4.4
(176 ratings)
3 Weeks
·Cohort-based Course
An online course for everything LLMs.
4.4
(176 ratings)
3 Weeks
·Cohort-based Course
An online course for everything LLMs.
Course overview
This started as an LLM fine-tuning course. It organically grew into a learning event with world-class speakers on a broad range of LLM topics. The original fine-tuning course is still here as a series of workshops. But there are now many self-contained talks and office hours from experts on many Generative AI topics.
All materials + recordings will be available to participants who enroll. There are 11 talks and 4 workshops (and growing) in addition to office hours.
Conference Talks
------------------------------
Jeremy Howard: Co-Founder Answer.AI & Fast.AI
- Build Applications For LLMs in Python
Sophia Yang: Head of Developer Relations, Mistral AI
- Best Practices For Fine Tuning Mistral
Simon Willison: Creator of Datasette, co-creator of Django, PSF Board Member
- Language models on the command-line
JJ Allaire: CEO, Posit (formerly RStudio) & Researcher for the UK AI Safety Institute
- Inspect, An OSS framework for LLM evals
Wing Lian: Creator of Axolotl library for LLM fine-tuning
- Fine-Tuning w/Axolotl
Mark Saroufim and Jane Xu: PyTorch developers @ Meta
- Slaying OOMs with PyTorch FSDP and torchao
Jason Liu: Creator of Instructor
- Systematically improving RAG applications
Paige Bailey: DevRel Lead, GenAI, Google
- When to Fine-Tune?
Emmanuel Ameisen: Research Engineer, Anthropic
- Why Fine-Tuning is Dead
Hailey Schoelkopf: research scientist, Eleuther AI, maintainer, LM Evaluation Harness
- A Deep Dive on LLM Evaluation
Johno Whitaker: R&D at AnswerAI
- Fine-Tuning Napkin Math
John Berryman: Author of O'Reilly Book Prompt Engineering for LLMs
- Prompt Eng Best Practices
Ben Clavié: R&D at AnswerAI
- Beyond the Basics of RAG
Abhishek Thakur leads AutoTrain at HuggingFace
- Train (almost) any llm model using 🤗 Autotrain
Kyle Corbitt is currently building OpenPipe
- From prompt to model: fine-tuning when you've already deployed LLMs in prod
Ankur Goyal: CEO and Founder at Braintrust
- LLM Eval For Text2SQL
Freddy Boulton: Software Engineer at 🤗
- Let's Go, Gradio!
Jo Bergum: Distinguished Engineer at Vespa
- Back to basics for RAG
Fine-Tuning Course
---------------------------
Run an end-to-end LLM fine-tuning project with modern tools and best practices. Four workshops guide you through productionizing LLMs, including evals, fine-tuning and serving.
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
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.
The Fine-Tuning course has these guest speakers:
- Shreya Shankar: LLMOps and LLM Evaluations researcher
- Zach Mueller: Lead maintainer of HuggingFace accelerate
- Bryan Bischof: Director of AI Engineering at Hex
- 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
- Joe Hoover: Lead ML Engineer at Replicate
FAQ:
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Q: It says this course already started. Should I still Enroll?
A: Yes. Everything is recorded, so you can watch videos for any events that have happened so far, join for live events moving forward, and even learn from talks long after the conference is over.
Q: Will there be a future cohort?
A: No. We were fortunate to have so many world-class speakers. We don't think this can be replicated, so it is now a one-time-only event with all recordings available.
Q: Are you still giving out free compute credits?
A: No. Students who enrolled after 5/29/2024 are not eligible for compute credits. You will still get access to the lectures and recordings. EXCEPTION: if you enroll in the course by 6/10/2024 and use Modal by 6/11/2024, they will give you $1,000 in compute credits.
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
Connect With A Large Community Of AI Practitioners
Discord with 1000+ members attending the conference.
Learn more about LLMs
Topics such as RAG, Evals, Inference, Fine-Tuning, are covered.
Learn about the best tools
We have curated the tools that we like the most. Credits for many of these tools are provided.
Learn about fine-tuning in-depth
This conference used to be a fine-tuning LLMs course. That course is still here, and takes place over the course of 4 workshops.
4 interactive live sessions
Lifetime access to course materials
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.
Mastering LLMs For Developers & Data Scientists
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4.4
(176 ratings)
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.
Be the first to know about upcoming cohorts
4-6 hours per week
Tuesdays
1:00pm - 3:00pm EST
Interactive weekly workshops where you will learn the tools you will apply in your course project.
Weekly projects
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.
Be the first to know about upcoming cohorts