Generative AI Foundations Course in Chennai
Learn Generative AI. Understand How Modern AI Works. Build Your AI Foundation.
A live, practitioner-led Generative AI Foundations program for students, working professionals and technology learners who want to understand, use and apply Generative AI effectively.
Learn how modern Generative AI systems work, explore leading AI tools, master practical prompting, understand LLMs, discover RAG and AI agents, and build a strong foundation for advanced AI development.
₹4,999 + GST
Limited seats per cohort
What Is the CraftVoy Generative AI Foundations Course?
CraftVoy Generative AI Foundations is a 4-week, live instructor-led online program for beginners that teaches how Generative AI works, how large language models (LLMs) generate responses, how to write structured prompts, how to choose between AI tools such as ChatGPT, Claude and Gemini, and the fundamentals of Retrieval-Augmented Generation (RAG) and AI agents. No programming experience is required. The fee is ₹4,999 + GST, cohorts are capped at 20 learners, and graduates receive a CraftVoy Certificate of Completion.
- Who it is for:
- Students, working professionals, technology and business professionals, career switchers
- Prerequisites:
- Basic computer and internet skills
- Delivered by:
- CraftVoy, Chennai, led by Vijay Gurunathan
- Next step:
- AI Builder, then AI Engineering
Last updated:
Why Learn Generative AI?
Generative AI is changing how software is built, how businesses operate and how professionals work.
But simply knowing how to use ChatGPT is not enough. To work effectively with Generative AI, you need to understand:
- How Generative AI works
- What Large Language Models are
- How to write effective prompts
- How to select the right AI model and tool
- How to work with text, documents and structured data
- How AI applications use APIs
- What RAG means and why it matters
- How AI agents work
- Where Generative AI can be applied in real-world scenarios
- What it takes to progress from AI user to AI builder
CraftVoy Generative AI Foundations gives you that structured foundation.
Generative AI Foundations at a Glance
| Program | Generative AI Foundations |
|---|---|
| Duration | 4 Weeks |
| Format | Live Instructor-Led |
| Mode | Online |
| Cohort Size | Maximum 20 learners |
| Level | Beginner to Foundation |
| Coding Requirement | Not required |
| Projects | Practical exercises and mini projects |
| Mentorship | Live instructor guidance |
| Assessment | Practical assignments and final assessment |
| Certificate | CraftVoy Certificate of Completion |
| Fee | ₹4,999 + GST |
Who Is This Program For?
Designed for learners who want a structured starting point without immediately committing to a long-term AI Engineering program.
Students
Build practical AI knowledge before entering advanced AI, software engineering or data-related programs.
Working Professionals
Learn how Generative AI can improve productivity, research, analysis, communication and everyday professional workflows.
Software & Technology Professionals
Build a conceptual foundation before progressing into LLM engineering, RAG, AI applications and Agentic AI.
Business & Management Professionals
Understand the capabilities, limitations and enterprise applications of Generative AI.
Career Switchers
Develop a structured foundation before deciding whether to pursue a deeper AI Engineering pathway.
Do I Need Programming Experience?
No. Generative AI Foundations is intentionally designed as a beginner-friendly program. Basic computer and internet skills are sufficient.
You do not need
- Previous AI experience
- Machine Learning experience
- Data Science experience
- A Computer Science degree
- Python programming experience
Learners who already know Python or software development can use this program as a foundation before progressing into AI Builder or AI Engineering.
What You Will Learn: 8-Module Curriculum
From AI fundamentals to LLMs, prompting, RAG, agents and responsible enterprise AI, across four weeks.
Module 01Introduction to Generative AI
Understand the evolution from traditional software and AI to modern Generative AI.
Introduction to Generative AI
Understand the evolution from traditional software and AI to modern Generative AI.
- Artificial Intelligence fundamentals
- Machine Learning vs Generative AI
- Generative AI vs traditional AI
- Generative AI use cases
- What changed with modern AI
- AI models and AI applications
- Capabilities and limitations of Generative AI
- Responsible use of AI
Outcome: You will understand where Generative AI fits within the broader technology landscape.
Module 02Understanding Large Language Models
Understand the technology behind modern text-generation systems.
Understanding Large Language Models
Understand the technology behind modern text-generation systems.
- What is an LLM?
- How LLMs generate responses
- Tokens and context
- Training and inference
- Parameters and model capabilities
- Context windows
- Foundation models
- Model limitations
- Hallucinations
- Knowledge cutoff and model knowledge
- Model selection basics
Outcome: You will be able to explain the basic architecture and behaviour of modern LLM-based systems.
Module 03Prompt Engineering
Learn how to communicate effectively with Generative AI systems.
Prompt Engineering
Learn how to communicate effectively with Generative AI systems.
- Prompt fundamentals
- Instruction design
- Context and constraints
- Role-based prompting
- Few-shot prompting
- Structured prompting
- Output formatting
- Prompt refinement
- Reasoning-oriented prompting
- Prompt evaluation
- Common prompting mistakes
Outcome: Move from simply asking AI questions to designing structured AI interactions. Practice prompts for research, summarization, content generation, data analysis, business analysis, technical assistance, document processing and structured outputs.
Module 04Generative AI Tools & AI Workflows
Explore how modern AI tools can be used for different tasks.
Generative AI Tools & AI Workflows
Explore how modern AI tools can be used for different tasks.
- ChatGPT
- Claude
- Gemini
- Microsoft Copilot
- AI-assisted research
- AI-assisted writing
- AI-assisted analysis
- AI-assisted coding
- Document interaction
- Multimodal AI
- Image and content generation
- Comparing AI models
- Choosing the right AI tool
Outcome: Practical exercise: design a personal or professional AI Productivity Workflow.
Module 05From AI User to AI Application
Understand what happens behind the interface of an AI application.
From AI User to AI Application
Understand what happens behind the interface of an AI application.
- AI application architecture
- LLM APIs
- API requests and responses
- System prompts
- User prompts
- Context
- AI application workflow
- Model selection
- AI application cost considerations
- AI security basics
Outcome: Understand the difference between using an AI tool and building an application that uses AI.
Module 06Introduction to RAG
Understand one of the most important concepts in modern enterprise AI.
Introduction to RAG
Understand one of the most important concepts in modern enterprise AI.
- What is Retrieval-Augmented Generation?
- Why LLMs need external knowledge
- Documents and knowledge bases
- Embeddings
- Vector databases
- Retrieval
- Context augmentation
- RAG workflow
- RAG use cases
- Basic RAG architecture
Outcome: Mini project: design a conceptual Document Q&A Assistant.
Module 07Introduction to AI Agents
Understand the evolution from AI chatbots to AI agents.
Introduction to AI Agents
Understand the evolution from AI chatbots to AI agents.
- What is an AI agent?
- AI assistant vs AI agent
- Tools and function calling
- Agent workflows
- Planning
- Memory
- Multi-step tasks
- Agent use cases
- Agent limitations
- Introduction to Agentic AI architecture
Outcome: Mini exercise: design an AI agent workflow for a real-world business scenario.
Module 08Responsible & Enterprise Generative AI
Learn why enterprise AI requires more than a powerful model.
Responsible & Enterprise Generative AI
Learn why enterprise AI requires more than a powerful model.
- AI governance fundamentals
- Data privacy
- Security considerations
- Responsible AI
- Hallucination management
- Human oversight
- Enterprise AI risks
- Intellectual property considerations
- AI usage policies
- Introduction to AI governance
Outcome: Understand the difference between experimenting with AI and responsibly using AI in an organization.
Practical Learning: Projects and Exercises
This is not a purely theoretical Generative AI course. You will work on hands-on exercises throughout the program.
AI Productivity Assistant
Design an AI workflow for a professional productivity use case.
Prompt Engineering Challenge
Create and evaluate prompts for different business and technical scenarios.
AI Model Comparison
Compare different Generative AI models for specific tasks.
Document Q&A Concept
Design a basic RAG-based document assistant.
AI Agent Workflow
Design an agentic workflow for a practical business scenario.
Generative AI Solution Concept
Create a complete solution concept for a real scenario.
The final mini project covers
- Business problem
- AI use case
- Model selection
- Prompt strategy
- Data requirements
- RAG / agent consideration
- Architecture concept
- Risks
- Responsible AI considerations
What You Will Be Able to Do After the Program
- Explain Generative AI and LLM fundamentals
- Use major Generative AI tools effectively
- Design structured prompts
- Evaluate AI responses
- Compare AI models for different use cases
- Understand LLM APIs
- Understand basic AI application architecture
- Explain RAG architecture
- Explain AI agent concepts
- Identify practical AI use cases
- Recognize key AI risks
- Design a basic Generative AI solution
- Decide your next AI learning pathway
Tools & Technologies
Depending on the exercises and cohort, learners may work with selected tools. The emphasis is not on memorizing tools. The objective is to understand how to select and apply the right AI capability for the right problem.
- ChatGPT
- Claude
- Gemini
- Microsoft Copilot
- OpenAI APIs
- Python
- GitHub
- VS Code
- RAG tools
- AI development platforms
Live. Practical. Structured.
CraftVoy programs are designed around learning by doing, rather than simply watching recorded videos.
Live Sessions
Attend instructor-led sessions where concepts are explained and demonstrated.
Practical Exercises
Apply concepts immediately through guided activities.
Real-World Scenarios
Work through business and technology use cases rather than isolated examples.
Instructor Guidance
Get support while working through exercises and projects.
Peer Learning
Learn alongside a small cohort of other AI learners.
Cohort Structure: Maximum 20 Learners
The program is intentionally kept as a controlled cohort rather than a mass recorded course. This allows the instructor to:
- Answer questions
- Review exercises
- Conduct practical demonstrations
- Discuss individual use cases
- Provide learning guidance
- Maximum: 20 learners
Program Eligibility
- Minimum requirements
- Basic computer knowledge, basic internet usage, ability to attend live sessions and interest in Generative AI
- Programming
- Not required. Programming knowledge is an advantage but is not a prerequisite.
- Age
- Recommended for learners 16 years and above
Assessment & Certification
Learners complete practical exercises and a final assessment. Successful completion demonstrates understanding of:
- Generative AI fundamentals
- Prompt engineering
- LLM concepts
- AI workflows
- RAG fundamentals
- Agentic AI concepts
- Responsible AI
A CraftVoy Certificate of Completion is provided upon meeting the program requirements.
The certificate validates program completion. The primary value of the program is the knowledge, practical experience and portfolio developed during the learning journey.
What Is Included in Your Program Fee?
Live Instructor-Led Sessions
Structured weekly learning with an experienced technology practitioner.
Practical Labs
Hands-on exercises designed around real AI workflows.
Project Guidance
Guidance for your practical assignments and final mini project.
Learning Materials
Structured resources and reference materials.
AI Technology Environment
Access to selected AI tools and technology resources required for program activities, subject to applicable usage limits and platform policies.
Assessments
Practical assignments and final assessment.
Certificate
CraftVoy Certificate of Completion.
You don't need to purchase an expensive AI course bundle, or hold any prior AI, Machine Learning or Data Science certification, a Computer Science degree or professional AI experience.
Generative AI Foundations vs AI Engineering
Not sure which CraftVoy program is right for you?
| Attribute | Generative AI Foundations | AI Engineering |
|---|---|---|
| Level | Beginner | Intermediate–Advanced |
| Duration | 4 weeks | 24 weeks |
| Coding | Not required | Required |
| Focus | Understand & apply GenAI | Engineer AI systems |
| Projects | Practical exercises & mini projects | 6+ projects + enterprise capstone |
| Cohort | Up to 20 | Maximum 10 |
| Fee | ₹4,999 + GST | ₹34,999 + GST |
| Best for | AI beginners | Serious AI engineering learners |
The progression: Learn AI → Build AI → Engineer AI
If you are new to Generative AI, start with Generative AI Foundations. If you already have strong programming fundamentals and want to build professional AI systems, consider AI Engineering.
Your CraftVoy AI Learning Path
Step 1 — Learn AI (You are here)
Generative AI Foundations
Understand modern AI and build your foundation.
Why CraftVoy?
Build Skills. Build Technology. Build Your Future.
Our programs are designed by technology practitioners with real-world experience across software engineering, cloud, enterprise architecture, AI and digital transformation.
Rather than treating AI as a collection of tools, CraftVoy approaches learning through Fundamentals → Practical Application → Engineering → Architecture. This helps learners understand not only how to use AI, but also how AI systems fit into real technology environments.
Learn Directly from an Industry Expert
Vijay brings over 17 years of hands-on enterprise technology experience across AI, cloud, and solution architecture. Having worked with global enterprises in automotive, manufacturing, and analytics, he mentors students with real-world case studies and proven engineering frameworks not just textbook theory.
Learn From Enterprise Technology Experience
CraftVoy is founded by Vijay Gurunathan, a technology architect and entrepreneur with 17+ years of experience across software engineering, enterprise architecture, cloud, AI and digital transformation. His professional experience spans technology environments across automotive, manufacturing, telecom, retail, CPG and other enterprise domains.
Frequently Asked Questions
What is Generative AI?
What is the CraftVoy Generative AI Foundations program?
How much does the Generative AI Foundations course cost?
Is this a Generative AI course for beginners?
Do I need Python to join?
Is this a ChatGPT course?
Will I learn Prompt Engineering?
Will I learn RAG?
Will I learn AI Agents?
Is coding required?
How many learners are in a cohort?
How long is the program?
Is it live or recorded?
Is the course available in Chennai?
Do I get a certificate?
What happens after Generative AI Foundations?
Is this suitable for working professionals?
Is this suitable for college students?
How is this different from a self-paced AI course?
Program Investment
Generative AI Foundations
₹4,999 + GST
4 Weeks · Live Instructor-Led · Practical Learning · Maximum 20 Learners
What's included:
- Live sessions
- Practical exercises
- AI tool exploration
- Prompt Engineering
- LLM fundamentals
- RAG fundamentals
- AI Agent fundamentals
- Mini projects
- Final assessment
- Learning resources
- CraftVoy Certificate of Completion
Limited seats per cohort. Cohort dates and availability are confirmed by CraftVoy before enrollment.
Not Sure Where to Start?
Take the CraftVoy AI Readiness Assessment. We will help you identify whether you should start with Prompt Engineering, Generative AI Foundations, AI Builder or AI Engineering.
Take AI Readiness AssessmentBuild Your AI Foundation
Generative AI is moving beyond experimentation. The next generation of technology professionals will need to understand how AI works, how to apply it responsibly and how AI systems can be integrated into real-world technology environments.
Learn Generative AI. Understand Modern AI. Prepare to Build.