4 Weeks
·Cohort-based Course
All-time best selling AI technical course on Maven! Train, validate and deploy your first fine-tuned LLM
Previously at
Last chance to enroll
1
day
14
hours
32
mins
Course overview
Most software engineers and data scientists talk about LLMs, but few have the hands-on knowledge to train, validate and deploy fine-tuned LLMs for specific problems.
This course takes your skills (and career) to the next level as you run an end-to-end LLM fine-tuning project with the latest tools and best practices.
More than seven workshops guide you through the successive steps as you run your own end-to-end fine-tuning project. Additionally, we provide office hours and bonus lessons from world class experts (see guest instructors).
Workshop 1: Determine when (and when not) to fine-tune an LLM
Workshop 2: Train your first fine-tuned LLM with Axolotl
Workshop 3: Set up instrumentation and evaluation to incrementally improve your model
Workshop 4: Deploy Your Model
Workshop 5: Build Applications For LLMs in Python
Workshop 6: Prompt Engineering (Optional)
Workshop 7: Best Practices For Fine Tuning Mistral (Optional)
This is accompanied by 5+ hours of office hours.
Lectures explain the why and demonstrate the how for all the key pieces in LLM fine-tuning. Your hands-on-experience in the course project will ensure your ready to apply your new skills in real business scenarios.
With world-class guest instructors:
- Jeremy Howard: Co-Founder Answer.AI & Fast.AI
- Sophia Yang: Head of Developer Relations, Mistral AI
- Wing Lian: Creator of Axolotl library for LLM fine-tuning
- Logan Kilpatrick: Product Lead for Google AI/Gemini
- Shreya Shankar: LLMOps and LLM Evaluations researcher
- Zach Mueller: Lead maintainer of HuggingFace accelerate
- Bryan Bischof: Director of AI Engineering at Hex
- Johno Whitaker: R&D at AnswerAI
- Charles Frye: AI Engineer at Modal Labs
- Eugene Yan: Senior Applied Scientist @ Amazon
- Harrison Chase: CEO of LangChain
- Travis Addair: Co-Founder & CTO of Predibase
- John Berryman: Author of O'Reilly Book Prompt Engineering for LLMs
- Joe Hoover: Lead ML Engineer at Replicate
All students in the first cohort (May 14 - Jun 4) get the following freebies thanks to our sponsors:
1. $501.43 in API credits from OpenAI
2. $501.42 in compute credit from HuggingFace
3. $501 in compute credit from Replicate
4. $500 in compute credit from Modal Labs
5. $200 in compute credit from Jarvis Labs
6. $250 in credits from LangSmith.
This is a total value of $2,450 in just compute & software!
All course materials + recordings will be available to students who enroll.
Note: This is a cohort course, but you should still enroll in the current cohort b/c everything is recorded. Also, the free compute and incentives apply to only the current cohort!
01
Data scientists looking to repurpose skills from conventional ML into LLMs and generative AI
02
Software engineers with Python experience looking to add the newest and most important tools in tech
03
Programmers who have called LLM APIs that now want to take their skills to the next level by building and deploying fine-tuned LLMs
Understand the costs and benefits of fine-tuning a model and how they vary from one problem to the next.
We'll discuss your judgments with applications to specific use cases.
Axolotl builds in best-practices for faster and more reliable fine-tuning.
Gain experience using Axolotl with guidance from an Axolotl contributor.
Learn the methods for evaluating ML models. Work through where each method is applicable, and plan how to build data collection into real-world processes.
Compare the key criteria for successful model deployment and determine which platforms will meet your needs. Then deploy your own fine-tuned LLM from the course project.
12 interactive live sessions
Lifetime access to course materials
13 in-depth lessons
Direct access to instructor
Projects to apply learnings
Guided feedback & reflection
Private community of peers
Course certificate upon completion
Maven Satisfaction Guarantee
This course is backed by Maven’s guarantee. You can receive a full refund within 14 days after the course ends, provided you meet the completion criteria in our refund policy.
LLM Fine-Tuning for Data Scientists and Software Engineers
Week 1
May 14—May 19
Events
Tue, May 14, 5:00 PM - 7:00 PM UTC
Modules
Week 2
May 20—May 26
Events
Tue, May 21, 5:00 PM - 7:00 PM UTC
Fri, May 24, 5:00 PM - 6:00 PM UTC
Fri, May 24, 6:30 PM - 7:30 PM UTC
Modules
Week 3
May 27—Jun 2
Events
Tue, May 28, 5:00 PM - 7:00 PM UTC
Wed, May 29, 5:00 PM - 6:00 PM UTC
Thu, May 30, 5:30 PM - 6:30 PM UTC
Thu, May 30, 8:00 PM - 8:45 PM UTC
Fri, May 31, 4:00 PM - 5:00 PM UTC
Modules
Week 4
Jun 3—Jun 4
Events
Tue, Jun 4, 5:00 PM - 7:00 PM UTC
Modules
Post-Course
Events
Wed, Jun 5, 4:30 PM - 5:00 PM UTC
Thu, Jun 6, 10:00 PM - 11:00 PM UTC
Chief Generative AI Architect @ Straive
Dan has worked in AI since 2011, when he finished 2nd (out of 1350+ teams) in a Kaggle competition with a $500k prize. He contributed code to TensorFlow as a data scientist at Google and he has taught online deep learning courses to over 250k people. Dan has advised AI projects for 6 companies in the Fortune 100.
Founder @ Parlance Labs
Hamel is an ML engineer who loves building machine learning infrastructure and tools 👷🏼♂️. He leads or contribute to many popular open-source machine learning projects. His extensive experience (20+ years) as a machine learning engineer spans various industries, including large tech companies like Airbnb and GitHub.
Hamel is an independent consultant helping companies operationalize LLMs. At GitHub, Hamel lead CodeSearchNet, a large language model for semantic search that was a precursor to CoPilot, a large language model used by millions of developers.
Cohort 1
$500 USD
Dates
Payment Deadline
Don't miss out! Enrollment closes in 2 days
1:00pm - 3:00pm EST
Interactive weekly workshops where you will learn the tools you will apply in your course project.
2 hours per week
You will build and deploy an LLM as part of the course project. The course project is divided into four weekly project.
By the end, you will not only know about fine-tuning, but you will have hands-on experience doing it.
Cohort 1
$500 USD
Dates
Payment Deadline
Don't miss out! Enrollment closes in 2 days