GenAI Bootcamp

1. Introduction to Artificial Intelligence (AI)
2. What AI is and how it’s used in everyday life
3. Overview of ML, DL, and Data Science (DS)
4. Simple explanation of Machine Learning, Deep Learning, and Data Science
5. Key differences with real-world examples
6. Generative AI (GenAI) – Concepts & Applications

1. Popular use cases: content creation, images, coding, business
2. Hands-On Activity
3. Try free GenAI tools for text generation
4. Create sample AI-generated images

1. Introduction to Gen AI Tools
2. Explore and experiment with popular Generative AI tools
3. Get Started with Co-Pilot
4. Quickly build a simple website using Co-Pilot
5. Try out review and test creation with Co-Pilot
6. Try free GenAI tools (ChatGPT).
5. Create a poem, generate an image, and compare results.

1. How LLMs like GPT & Claude work
2. Industry adoption & future scope
3. Hands-On: Compare answers from GPT vs. Claude

1. How to write better prompts
2. Role prompting, examples, and best practices

1. Students create prompts for different tasks (coding, Q&A, writing)
2. Chat Summarization & Conversational AI
3. Using AI for summarizing content & conversations
4. Hands-On: Summarize a long article or chat transcript
5. AI in Customer Experience – Agent & CSAT Scoring
6. How AI is transforming customer support
7. Hands-On: AI scoring of sample support chats

1. AI-Based Performance Testing
2. Using AI to automate testing processes
3. Hands-On: Automating simple test cases with AI

1. Step 1: Connect to an LLM (GPT/Claude API or sandbox)
2. Step 2: Design a prompt flow
3. Step 3: Deploy a working chatbot
4. Hands-On Lab: Students build & test their chatbot
5. Real-World AI Tools & Frameworks
6. Real-World AI Tools & Frameworks
7. Hugging Face, LangChain, OpenAI Playground, Claude AI
8. Spotlight on Claude AI – Features & Use Cases
9. Quiz & Open Q&A
10. Hackathon-Style Showcase
11. Students present chatbot outputs
12. Peer feedback and discussion

1. LangChain, LlamaIndex, HuggingFace, Pinecone, FAISS.
2. No-code AI platforms.

1. AI Ethics & Responsible Use
2. Bias, hallucinations, deepfakes, data privacy.
3. Quiz + Open Q&A

1. Students present chatbot results.
2. Feedback session.

1. Multi-Modal AI – Beyond Text
2. Image + Text → Captions, Visual Q&A.
3. Speech-to-Text (Whisper, Deepgram), Text-to-Speech (ElevenLabs).
4. Video generation & editing (Runway, Pika).

1. Generate captions for an image.
2. Convert text into voice.
3. Explore a free speech-to-text tool.

1. Healthcare (diagnosis assistants, radiology).
2. Finance (fraud detection, advisory).
3. E-commerce (personalized shopping).
4. EdTech (AI tutors, adaptive learning).

1. Students pick a domain (banking, healthcare, retail).
2. Build an AI-powered solution prototype (with prompts, chatbot, or workflow).

1. Why context improves answers.
2. Tools: LangChain + FAISS + Vector DBs.

1. Upload custom data (PDF, notes).
2. Query AI on that dataset.

1. APIs, integration into apps (Slack bots, WhatsApp bots).
2. Team-based AI mini-hackathon kickoff.

1. Build a small GenAI app (chatbot, summarizer, tutor, support bot).
2. Must include: prompt engineering + deployment + demo.

1. Each team presents their project (5-min pitches).
2. Judges/mentors Q&A.
Wrap-Up:

Key takeaways.
1. Future skills roadmap (AI Ops, Agents, Autonomous AI).
2. Certificate distribution & group photo.