Gen AI Course for Beginners
This course is designed for AI enthusiasts who want hands-on experience building end-to-end Generative AI applications. Through real-world use cases and practical exercises, you'll learn how to leverage the power of Large Language Models (LLMs) to automate tasks and build intelligent solutions. You'll master the fundamentals of Gen AI, including embeddings, vector databases, and the core principles of Retrieval Augmented Generation (RAG). The course focuses on building robust applications using the LangChain framework, covering essential concepts like document loaders, text splitters, and chain architectures. You will then apply this knowledge to build two complete projects: an Equity Research Tool for processing financial news and a Retail Q&A Tool for querying structured database information. By the end, you'll have a clear understanding of the full Gen AI development lifecycle, from foundational concepts to deploying functional, production-ready AI applications.
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This micro course includes:
- 03h:17m:18s on-demand videos
- 10 Lectures
- 1 Quiz (paid access)
- Access on any Device
- Certificate of completion (paid access)
Course Curriculum
10 Lectures | 03h:17m:18s
1:
Gen AI Course and Projects
10 Lectures
-
1.1: Overview
Free -
1.2: What is Gen AI
Free -
1.3: Gen AI Evolution
Free -
1.4: What is LLM
Free -
1.5: Embedding Vector DB
Free -
1.6: What is RAG (Retrieval Augmented Generation)?
Free -
1.7: Tooling for Gen AI
Free -
1.8: Langchain Fundamentals
Free -
1.9: Project 1: News Analysis - Financial Domain
Free -
1.10: Project 2: Q&A System - Retail Domain
Free
Course Instructor/Creator
Get Certified
When You Complete This Course
You receive a ‘Certificate of Completion’ signed and addressed personally by me, your guide and mentor. – Dhaval Patel
Add and share this certificate with your Resume/CV or on your LinkedIn profile.
This micro course includes:
- 03h:17m:18s on-demand videos
- 10 Lectures
- 1 Quiz (paid access)
- Access on any Device
- Certificate of completion (paid access)
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