Course
Generative AI Training
Unlock the power of Generative AI with our structured training program designed for students, developers, and AI enthusiasts.
Learn the fundamentals of AI, Large Language Models (LLMs), RAG, LangChain, and real-world AI applications. Develop hands-on projects and gain industry-aligned skills to build cutting-edge AI solutions.
Intake starts
March 31, 2025
Course Fee
Rs. 35,000
What you will learn
- Python foundations for AI applications
- Generative AI principles and prompt engineering
- API integration and LangChain for AI workflows
- Building and optimizing Retrieval-Augmented Generation (RAG) systems
- AI model evaluation and optimization techniques
- Hands-on capstone project with real-world applications
Course Syllabus
Week 0: Orientation Session
- Overview of Generative AI and course logistics
- Tools and resources for the training
- Learning objectives and expected outcomes
Weeks 1-2: Foundations of Python for AI
- Python basics: Syntax, data types, control structures
- Essential libraries: NumPy, Pandas, Matplotlib
- Hands-on: Mini-project on data analysis
Week 3: Introduction to Generative AI and LLMs
- Evolution of AI: Traditional models to neural networks
- Mechanics & applications of Generative AI
- Prompt Engineering: Writing effective prompts for AI models
- Activity: Interactive prompt writing with ChatGPT
Weeks 4-5: Advanced Prompt Engineering & API Integration
- Techniques: Zero-shot, few-shot, chain-of-thought prompting
- API usage: Connecting and handling responses
- Workshop: Build an AI-powered app with ChatGPT API
Week 6: Implementing AI Solutions with LangChain
- Introduction to LangChain for AI development
- Implementing LangChain in real-world workflows
- Project: Develop a collaborative AI use case
Week 7: Fundamentals of Retrieval-Augmented Generation (RAG)
- How RAG improves AI response quality
- Technologies: Tokens, embeddings, vector databases
- Discussion on practical applications of RAG
Week 8: Implementing and Optimizing RAG
- Building a basic RAG system
- Performance tuning and optimization
- Case Study: Real-world RAG applications
Week 9: Evaluation and Optimization of GenAI application
- GenAI model evaluation metrics: BLEU, ROUGE, BERTScore
- Strategies for fine-tuning and optimization
- Workshop: Evaluating GenAI applications on real datasets
Week 10: Practical Applications & Case Studies
- Real-world AI applications across different industries
- Guest lectures from AI industry experts
- Interactive Q&A with professionals
Weeks 11-12: Capstone Project
- End-to-end AI project: From ideation to deployment
- Peer reviews and iterative improvements
- Final presentation to an audience, including industry experts
Skill level
Beginner to Intermediate
Duration
12 weeks
Prerequisites
Basic programming knowledge (Python preferred)
Format
Hybrid (Live Sessions + Self-Paced Learning)
Hands-on Projects
Why Take This Course?
Who should take this course?
Aspiring AI developers
looking to build GenAI applications
Software engineers
wanting to expand into AI/ML
Students & researchers
exploring AI-powered solutions
Product managers & startup founders
interested in AI-driven innovation