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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

Free Download AI Governance Fundamentals Framework, Templates & Sprint
Published 4/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 56m | Size: 1.94 GB
Build an AI governance framework, assess risk, draft policies, and assign accountability with ready-to-use templates

What you’ll learn
Build a complete AI governance framework: inventory, risk assessment, policy, and accountability
Identify and score AI risk across seven categories using a practical scoring matrix
Draft an AI acceptable use policy that any employee can understand and follow
Understand the EU AI Act, US state laws, and the national AI legislative framework
Assign governance accountability using a RACI matrix with named owners for every AI use case
Create a 30-day sprint plan to take your organization from ungoverned to Level 3 maturity
Prepare audit-ready evidence across six categories that regulators and auditors expect
Apply governance to real scenarios through hands-on assignments and AI-powered role plays
Requirements
No technical background required. This course is designed for business professionals, not engineers. You should have a basic understanding of what AI tools like ChatGPT or Copilot do (you do not need to know how they work). Familiarity with your organization’s structure and current AI usage will help you apply the frameworks immediately.
Description
Your organization is already using AI. The question is whether anyone is governing it.
78% of employees admit to using AI tools their employer never approved. Over a third are sharing confidential data with those tools. AI incidents are up 56% year over year. And only 34% of organizations have a governance framework.
This course is designed to help you start closing that gap.
What makes this course different
● Built by someone who has governed AI in regulated industries, not by someone who read about it
● Covers the 2026 White House National AI Legislative Framework alongside existing regulations
● Practical, not theoretical: includes five ready-to-use templates, not just concepts
● Running scenario (Meridian Consulting) that makes every framework concrete and applicable
● Hands-on assignments where you build governance artifacts for your own organization
● AI-powered role play scenarios where you rehearse real governance conversations
● 15 years of regulated finance experience (Citi, JPMorgan, Bloomberg) distilled into a focused course
What you will learn
● What AI governance actually is (and the five things it is NOT)
● The three pillars: visibility, accountability, and oversight
● Seven categories of AI risk with real-world failure examples
● How to build an AI inventory and discover shadow AI
● How to score risk across seven categories using a practical matrix
● How to draft an acceptable use policy your employees can understand and follow
● How to assign accountability using a RACI matrix
● The EU AI Act phased timeline and what it means for your organization
● The three layers of US AI regulation: state laws, federal agency guidance, and the national legislative framework
● NIST AI RMF vs ISO/IEC 42001: which framework to adopt and why
● Industry-specific Requirements for financial services, healthcare, legal, HR, and government
● What evidence auditors expect and the minimum viable evidence package
● The five-level AI governance maturity model
● A week-by-week 30-day sprint plan designed to help you move from Level 1 (Unaware) toward Level 3 (Defined)
What you will build
Throughout the course, you will follow Meridian Consulting, a fictional 200-person firm with four ungoverned AI use cases. By the end, you will have worked through governing all four and practiced building governance artifacts for your own organization.
Your governance starter kit (5 downloadable templates)
1. AI Inventory Template (Excel)
2. AI Risk Assessment Template (Excel)
3. Acceptable Use Policy Template (Word)
4. AI Governance RACI Matrix (Excel)
5. 30-Day Governance Sprint Planner (PDF)
Plus 3 bonus resources: Audit Readiness Checklist, Regulatory Quick Reference Guide, and Maturity Model Self-Assessment.
What you will practice
● Assignment 1: Build a governance framework for your organization (inventory, risk score, policy rules, owner assignment)
● Assignment 2: Draft your 30-day governance sprint plan with specific people, timelines, and deliverables
● Role Play 1: Brief your CEO on AI governance Requirements (AI-powered, you rehearse the real conversation)
● Role Play 2: Address shadow AI on your team with a defensive VP who sees governance as a threat to productivity
Course format
● ~90 minutes across 15 videos + 1 promo
● Face-on-camera for hooks, scenarios, and recaps
● Professional slides with voiceover for frameworks and data
● Screen recordings walking through each template live
● 2 hands-on assignments with instructor solutions
● 2 AI-powered role play scenarios
● able templates ready to use the same day
Your instructor
Ritesh Vajariya has spent 15 years in regulated finance at Citi, JPMorgan, and Bloomberg, including work on BloombergGPT. He spent 5 years as an AWS Principal Architect, involved in launching SageMaker and Bedrock. Most recently, he led global generative AI strategy at Cerebras. He has trained over 60,000 professionals across 65+ courses. When he covers compliance, he is drawing from 15 years in regulated financial environments, not reading documentation.
This course is designed for anyone responsible for how AI is used in their organization. If you are a business leader, compliance professional, IT director, HR leader, legal counsel, or anyone who has realized that AI governance is no longer optional, this course provides the frameworks, templates, and practice scenarios to help you get started.
Who this course is for
Business leaders and executives responsible for AI adoption and risk management
Compliance and governance professionals expanding into AI oversight
IT directors and CISOs managing AI tool deployment and security
HR leaders using or evaluating AI for hiring, performance, or workforce decisions
Legal counsel advising on AI-related regulatory Requirements
Consultants and advisors helping clients navigate AI governance
Anyone who has realized their organization is using AI without governance and wants to fix it

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Free Download AI Governance Basics What Every Professional Must Know
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 532.94 MB | Duration: 1h 15m
Learn AI governance fundamentals – frameworks, risk, responsible AI, and regulation – in under 2 hours. No technical bac
What you’ll learn

Understand what AI governance is, why it matters, and how global regulations like the EU AI Act and NIST AI RMF define the landscape.
Identify the core principles of responsible AI – fairness, transparency, privacy, accountability, and human oversight – and why they exist.
Recognize the main categories of AI risk and how organizations classify, assess, and manage AI systems responsibly.
Understand how data governance, consent, and privacy obligations connect to AI development and deployment.
Navigate generative AI governance challenges and evaluate vendor AI tools using the right due diligence questions.
Requirements
No technical background required – this course is designed for professionals across all functions and seniority levels.
A basic familiarity with AI tools (such as chatbots or AI-assisted software) is helpful but not mandatory.
Curiosity and an openness to exploring how governance, ethics, and regulation intersect with AI technology.
Description
This course contains the use of artificial intelligence.AI is reshaping every industry – but are the people deploying it equipped to do so responsibly?From biased hiring algorithms to chatbots giving legally binding wrong advice, from hallucinating AI outputs to opaque automated decisions – the risks of ungoverned AI are no longer hypothetical. They are landing in courts, regulators’ inboxes, and boardrooms right now. This free introductory course gives you a structured, jargon-free foundation in AI governance – so you understand what it is, why it matters, and how organizations are approaching it.Whether you work in compliance, legal, HR, operations, finance, technology, or leadership, this course explains AI governance in plain language and connects every concept to situations you’re likely to encounter at work.What This Course CoversWhat AI governance is, why it has become a global regulatory and business priority, and what the cost of getting it wrong looks like in practiceThe global regulatory landscape – including the EU AI Act’s four-tier risk classification, the NIST AI RMF, ISO 42001, and OECD AI PrinciplesThe core principles of responsible AI: fairness, transparency, accountability, privacy, safety, and human oversightHow organizations identify, classify, and manage AI risk – including third-party and vendor AI riskData governance obligations connected to AI: consent, lawful basis, automated decision-making, and privacy by designHow governance applies across the AI development lifecycle – from pre-development ethics review to post-deployment monitoringGenerative AI governance: hallucination risks, acceptable use policies, and vendor evaluationThe organizational structures, roles, and policy frameworks that underpin effective AI governanceHow to begin your own AI governance learning journey and what certifications and frameworks to explore nextWho Will BenefitProfessionals in compliance, legal, operations, HR, and business functions who need a structured AI governance foundationManagers and business leaders beginning to oversee AI tools and wanting clarity on their responsibilities under emerging regulationLearners considering a career path in AI governance, AI risk management, responsible AI, or related certificationsPrerequisitesNo technical background is required. If you have a basic awareness of AI tools – such as chatbots or AI-assisted software – you have everything you need. This course is designed for professionals across all functions and seniority levels, not just IT or data teams.What You Get With This CourseChapter quizzes at the end of every section to test and reinforce your understandingAn initial knowledge check and a final full-length assessment to measure your progress from start to finishThree practical assignments that take you from passive learner to active practitionerThree immersive role play scenarios that put your knowledge into real organizational contextsA comprehensive downloadable toolkit – including glossaries, checklists, templates, cheat sheets, a vendor due diligence questionnaire, a risk assessment worksheet, and an AI acceptable use policy template – tools you can start using immediatelyThis course is the first step on the AI Governance Professional Track. Completing it will give you a clear picture of your next steps – whether that’s the EU AI Act, NIST AI RMF, AI risk management, or a formal certification pathway.
Professionals in compliance, legal, HR, operations, and business functions who need a structured, jargon-free introduction to AI governance.,Managers and decision-makers beginning to use or oversee AI tools who want to understand their responsibilities under emerging regulations.,Learners exploring a career path in AI governance, AI risk management, or responsible AI – and looking for a structured starting point.
Homepage
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https://www.udemy.com/course/ai-governance-basics-what-every-professional-must-know/

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Free Download AI Generalist Mastery From Zero to Building Real AI Systems
Published 4/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 7h 18m | Size: 2.41 GB
Become a versatile AI professional-learn tools, build AI apps, automate workflows, and design real-world AI solutions

What you’ll learn
Build real-world AI systems, workflows, and agents using modern tools and frameworks
Master prompt engineering and AI interaction techniques to get reliable, high-quality outputs
Design and implement AI automation pipelines using tools like Zapier, Make, and APIs
Apply AI across business functions (marketing, operations, finance, product) to solve real problems
Develop and deploy AI-powered applications (chatbots, assistants, and simple apps)
Create a portfolio of AI projects to showcase practical skills and accelerate career growth
Requirements
No prior experience in AI or machine learning required-this course is beginner-friendly
Basic computer skills (using a browser, installing apps, managing files)
Familiarity with tools like Google Docs, Excel, or Notion is helpful but not required
A laptop or desktop with a stable internet connection
Access to AI tools (free or paid) such as ChatGPT, Claude, or similar platforms
Willingness to learn by doing-this is a hands-on, project-based course
Optional: Basic understanding of workflows or automation tools is a plus, but not necessary
Description
"This course contains the use of artificial intelligence"
Step into the future of work with the AI Generalist Mastery course-designed to transform you from a beginner into a highly versatile professional who can build, automate, and deploy real-world AI systems. In today’s rapidly evolving landscape, companies are no longer looking for just specialists-they need AI generalists who can bridge the gap between technology, business, and execution.
This course is built for professionals who want practical, hands-on skills in Artificial Intelligence, Generative AI, and AI automation, without getting lost in heavy theory or complex math. Instead of focusing purely on models, you will learn how to use AI tools, design intelligent workflows, and build AI-powered applications that solve real business problems.
You’ll start with a strong foundation in AI fundamentals, including how Large Language Models (LLMs) work, their capabilities, and limitations. From there, you’ll master prompt engineering, enabling you to turn tools like ChatGPT, Claude, and other AI platforms into powerful assistants for productivity, content creation, and decision-making.
As you progress, you’ll dive into the modern AI tools ecosystem, learning how to integrate platforms like Zapier, Make, and n8n to create AI automation workflows. You won’t just learn tools-you’ll build systems. This includes designing end-to-end AI workflows, creating AI agents, and implementing real-world automation pipelines that can handle multi-step tasks.
One of the most powerful aspects of this course is its focus on agentic AI systems. You will learn how to design AI agents using frameworks like Observe → Think → Plan → Act → Reflect, enabling you to create intelligent systems that can reason, plan, and execute tasks autonomously.
You’ll also gain practical experience in AI for business applications, applying AI across functions like marketing, operations, finance, and product management. This ensures you can drive impact regardless of your role or industry.
By the end of the course, you will build multiple portfolio-ready projects, including AI-powered apps, automation systems, and a complete capstone AI project where you design and present your own solution-from problem definition to business impact.
This course is ideal for professionals, product managers, consultants, entrepreneurs, and career switchers who want to stay competitive in the age of AI. Whether you are non-technical or semi-technical, you will leave with the confidence and capability to build AI solutions, automate workflows, and position yourself as an AI expert.
If you’re looking to move beyond just "using AI" and start building real AI systems, this course is your complete roadmap to becoming an AI Generalist.
Who this course is for
Professionals who want to stay relevant and competitive in the age of AI
Product managers, consultants, and business leaders looking to apply AI in real-world scenarios
Entrepreneurs and founders who want to build AI-powered products or automate their business
Non-technical or semi-technical learners who want to learn AI without deep coding or math
Career switchers aiming to break into AI roles or transition into tech-driven careers
Freelancers who want to offer AI automation, consulting, or AI-powered services
Anyone who wants to move from just using AI tools → building real AI systems and workflows

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Free Download AI Fundamentals for Beginners From AI Testing to GenAI
Published 4/2026
Created by Pankaj Gupta
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 81 Lectures ( 3h 44m ) | Size: 3.1 GB

Learn AI & GenAI testing from scratch with real‑world examples, no‑code, beginner friendly + Prompt Engineering
What you’ll learn
✓ Understand how AI systems differ from traditional applications
✓ Test machine learning models with the right mindset
✓ Design effective AI test cases
✓ Identify bias, hallucination, and unsafe AI responses
✓ Test Generative AI systems using prompt variations
✓ Apply automation basics in AI testing
✓ Handle real-world AI testing scenarios confidently
✓ Explain AI testing concepts clearly in interviews
✓ This is highly relevant for modern AI projects.
Requirements
● Basic knowledge of software testing
● Curiosity to learn AI testing
● No machine learning background needed
● No heavy coding required
Description
AI Testing for Beginners – Practical Guide for Software Testers
Artificial Intelligence is now part of modern software applications – including chatbots, recommendation systems, resume screening tools, credit scoring systems, and Generative AI platforms.
However, many software testers find it challenging to test AI-based systems effectively.
Traditional testing approaches often fall short because
• Expected results are not always fixed
• AI outputs can vary for the same input
• Behavior may change over time
• Issues like bias, inconsistency, and hallucinations can occur
• Automation strategies need a different approach
If you are a tester exploring AI systems, this course is designed to help you understand how AI works and how testing needs to adapt.
What Makes This Course Different
This course is designed specifically for software testers, not data scientists.
You will learn
• AI concepts explained in simple, practical language
• Testing approaches tailored for real-world QA scenarios
• Clear explanations without complex mathematics
• Coverage of modern Generative AI testing concepts
• Beginner-friendly content with minimal coding Requirements
The focus is on helping you understand AI systems from a tester’s perspective.
What You Will Learn
By the end of this course, you will have a clear understanding of
• How AI systems differ from traditional applications
• The mindset required for testing AI-based features
• Approaches to designing test cases for AI behavior
• Common risks such as bias, hallucination, and unsafe responses
• Techniques for testing Generative AI using prompt variations
• Where automation fits into AI testing workflows
• How to approach AI testing scenarios in real-world projects
• Key concepts that can help you discuss AI testing in interviews
Special Focus: Generative AI Testing
Generative AI is becoming a core part of modern applications.
In this course, you will explore how to evaluate
• Prompt variations and their impact on responses
• Hallucination scenarios
• Toxic or unsafe outputs
• Guardrails and safety mechanisms
• Context handling and memory behavior
• Response consistency
These concepts are highly relevant for tools like chatbots and AI assistants.
Practical & Real-World Approach
This course focuses on practical understanding through relatable examples, including
• Chatbot testing approaches
• Resume screening system scenarios
• Recommendation system behavior
• Credit scoring system analysis
• Introduction to automation in AI testing
• Hybrid testing strategies (manual + automation)
All topics are explained in a simple and structured way to make learning easier.
Strong Foundation: AI Basics Made Simple
Before moving into testing, the course builds a clear foundation by covering
• What Artificial Intelligence and Generative AI are
• How AI systems learn and make decisions
• Why AI outputs vary and how to interpret them
This helps reduce confusion and makes advanced topics easier to follow.
AI Testing with Practical Thinking
You will explore how testers approach AI systems in real scenarios, including
• Testing chatbot interactions
• Identifying inconsistency and unexpected outputs
• Evaluating risk and behavior instead of exact results
• Understanding how AI testing differs from traditional testing
Introduction to Prompt Engineering
The course also introduces key prompt engineering concepts, such as
• Writing effective vs ineffective prompts
• Zero-shot, one-shot, and few-shot prompting
• Structuring prompts for better AI responses
• Understanding how prompt design impacts output
Who this course is for
■ Manual Testers moving into AI projects
■ Automation Testers exploring AI systems
■ QA Engineers working with chatbots
■ Professionals preparing for AI testing interviews
■ Anyone curious about AI testing basics
Homepage
Code:Copy to clipboard

https://www.udemy.com/course/ai-fundamentals-for-beginners-ai-testing-genai

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Free Download AI for Scrum Masters
Published 4/2026
Created by Agile Enterprise Coach London
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 88 Lectures ( 8h 0m ) | Size: 8.4 GB

Accelerate Agile Delivery, Coaching Impact, and Team Effectiveness Using AI and ChatGPT
What you’ll learn
✓ Understand Large Language Models, foundational models, and how GenAI fits into Agile ways of working
✓ Create and refine Agile and product-related deliverables using structured ChatGPT prompt frameworks
✓ Apply AI to Product Vision Boards, Business Model Canvas, Kano Models, Market Segmentation, and Porter’s Five Forces
✓ Generate user stories and improve backlog clarity using ChatGPT
✓ Use AI responsibly by understanding accuracy, limitations, citations, and Responsible AI principles
✓ Create presentations using ChatGPT and PowerPoint workflows
✓ Improve Agile coaching effectiveness using AI-supported facilitation and content creation
✓ Strengthen your understanding of Scrum roles, artifacts, events, and principles
✓ Apply AI knowledge in Scrum, Agile, and SAFe environments through a hands-on capstone project
Requirements
● No prior AI or ChatGPT experience is required
● No programming or technical background is needed
● Basic familiarity with Agile or Scrum concepts is helpful but not required
● A willingness to learn and experiment with AI tools is sufficient
● Access to a computer, internet connection, and a free ChatGPT account is recommended
Description
AI for Scrum Masters
Accelerate Agile Delivery, Coaching Impact, and Team Effectiveness Using AI and ChatGPT
Accelerate Agile delivery, improve team effectiveness, and elevate your impact as a Scrum Master or Agile Coach using the power of AI, ChatGPT, and Generative AI tools.
This course is a comprehensive, hands-on learning journey designed for Scrum Masters, Agile Coaches, and transformation leaders who want to apply AI practically across Scrum, Agile, and SAFe environments.
Unlock the Power of AI for Scrum Masters and Agile Coaches
In AI for Scrum Masters, you move beyond theory and buzzwords. This course shows you how to practically apply AI tools such as ChatGPT, Microsoft Copilot, Azure AI Studio, and Jasper AI to
• Improve backlog clarity and quality
• Support Product Owners and Developers
• Create high-quality Agile deliverables faster
This course focuses on AI usage specifically tailored for Scrum Masters and Agile Coaches, not generic AI concepts.
1. Getting Started with AI, GenAI, and ChatGPT
• Course introduction, agenda, and certification steps
• Trainer introduction and learning roadmap
• Introduction to ChatGPT, Large Language Models, Foundational Models, and Generative AI
• Create and set up your ChatGPT account
• Understand what OpenAI says about ChatGPT and its limitations
• Learn how GenAI tools like Microsoft Copilot can be used across Agile and Product lifecycles
2. Capstone Project: AI-Powered Agile and Scrum Deliverables
• Hands-on capstone project with real-world Scrum and Agile scenarios
• Use AI to support teams, Product Owners, and stakeholders
• Access reusable templates and key learning resources
3. AI Prompting Framework for Scrum Masters
• Deliverable Creation Framework using ChatGPT
• General ChatGPT Prompt Structure Template
• Learn how to ask better coaching and facilitation questions using AI
• Apply structured prompting techniques for Agile delivery and team coaching
4. Product and Strategy Artifacts Using ChatGPT
Scrum Masters must understand product thinking to coach effectively. In this section, you will learn how AI can support product-related discussions and alignment
• Product Vision Board concepts, prompts, and examples
• Business Model Canvas fundamentals and AI-generated outputs
• Kano Model for feature prioritization
• Market segmentation using ChatGPT
• Porter’s Five Forces for competitive and strategic awareness
5. User Stories, Backlogs, and Agile Delivery with AI
• Generate user stories related to features using ChatGPT
• Understand user stories and the Three Cs
• Improve backlog quality and refinement practices
• Definition of Done and Sprint readiness using AI
6. Responsible AI for Agile and Scrum
• Introduction to Responsible AI
• Ethical and safe use of AI in Agile environments
• Managing accuracy, bias, and citations in AI outputs
• Verification and validation techniques for AI-generated content
7. AI-Powered Presentations for Scrum Masters and Agile Coaches
• ChatGPT prompt templates for crafting presentation outlines
• Generate Sprint Review, Retrospective, and Executive presentations
• Move content from ChatGPT to PowerPoint using VBA
• Transfer content using MS Word and PowerPoint Online
• Enhance slide design using PowerPoint Designer
• Create new presentations from scratch or existing files
8. Agile and Scrum Foundations for Coaching Excellence
• Waterfall vs Agile
• Agile overview, values, and principles
• Definition of Scrum and Scrum Theory
• Scrum pillars, values, and artifacts
• Scrum roles: Developers, Product Owner, Scrum Master, and Stakeholders
• Scrum events: Sprint, Planning, Daily Scrum, Review, and Retrospective
9. Scaling Agile with SAFe for Scrum Masters
• SAFe overview and Big Picture navigation
• Lean-Agile principles
• Scrum at the team level in SAFe
• Scrum Master responsibilities in SAFe
• Agile Release Trains
• PI Planning events, agenda, and benefits
• Requirements and Agile teams in SAFe
• Who Can Benefit from This Course?
• Scrum Masters seeking to increase their impact using AI
• Agile Coaches driving team and enterprise-level transformations
• SAFe practitioners and Agile transformation leaders
• Product Owners and Agile leaders working closely with Scrum teams
• Aspiring Scrum Masters preparing for real-world Agile roles
Why Enroll in This Course?
• Practical, real-world AI use cases for Scrum Masters
• Hands-on capstone project focused on Agile delivery
• Reusable AI prompt frameworks for daily Scrum Master work
• Skills that future-proof your Agile career
• Designed and delivered by an experienced Enterprise Agile Coach
Join the AI-Powered Future of Scrum and Agile Coaching
AI will not replace Scrum Masters. Scrum Masters who use AI will outperform those who do not.
Enroll in AI for Scrum Masters and transform how you coach teams, facilitate Scrum events, support Product Owners, and scale Agile with confidence.
About Me: Vipesh Singla, MBA, Agile Product Management Coach
Embark on a journey of transformation with Vipesh Singla, a seasoned Agile Product Management Coach with an impressive track record. Certified and licensed as a SAFe Agile Coach and SAFe Practice Consultant, I bring a wealth of experience to the table.
Throughout my career, I have played pivotal roles in Agile Transformations and Product Management Assignments for a diverse array of Global 2000 companies. Notably, I’ve collaborated with esteemed clients and employers from prestigious groups such as GAFAM, Big 4, Big Tech, Big Pharma, Fortune 100, and FTSE 100. My versatility shines through various roles, including Product Manager, Product Owner, Scrum Master, and Agile Coach.
Education forms the foundation of my expertise, holding both an MBA and a Bachelor of Engineering degree from one of India’s prestigious institutes. As a certified SAFe SPC/Agile Coach, I bring a proven track record of driving successful Agile transformations.
With a track record that speaks volumes, I am proud to be at the forefront of Agile Product Management coaching. Boasting a remarkable achievement of over 1 Million plus registrations across all my programs, I have had the privilege of influencing and guiding a diverse community of 300,000 unique students.
My digital presence extends globally, reaching enthusiasts and professionals in 200 countries. This widespread outreach has allowed me to connect with a vast audience, transcending language barriers. Our community is not confined to English alone; we thrive in a multilingual environment, with students conversing in 47 languages.
As an Agile Product Management Coach, my commitment is to empower individuals worldwide with the knowledge and skills necessary for success in the dynamic field of product management. Join me on this transformative journey, and let’s navigate the realm of Agile Product Management together.
Who this course is for
■ Agile Coaches supporting teams, programs, or enterprise Agile transformations
■ SAFe practitioners working with Scrum teams in scaled Agile environments
■ Product Owners and Agile team members who collaborate closely with Scrum Masters
■ Aspiring Scrum Masters preparing for real-world Scrum and Agile roles
■ Agile professionals who want a practical, hands-on introduction to using AI in day-to-day Agile work
■ Agile professionals who want a practical, hands-on introduction to using AI in day-to-day Agile work
Homepage
Code:Copy to clipboard

https://www.udemy.com/course/ai-for-scrum-masters

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