environments. It focuses on how AI tools can support research, automate cataloguing processes, enhance metadata management, and improve user engagement.
Libraries are no longer limited to physical collections. Digital databases, online journals, and multimedia resources require advanced systems to organise and retrieve information efficiently. AI plays a key role in transforming these processes by enabling intelligent search systems, recommendation engines, and automated classification. This course also addresses ethical and legal responsibilities, ensuring that AI is used responsibly within library systems.
You will gain insight into how AI can support daily library operations, from assisting users with research queries to improving service delivery. The course also explains how to manage AI adoption within library settings, helping institutions remain relevant in a technology-driven world. By the end, you will understand how to align AI capabilities with library goals, ensuring better service quality and operational efficiency.
Who this course is for
Librarians who want to upgrade their skills with modern AI-driven systems
Library assistants aiming to move into advanced information management roles
Information science students preparing for future-focused careers
Anyone interested in combining AI with Library Management systems

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AI Language Models and Foundation Models (2026)
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English + subtitle | Duration: 1h 2m | Size: 166 MB​

Master the architecture of foundation models. Learn the evolution from BERT to multimodal systems, understand encoder/decoder architectures, and discover how AI agents use tools and memory to solve complex problems.

What you’ll learn
Start working on the skills required to understand the cutting edge of AI: multimodal foundation models and autonomous agents.
In this course, AI Language Models and Foundation Models, you will gain the ability to dissect the architectures that power the AI revolution, moving beyond simple text generation to understand how models see and act.
First, you will explore the Evolution and Architecture of these models. You will define what makes a "Foundation Model" and break down the core Transformer types: Encoder-only (BERT), Decoder-only (GPT), and Multimodal variants.
Next, you will discover the power of agents and autonomy, learning how modern AI extends beyond static prompts by utilizing tools, memory, and planning to perform complex tasks.
Finally, you will witness transfer learning in action, seeing how a massive pre-trained model can be adapted for a specific task through a hands-on fine-tuning demonstration.
When you’re finished with this course, you’ll have the skills and knowledge of AI language models and foundation models needed to comprehensively understand these models, explore their real-world applications, and effectively fine-tune them for various language processing tasks.

Free Download AI Integration in Test Automation for Writing and Debugging
Published 4/2026
Created by Suleyman Yuksel
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 42 Lectures ( 6h 0m ) | Size: 4.3 GB

Design AI-friendly test automation, integrate AI, turn plain text scenarios into test automation, and analyze failures
What you’ll learn
✓ Design AI-friendly test automation frameworks using Java, TestNG/JUnit, and Maven
✓ Integrate OpenAI APIs into real-world test automation workflows
✓ Design and prepare effective prompts for AI-driven test automation
✓ Build a Spring MVC microservice that converts plain-text scenarios into automation code using AI
✓ Transform multi-scenario test plans into executable automation suites using an AI-powered service
✓ Generate clean, maintainable automated tests from natural-language scenarios
✓ Integrate AI safely into existing automation frameworks without breaking test reliability
✓ Connect AI to service logs, test execution output, and reports for intelligent analysis
✓ Use AI to analyze test failures, logs, and automation code to identify root causes
✓ Produce clear, human-readable bug Descriptions from raw logs and test results using AI
✓ Design controlled AI workflows that ensure deterministic and reliable test results
✓ Apply all techniques to enterprise-scale automation and microservice-based systems
Requirements
● Basic to intermediate Java knowledge
● Basic understanding of OOP concepts (classes, interfaces, inheritance)
● Basic xperience with Java-based test automation frameworks such as TestNG or JUnit
● Basic familiarity with Spring Boot or Spring MVC, but it is not required to follow the course.
Description
AI is changing how test automation is built-but using AI effectively requires more than copying scenarios into a chat window.
This course shows how to design and build real AI-powered automation systems, where plain-text test plans are transformed into executable automation suites, tests are run automatically, and failures are analyzed intelligently using test code, execution output, and service logs.
Rather than focusing on prompt-only workflows or demos, this course takes a system-level engineering approach. You will learn how to integrate AI into existing automation frameworks in a controlled, deterministic, and reliable way, without compromising test quality or trust in results.
You will build an AI-assisted automation pipeline using Java and Spring MVC, integrate AI APIs, and design automation that is intentionally structured to work well with AI. The course also tackles one of the biggest real-world challenges in automation: a failing test does not always mean a service bug. You will learn how to use AI to analyze test code, test execution output, and service logs together to reduce investigation time and produce clear, human-readable explanations of what actually went wrong.
This course is designed for engineers working with enterprise-scale systems, where automation must be maintainable, debuggable, and scalable. The focus is on architecture, design decisions, and practical implementation-not basic Java, beginner automation, or AI hype.
Who this course is for
■ SDETs, QA Automation Engineers, and Software Developers who want to integrate AI into existing test automation frameworks
■ Engineers who want to transform multi-scenario test plans into executable automation suites using an AI-powered service
■ Professionals looking to adopt AI safely and in a controlled way without compromising test reliability or determinism
■ Engineers who spend significant time investigating failed tests and want to use AI to distinguish test issues from real service defects
■ Teams that want to reduce debugging time by using AI to analyze test code, execution output, and service logs together and produce clear, user-friendly failure explanations
Homepage
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https://www.udemy.com/course/ai-integration-in-test-automation-for-writing-and-debugging

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Free Download AI Income Blueprint 2026
Published 3/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 3h 52m | Size: 3.2 GB
From Beginner to Paid: A Complete Guide to Earning with AI

What you’ll learn
Learn how to use AI tools like ChatGPT, image, and video generators to create real freelance services from scratch
Build and package AI-powered services such as content writing, design, and video creation that clients will pay for
Find clients on platforms like Upwork and Fiverr and write proposals that get accepted even as a beginner
Follow a step-by-step roadmap to go from beginner to your first real results with AI, including practical action plans and workflows
Requirements
No prior experience needed. This course is beginner-friendly and covers everything step by step. You only need a computer, internet connection, and willingness to take action
Description
This course contains the use of artificial intelligence.
AI Income Blueprint 2026
From Beginner to Paid: A Complete Guide to Earning with AI
AI Income Blueprint 2026 is a practical, beginner-friendly course designed to help you turn AI tools into real income, even if you have no prior experience. This program provides a clear, step-by-step roadmap that takes you from learning the basics of AI to landing your first client and growing your results.
Throughout the course, you will learn how to use powerful AI tools for writing, design, video, and automation, and how to turn those skills into services that businesses are actively looking for. You will also discover how to create compelling offers, set your pricing, and position yourself effectively in a competitive market.
The course is structured into six sections covering everything from foundational knowledge to execution and long-term growth. You will follow a proven system that guides you through choosing a service, building a simple portfolio, finding clients, and closing your first project. A dedicated execution plan helps you take action quickly, including a 7-day roadmap to get started.
In addition, the included AI Income Blueprint Workbook provides hands-on exercises for every lesson, helping you apply what you learn immediately and build a practical, repeatable system.
By the end of the course, you will have a clear service, a client acquisition strategy, and a structured path to grow using AI.
Who this course is for
Beginners who want to make money online using AI, freelancers looking to upgrade their skills, and anyone who wants to build a side income or start an AI-based business

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Free Download AI in SDLC Software Development Lifecycle with AI
Published 3/2026
Created by Sandeep Soni
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 9 Lectures ( 1h 39m ) | Size: 1.67 GB

Use AI tools to plan, design, code, test, and deploy software across the SDLC with modern development workflows
What you’ll learn
✓ Understand SDLC phases and their purpose
✓ Identify how AI can be applied in each SDLC phase
✓ Use AI tools for requirement analysis and planning
✓ Apply AI in software design and architecture
✓ Use AI for code generation and debugging
✓ Automate testing using AI-based tools
✓ Automate testing using AI-based tools
✓ Understand real-world AI-driven development workflows
✓ Improve team productivity using AI tools
Requirements
● Basic understanding of software development concepts
● Familiarity with programming basics
● Awareness of software development lifecycle (SDLC) concepts
Description
This course provides a comprehensive understanding of how Artificial Intelligence is transforming the Software Development Lifecycle (SDLC), enabling teams to build, test, and deliver software faster and more efficiently.
Modern development teams are increasingly adopting AI tools to improve productivity, reduce manual effort, and enhance code quality. In this course, you will learn how AI can be applied across every phase of the SDLC, from planning and requirement analysis to development, testing, and deployment.
You will begin by understanding the traditional SDLC phases and how AI integrates into each stage. The course then explores how AI tools can assist in requirement gathering, design decisions, code generation, debugging, testing automation, and documentation.
You will learn how to use tools such as GitHub Copilot, AI-based testing tools, and modern AI workflows to improve development efficiency. The course also covers how AI supports DevOps practices, CI/CD pipelines, and continuous delivery.
In addition, the course highlights real-world use cases, showing how organizations are adopting AI to streamline development workflows and improve collaboration across teams.
By the end of this course, you will have a clear understanding of how to apply AI across the software development lifecycle, making this course highly valuable for developers, DevOps engineers, and teams adopting AI-driven development practices.
Who this course is for
■ Software Developers
■ DevOps Engineers
■ QA Engineers
■ Engineering Managers
■ IT professionals adopting AI workflows
■ Teams looking to improve development productivity using AI
Homepage
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https://www.udemy.com/course/ai-in-sdlc-software-development-lifecycle-with-ai

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Free Download AI in Clinical Medicine
Published 3/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 8h 21m | Size: 5.18 GB
LLMs, Imaging AI & Digital Pathways-From Use Case to Safe Deployment in Real Healthcare Systems

What you’ll learn
Select high-impact clinical AI use cases using a practical impact x feasibility framework
Map workflows to identify where AI truly changes decisions, timing, and workload
Define outcomes, guardrails, and equity checks that withstand governance scrutiny
Deploy LLMs safely using structured prompts, verification, and RAG grounded in policies
Evaluate imaging AI like a reviewer: prevalence traps, external validation, and failure modes.
Design patient-facing AI and monitoring pathways that avoid harm, alerts fatigue, and unsafe triage.
Requirements
There are no formal prerequisites-but to get full value, learners should come in with a solid professional baseline and the right expectations. Recommended background Clinical familiarity: you should understand how care is delivered in at least one setting (hospital, clinic, imaging, or digital care). You don’t need to be a physician, but you should know what workflows, handoffs, and clinical risk feel like. Basic AI literacy: comfort with core terms like training vs inference, sensitivity vs specificity, and what an LLM is at a high level. (You don’t need to code.) Quality/safety mindset: willingness to think in failure modes, escalation pathways, and "what could go wrong" rather than only "how accurate is it?" Operational thinking: interest in how tools get adopted-EHR integration, alert burden, staffing capacity, governance, and measurable outcomes.
Description
– This course contains the use of artificial intelligence –
Healthcare doesn’t need more AI hype-it needs leaders who can turn AI into outcomes without creating new risks. This course is a hands-on, expert-level playbook for building and deploying clinical AI in the real world: hospitals, clinics, imaging workflows, and patient-facing digital pathways.
You will learn how modern clinical AI actually works across predictive models, imaging AI, LLMs, multimodal systems, and agent-like workflow automation. More importantly, you’ll learn how to choose problems worth solving, map clinical workflows, define outcomes and guardrails (clinical, operational, safety, equity), and write use-case briefs that survive governance, IT security, and procurement.
We go deep into the realities of LLMs in healthcare: hallucinations, uncertainty, automation bias, structured prompting, and Retrieval-Augmented Generation (RAG) grounded in local policies and guidelines. You’ll also master imaging AI from dataset and labeling strategy to external validation, prevalence traps, and production integration patterns such as worklist triage, second reader workflows, QA backstops, and reporting automation.
Patient-facing AI gets equal rigor: symptom triage vs coaching vs adherence support, remote monitoring at scale, alert fatigue, and high-risk mental health and neurological safeguards. Throughout the course, you’ll work with real-world examples and the same frameworks used by leading health systems and digital health companies-so you can move from "interesting pilot" to safe, measurable, scalable deployment.
Who this course is for
Global and regional Market Access / HEOR / Medical Affairs leaders who need to evaluate AI-enabled clinical value claims
CMIO/CCIO teams, clinical informaticians, and digital transformation leaders
Radiology, pathology, dermatology, and ophthalmology leaders implementing imaging AI
Clinical operations and quality/safety leaders responsible for governance and outcomes
Digital health product managers building patient-facing AI and remote monitoring pathways
Healthcare data science and ML teams who want a workflow-native, deployment-first mindset
Consultants and strategy teams supporting AI adoption, vendor selection, and scaling

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Free Download AI in Action Global Case Studies from Public Institutions
Released 4/2026
With United Nations University and Microsoft
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: General | Genre: eLearning | Language: English + subtitle | Duration: 41m | Size: 183 MB

Explore what AI looks like in practice through expert segments on public policy, digital government, global health, and research, in this course from the United Nations University.
Course details
AI governance and implementation look different depending on sector, region, and institutional context-and those differences matter for anyone working at the intersection of technology and policy.This course brings together experts from the United Nations University network and partner institutions to explore what AI looks like in practice. Through short, focused segments, you’ll learn from practitioners in public policy, digital government, global health, youth research, and development. Each perspective highlights how AI governance and cooperation unfold across borders-from inclusive development and health equity to evidence-based policymaking.Contributors include Dr. Nicole Goldin (UNU-CPR), Charmaine Distor (UNU-EGOV), Dr. Rohit Ramchandani of Antara Global Health Advisors, Dr. Jaimee Stuart of Victoria University of Wellington, and Georgina Curto Rex of UNU Macau.This course was created by Microsoft and United Nations University. We are pleased to host this training in our library.
Skills covered
Artificial Intelligence (AI), Governance, Risk Management, and Compliance (GRC), AI Policy, Governance, and Regulation
Homepage
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https://www.linkedin.com/learning/ai-in-action-global-case-studies-from-public-institutions

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AI Implementation and Operations
Duration: 49m | .MP4 1920×1080 30 fps(r) | AAC, 48000 Hz, 2ch | 290.01 MB
Genre: eLearning | Language: English​

AI success doesn’t end with training a model. This course will teach you how to implement, integrate, and operate AI systems in real-world environments to ensure reliability, scalability, and continuous improvement.

More Info:
AI Implementation and Operations