Free Course on Training & Fine-Tuning LLMs for Production

Training & Fine-Tuning LLMs for Production

Gen AI 360 Foundational Model Certification

Enroll for free

Course Curriculum

1. Training & Fine-Tuning LLMs for Production | Gen AI 360 Foundational Model Certification
2. Course modules breakdown | Gen AI 360 Foundational Model Certification
3. Course Introduction and Logistics
1. Introduction to LLMs Module
2. What are Large Language Models
3. The Evolution of Language Modeling up to LLMs
4. A Timeline of Large Language Models
5. Emergent Abilities in LLMs
6. The Most Popular Proprietary LLMs
7. Open-Source LLMs
8. 7 tips to Mitigate Hallucinations and Biases in Large Language Models
9. Understanding Hallucinations and Bias
10. Applications and Use-Cases of LLMs
11. Intro to LLMs Quiz
1. Understanding Transformers and GPTs Introduction
2. Understanding Transformers
3. Transformers Architectures
4. Focus on the GPT Architecture
5. Evaluating LLM Performance
6. How to Tune your Language Models: Pro Tips for Improving AI Responses and Performance
7. Controlling LLM Outputs
8. Prompting and Few-Shot Prompting
9. Pretraining and Fine-Tuning of LLMs
10. Understanding Transformers and GPT Quiz
1. Training LLMs Module
2. When to Train an LLM from Scratch
3. What is LLMOps
4. Overview of the Training Process
5. Deep Lake and Data Loaders
6. How to train NanoGPT with Deep Lake streamable dataloader
7. Datasets for Training LLMs
8. Train an LLM in the Cloud
9. Going at Scale with LLM Training
10. Master LLMs: Top Strategies to Evaluate LLM Performance
11. Benchmarking Your Own LLM
12. Domain-Specific LLMs
13. Training Large Language Models from Scratch Quiz
1. RAG vs Fine-Tuning vs Deep Memory vs training LLM from Scratch: when to do what with LLMs
2. Fine-Tuning LLMs Module
3. Techniques for Fine-Tuning LLMs
4. Deep Dive into LoRA and SFT
5. Fine-tuning using LoRA and SFT
6. Fine-Tuning Large Language Models Quiz
7. How to Fine-Tune your LLM on Tweets! (large language models for investing)
8. Fine-Tuning using SFT for Financial Sentiment
9. Fine-Tuning using Cohere for Medical Data
10. Fine-Tune LLMs with AWS and TorchTune
1. Improving LLMs with RLHF Module
2. The Secret of LLMs - Reinforcement Learning from Human Feedback
3. Deep Dive into RLHF
4. Improving Trained Models with RLHF
5. Improving LLMs with RLHF Quiz
1. 5 Essential Steps to Building Language Models Apps
2. Deploying LLMs Module
3. Challenges of LLM Deployment
4. Model Quantization
5. Model Pruning
6. Deploying an LLM on a Cloud CPU
7. Deploying LLMs Quiz
1. Advanced Topics and Future Directions Module
2. Introduction to Large Multimodal Models
3. Scaling Laws in LLM Training
4. ReAct framework and ChatGPT plugins
5. Expanding the Context Window
6. Training on Generated Data and Model Collapse
7. Next Challenges in LLM Research
8. Advanced Topics and Future of LLMs Quiz

Course Highlights

Free
67 lessons
1.5 hrs of high-level video content
10 practical projects with Fine-Tuning on 4th Generation Intel® Xeon® Scalable Processors, SFT, RLHF, and LoRA, custom model training with Cohere
40 hours of learning content

Brought to you in collaboration with

Activeloop, Towards AI, & Intel Disruptor Initiative

Activeloop, Towards AI, and Intel Disruptor Initiative collaborate to bring Foundational Model Certification to tomorrow’s Gen AI professionals, executives and enthusiasts. The Foundational Model Certification is your essential gateway to mastering Large Language Models (LLMs) - from training to putting them in production. In the second course, jam-packed with 50+ theoretical lessons & 10 practical projects, you will learn how to train, fine-tune, and deploy LLMs into AI products at your organization.

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Course Reviews

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 Ranjan

Who Is This Course For?

If you want to learn how to train and fine-tune LLMs from scratch, and have intermediate Python knowledge as well as access to moderate compute resources (for some cases, just a Google Colab will suffice!), you should be all set to take and complete the course. This course is designed with a wide audience in mind, including beginners in AI, current machine learning engineers, students, and professionals considering a career transition to AI. We aim to provide you with the necessary tools to apply and tailor Large Language Models across a wide range of industries to make AI more accessible and practical.

Enroll for free

Why Should You Take This Course?

Evolution and Fundamentals of LLMs

Dive into the evolution from simple text models to advanced systems like Transformers and GPT. Learn about various LLMs, their unique features, and the incredible abilities they unlock as they scale.
Operational Techniques for LLMs (LLMOps)

Gain hands-on experience in training LLMs, from deciding when to start from scratch or fine-tune to mastering operational essentials (LLMOps). Dive into cloud training, efficient scaling, and benchmarking, while also exploring the power of specialized models for industry-specific tasks.
Hands-on Projects with The Database for AI

Learn how to efficiently use compute to train and fine-tune models from scratch. Address biases and hallucinations in LLMs. Arm yourself with cutting-edge techniques to ensure LLMs are at their best behavior.
Free Cloud Credits

On a rolling basis, qualifying participants will be offered cloud credits with generous support from Cohere and Lambda. Terms apply.

Industry Leaders on the Course

“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 AI

More Course Takers' Reviews

Incredible Overview

Lee Pang

As 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!

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I'm Surprised

Brian Barnes

I 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...

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Interactive and full of real world applications. Incredible!!

Elle Neal

This 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!

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really good insights.

Ramesh Nandipalli

course is really good. Course is very detailed with very good examples.

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Great Course

raja nouman

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

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Complete course

Sharan Harsoor

Very nice course and amazing projects.

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Best fit for beginners to kickstart their AI journey

Tanmay Sarkar

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this is a good course

Kim Tỵ

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Excellent Course!

Rakesh Arumalla

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Awesome course!

Sanjay Singh

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!

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Very through approach to learn about LLMs & LangChain

Jorge Mario Salazar Rios

The course has a lot of valuable information and many great examples to understand in deep the concepts presented.

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Exceeds the expectations

Ravikumar Malipeddi

Great content and use cases are well crafted. enjoyed the whole learning.

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Train & Fine-Tune LLMs with Deep Lake

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Frequently Asked Questions

Is the course free?

The course is absolutely free to take. If you're planning to run some of the examples with cloud providers and didn't qualify for our limited credit grant, you will need up to $150 to run the examples. However, you can use your own laptop or free compute resources to run most of the examples - which we cover in a related sections. You can still complete the course and pass chapter quizzes without running these projects or paying anything.
Will I get a certificate upon completion?

Yes, you will get Gen AI 360 Certified upon completion.
How long does the course take to complete?

Our quickest learners have completed the course as quickly as in 25 hours, but the average course completion time is 40+ hours of learning.

Course Prerequisites

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 Notebooks
Basic Knowledge of GitHub
Free Activeloop account
Free Cohere account
Free Weights & Biases account
Google Cloud Compute Engine (GCE) account
Google Cloud Platform (GCP) account

Introduction to the Course and Course Logistics

Intro to LLMs

Understanding Transformers and GPT

Training Large Language Models from Scratch

Fine-Tuning Large Language Models

Improving LLMs with RLHF

Deploying Large Language Models

Advanced Topics and Future of LLMs

Course Highlights

Evolution and Fundamentals of LLMs

Operational Techniques for LLMs (LLMOps)

Hands-on Projects with The Database for AI

Free Cloud Credits