Skills You'll Acquire
Generative AI Concepts
Building AI Agents
Workflow Automation with LangChain
Advanced Prompt Engineering
Hugging Face
Hugging Face
RAG
Basic knowledge of Python, PyTorch, and transformer architecture. You should also be familiar with machine learning and neural network concepts.
Learn the principles, applications, and workflows of RAG
Apply RAG, PyTorch, Hugging Face, LLMs, and LangChain technologies to different applications
Develop skills to craft effective prompts for accurate and context-aware responses
Understand LangChain’s tools, components, and chat models
Simplify application development using LangChain and large language models (LLMs)
Curriculum
This Course contains 4 Modules.
Introduction to Retrieval-Augmented Generation (RAG)
Understanding encoders, tokenizers, and the FAISS library
Hands-on labs
Implementing RAG with Hugging Face
Applying RAG with PyTorch
Practice quizzes and assessments
Introduction to Retrieval-Augmented Generation (RAG)
Understanding encoders, tokenizers, and the FAISS library
Hands-on labs
Implementing RAG with Hugging Face
Applying RAG with PyTorch
Practice quizzes and assessments
Introduction to Retrieval-Augmented Generation (RAG)
Understanding encoders, tokenizers, and the FAISS library
Hands-on labs
Implementing RAG with Hugging Face
Applying RAG with PyTorch
Practice quizzes and assessments
Introduction to Retrieval-Augmented Generation (RAG)
Understanding encoders, tokenizers, and the FAISS library
Hands-on labs
Implementing RAG with Hugging Face
Applying RAG with PyTorch
Practice quizzes and assessments
