Retrieval Augmented Generation for Production with LangChain & LlamaIndex
Gen AI 360 Foundational Model Certification
Hear from Gen AI 360 Certification takers
“Probably one of the most complete end to end LLM resources I have seen so far. Even if you are more advanced in GenAI and LLMs, there are still many things you might be interested in learning and are likely new for you. Very much recommended.”
Xavier (Xavi) Amatriain, VP of Engineering - Product AI Strategy, LinkedIn“@activeloopai @LangChainAI I signed up Wednesday and having been working through it.. insane quality for $0. 🤝”
Andrew Riley“Two of the things that make this certification different from every other LangChain course I've seen: 1. It's very extensive! It could be a book. 2. You'll work on industry-specific projects.”
Santiago @svpino“Yesterday I completed enough of @activeloopai‘s course to build something useful with #langchain Today a company owner liked the customer service bot I built for him and asked me to put it on his website. ZERO TO ONE BABY. Next: 1 to 10.”
Alex North Rule“Another great resource to stay ahead in the game - The Gen AI 360 Foundational model extensive course by @activeloopai Check it out : https://learn.activeloop.ai/courses/langchain 🚀🚀✨”
Abhishek RanjanCourse Introduction | Gen AI 360 Foundational Model Certification
Course Introduction and Logistics
Module 1 Introduction - Basics of Retrieval Augmented Generation with Langchain and LlamaIndex
LangChain: Basic Concepts Recap
Introduction to LlamaIndex by Jerry Liu, LlamaIndex CEO
Overview of Retrieval Augmented Generation and Its Components with LlamaIndex CEO Jerry Liu
LlamaIndex Introduction: Precision and Simplicity in Information Retrieval
Challenges with Naive RAG & How to Evaluate RAG Applications with LlamaIndex CEO Jerry Liu
Chat with Your Code: LlamaIndex and Activeloop Deep Lake for GitHub Repositories 🦙🌊
RAG Basics Quiz
Module 2 Introduction - Advanced Retrieval Augmented Generation
Brief Overview of Available Techniques: Fine-tuning, RAG; Activeloop’s Deep Memory
When to do what using LLMs? RAG vs Fine-Tuning vs Deep Memory vs Training LLM from Scratch
Using Deep Memory to Boost Retrieval Accuracy up to 22% on Average
Mastering Advanced RAG Techniques with LlamaIndex
Production-Ready RAG Solutions with LlamaIndex
Iterative Optimization of LlamaIndex RAG Pipeline: A Step-by-Step Approach
How to Use Deep Memory with LlamaIndex to Get +15% RAG hit_rate Improvement for Question Answering on Docs?
Use Deep Memory with LangChain to Get Up to +27% Increase in Accurate Questions Answers to LangChain Code DB
Deep Memory with LangChain RAG Applications Across Legal, Financial, and Biomedical Industries
Advanced Retrieval Augmented Generation (RAG) for Pharmaceuticals: Pill Search
Advanced Retrieval Strategies: Deep Memory, Small to Big Retrieval, Structured and Unstructured Data, Parsing Tables and mroe
Use OpenAI CLIP, LangGraph, & RAG to Generate Competitive Restaurant Insights
Advanced RAG Quiz
Build an AI QR Code Generator with ControlNet, Stable Diffusion, and LangChain
Next-Level Automation: Data Agents In LlamaIndex
Module 3 Introduction - Retrieval Augmented Generation Agents
LangChain Overview: Agents, Tools, and OpenGPT Introduction
LlamaIndex RAG-AGENT: Query and Summarize Over Database
Crafting AI Assistants via OpenAI and Hugging Face API
Building a Multi-Modal Financial Document Analysis and Recall for Tesla Investor Presentations
Smart Shopping Assistant with Deep Lake & LlamaIndex - Introduction
Building a Smart Shopping Assistant with DeepLake and LlamaIndex
PatentPT: How We Finetuned a Large Language Model and Built a Retrieval Engine to Search & Generate Patents
RAG Agents Quiz
Module 4 Introduction - Retrieval Augmented Generation Evaluation and Observability
RAG - Metrics & Evaluation
LangSmith Introduction
RAG Evaluation and Observability Quiz
Introducing the Towards AI Tutor Bot, powered by Activeloop and Intel
Building Fullstack Applications with LlamaIndex: LlamaPacks & more
Technical Report: Boosting Cosine Similarity & Retrieval Accuracy with Intel CPUs & Deep Memory
Interview Jerry Liu on the Future of AI: LlamaIndex, LLMs, RAG, Prompting and more
Activeloop, Towards AI, & Intel Disruptor Initiative
“In the rapidly evolving business landscape, leveraging Retrieval Augmented Generation (RAG) tools like LlamaIndex & Deep Lake by Activeloop is essential for enterprises seeking a competitive edge in GenAI. This course is tailored to quickly upskill your team in GenAI workflows, emphasizing the integration of Activeloop's advanced features like Deep Memory with LlamaIndex for unmatched retrieval accuracy. It's a strategic investment to enhance your team's capabilities, ensuring your enterprise stays at the forefront of AI innovation.”
Jerry Liu, CEO & Co-Founder, LlamaIndex“I believe that engineers and technology executives could benefit greatly from this course to stay at the forefront of AI. Intel continues to be at the vanguard of AI and new technology adoption. This Foundational Model Certification could help better equip the next generation of innovators with what they need to succeed with Generative AI and Large Language Models. It could also contribute to the broader adoption of AI applications and solutions across various industries.”
Arijit Bandyopadhyay, CTO – Enterprise Analytics & AI, Head of Strategy – Cloud & Enterprise, DCAI Group, Intel Corporation“Enterprises are investing in LLM applications across industries. However, there's a huge knowledge gap in how to train and fine-tune LLMs, and what software and hardware stack is needed for it. Gen AI 360-certified developers will be able to apply state-of-the-art methods and construct cost-effective and efficient solutions that won't break the bank while delivering full performance with advanced AI technologies like Deep Lake and performant hardware like 4th Generation Intel® Xeon® Scalable Processors.”
Davit Buniatyan, CEO Activeloop“We're passionate about educating and upskilling engineers in this rapidly growing field. That's why we've designed this practical course to implement AI into company processes or use LLMs to build entirely new products.”
Louie Peters, CEO Towards AIAs all of these technologies enter from bleeding edge to leading edge, it can be frustrating not having consistent examples or documentation to help carve away at the features Im desiring to implement both personally and for my employers. This...
Read MoreAs all of these technologies enter from bleeding edge to leading edge, it can be frustrating not having consistent examples or documentation to help carve away at the features Im desiring to implement both personally and for my employers. This was an absolutely incredible overview of LangChain, coupled with fantastic real world examples (with reasoning and failed attempts nonetheless). This course gave me everything I needed to iterate step by step on a few product features I've been exploring for work, as well as additional capabilities of both AI and LangChain that will be hard for my colleagues to believe are possible. I can't recommend this course enough and I've been eagerly awaiting completing it so I can show off my certificate and urge people to get their own. I'm super grateful to activeloop and team for organizing all these wonderful documents and examples and explaining it clearly and intentionally. This has supercharged my career and skills for the foreseeable future!
Read LessI didn't expect much. There are some tutorials out there covering most of the stuff found here. I mean, how hard can writing a prompt really be? As it turns out, you can get pretty darn advanced with it. This is literally the only course I've foun...
Read MoreI didn't expect much. There are some tutorials out there covering most of the stuff found here. I mean, how hard can writing a prompt really be? As it turns out, you can get pretty darn advanced with it. This is literally the only course I've found regarding Langchain that is as serious as a heart attack. Most are only high level overviews. This is the real deal. And it's free...
Read LessThis course is FANTASTIC! I have tried to navigate Langchain for a while now, due to their being so much functionality, I found it hard to grasp all the concepts. Not only did this course give me a great overview, it was packed with exciting proje...
Read MoreThis course is FANTASTIC! I have tried to navigate Langchain for a while now, due to their being so much functionality, I found it hard to grasp all the concepts. Not only did this course give me a great overview, it was packed with exciting projects. I made my own course material chatbot half way through, it was made so simple for me. Can't wait for more!! Thank you so much for making this accessible!
Read Lesscourse is really good. Course is very detailed with very good examples.
course is really good. Course is very detailed with very good examples.
Read LessLangchain is a framework to create chatbots and other AI apps on given data stored in vector databases. Deep Lake is great as it is a database used to store data of all types audio, videos, text etc. for LLMs. Highly recommend
Langchain is a framework to create chatbots and other AI apps on given data stored in vector databases. Deep Lake is great as it is a database used to store data of all types audio, videos, text etc. for LLMs. Highly recommend
Read LessVery nice course and amazing projects.
Very nice course and amazing projects.
Read LessFound it really helpful. It covers theory and projects, both. The way codes are explained by guiding on developing amazing applications is quite compelling. Strongly recommend it to every AI developer. Thanks a lot!
Found it really helpful. It covers theory and projects, both. The way codes are explained by guiding on developing amazing applications is quite compelling. Strongly recommend it to every AI developer. Thanks a lot!
Read LessThe course has a lot of valuable information and many great examples to understand in deep the concepts presented.
The course has a lot of valuable information and many great examples to understand in deep the concepts presented.
Read LessGreat content and use cases are well crafted. enjoyed the whole learning.
Great content and use cases are well crafted. enjoyed the whole learning.
Read LessThe course is absolutely free to take. You do need a paid OpenAI account or alternatively, build the example projects with Open-Source LLM models. As a result20, you can still complete the course and pass chapter quizzes without running these projects or paying anything.
Yes, you will get Gen AI 360 Certified upon completion.
Our quickest learners have completed the course as quickly as in 15 hours, but the average course completion time is 20+ hours of learning.
Please know that prior knowledge of coding and Python is a prerequisite. You are not expected to have prior LlamaIndex knowledge but certain familiarity would be useful. You can learn LangChain from scratch in our previous course at learn.activeloop.ai/courses/langchain.
We've designed the course in a way that would be valuable for non-technical executives as well. To make the most out of it, however, you do need to be technical as it involves a lot of hands-on projects.
Intermediate Python Knowledge
Basic Knowledge of Jupyter & Gradio
Basic Knowledge of GitHub
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