GenAI Launchpad - Skillancy

About Course

In this course you will learn to Build, Deploy, Scale with the help of Generative AI

Course Content

Pre-Phase – AI Foundations =>

Module 1: ML Concepts for GenAI (2 weeks – 8 Hours)

Module 2: Introduction to AI & GenAI Foundations (0.5 Weeks – 2 Hours)

Phase 1 – Foundation GenAI =>

Module 3: Introduction to AI & GenAI Foundations (0.5 Weeks – 2 Hours)

Module 4 : Prompt Engineering Fundamentals (1 Week – 4 Hours)

Module 5: Problem-Solving with GenAI (0.5 Week – 2 Hours)

Phase 2 – Advanced GenAI =>

Project 1 : RetailGenie AI (2 Weeks – 12 Hours)

Project 2: InfoNavigator AI (1.5 Weeks – 8 Hours)

Project 3: DocuMind AI (2 Weeks – 10 Hours)

About Course

Course Content

Pre-Phase – AI Foundations =>

Module 1: ML Concepts for GenAI (2 weeks – 8 Hours)

Session 1 (2 Hours)

Session 2 (2 Hours)

Session 3 (2 Hours)

Session 4 (2 Hours) – Demo

End Goal – Understand how ML paradigms connect to GenAI training (supervised, unsupervised, RLHF).

Module 2: Introduction to AI & GenAI Foundations (0.5 Weeks – 2 Hours)

Session 1 (2 Hours)

End Goal – Understand basic AI concepts & run first GenAI demo.

Phase 1 – Foundation GenAI =>

Module 3: Introduction to AI & GenAI Foundations (0.5 Weeks – 2 Hours)

Session 1 (2 Hours)

End Goal – Identify and classify real-world GenAI applications across domains; present a comparative analysis of underlying models.

Module 4 : Prompt Engineering Fundamentals (1 Week – 4 Hours)

Session 1 (2 Hours)

Session 2 (2 Hours)

End Goal – Design and test effective prompts for summarization, Q&A, and creative writing; compare zero-shot, few-shot, and chain-of-thought results.

Module 5: Problem-Solving with GenAI (0.5 Week – 2 Hours)

Session 1 (2 Hours)

End Goal – Frame a real-world problem, design a GenAI-powered prototype, and present a structured evaluation comparing prompt strategies.

Phase 2 – Advanced GenAI =>

Project 1 : RetailGenie AI (2 Weeks – 12 Hours)

Sessions 1–2 (4 Hours) — Strategy & LLM Context

Sessions 3–4 (4 Hours) — Core Prompts

End Goal – AI-powered retail assistant chatbot deployed on Flask for order tracking, FAQs, and recommendations.

Project 2: InfoNavigator AI (1.5 Weeks – 8 Hours)

Sessions 1–2 (4 Hours) — Embeddings & Vectorstore

Sessions 3–4 (4 Hours) — Search, Q&A & Demo

End Goal – AI research assistant that performs semantic search and Q&A over large document repositories.

Project 3: DocuMind AI (2 Weeks – 10 Hours)

Sessions 1–2 (4 Hours) — Architecture & Ingestion

Sessions 3–4 (4 Hours) — Fine-tuning & Indexes

Session 5 (2 Hours) — Smart Features & Deploy

End Goal – Domain-specific document assistant for finance/legal/medical data with smart retrieval and compliance alerts.

Skillancy

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