Mastering Fine Tuning Large Language Models
- Learn to build efficient task and domain-specific large language models using fine tuning:
- Live instructor-led learning
- Comprehensive and hands-on exercises on fine tuning large language models
- Parameter Efficient Fine Tuning (PEFT), Quantization, Low Rank Adapatation (LoRA), RLHF
- Pros and cons of RAG vs. fine tuning
- GPU cloud, coding sandboxes and subscriptions for fine tuning exercises included
- Teaching assistants, cohort-discussion forum and alumni network
- Verified certificate from University of New Mexico Continuing Education
Who is this course for?
Fine tuning is often needed when a large model has to be adapted for a specific task, domain or style.
This course is designed for anyone interested in fine tuning large language models while understanding the challenges, risks, cost, accuracy and latency tradeoffs in building LLM applications.
Product Leaders
Curriculum
The most comprehensive course on LangChain in industry taught by practitioners who build RAG-based LLM products. Theory and coding exercises
Fundamentals
Understand when and why fine tuning is needed. Understand completion and instruct models. Discuss transfer learning, supervised and unsupervised fine tuning.
RAG vs. Fine Tuning
Discuss in detail the risks and tradeoffs between using fine tuning and retrieval augmented generation and why an enterprise would need one or the other.
Optimization
Learn about techniques like PEFT, quantization, LoRA (Low Rank Adaptation). Improving models using RLHF.
Fine tuning Llama2 7B
Learn to quantize a Llama2 7B parameter 4-bit quantized model on an instruction fine tuning dataset. Evaluate and benchmark against the original model as baseline.
Domain-specific models
Proposed – Symbl.AI
Risks and Challenges
Understand the inherent risks in fine tuning and how to guard against them.
More than just a course
The course registration comes with access to our learning platform with hundreds of free tutorials, coding exercises, sandboxes, and other bonus learning material.
Watch tutorials or practice coding in browser-based Jupyter notebooks and inline code runners. We call our learning platform a complete learning ecosystem.
All learners get access to a GPU cloud and APIs for fine tuning large language models.
All software licenses, subscriptions, tools, and computing resources are included. For Guru package, LLM API keys are also included.
Every attendee gets a dedicated compute and storage pre-configured with relevant libraries and packages.
Get help from course staff, share ideas and discuss with your peers.
Dozens of other short courses and coding exercises are included in the registration.
Join the exclusive community of 11,000+ alumni globally. Dicuss, collaborate, and expand your network.
In collaboration with
We have partnered with some of the foremost names in industry to bring this course to you.
Customers reviews
Dojo
-
Live Instuctor-led training
-
Direct access to instructor
-
Hands-on fine tuning exercises
-
GPU cloud and coding sandboxes
-
Access to private community of learners
-
Restricted access to learning platform
Guru
-
Everything in Dojo plus
-
Verified certificate with 1 CEU
-
100+ hands-on coding exercises
-
Bonus learning material
-
Recording of live sessions
-
Online coding sandboxes
Earn a verified Certificate
Earn a verified certificate from The University of New Mexico Continuing Education:
- 1 Continuing Education Credit (CEU)
- Acceptable by employers for reimbursements
- Valid for professional licensing renewal
- Verifiable by The University of New Mexico Registrar’s office
- Add to LinkedIn and share with your network
Frequently Asked Questions
Are there any pre-requisites for this course?
Yes. You should be comfortable with Python programming. Basic understanding of large language models is strongly recommended.
What happens if I can’t make it to the live session?
No worries. All sessions are recorded and made available for you to view in the learning platform.
I work full-time, what is the time commitment?
The live session is 8 hours. You can learn at your own pace afterward.
How long will I have access to the course?
All Guru package registrations receive a 12-month access to the learning platform.
Do I need to install any software or get any subscriptions?
Any software licenses, tools, and computing resources are included in the registration fee. Guru package includes API keys for LLM usage.
Will I get a certificate?
Yes. Additionally, Guru package includes a verified certificate with 1 Continuing Education Credit. A transcript can be requested from the University of New Mexico registrar’s office.
What is the course duration?
The live instructor-led sessions are 8 hours long. There is a lot more learning material available before and after the live session.
Are the sessions interactive?
Yes. We encourage learners to bring a lot of questions. We also have dedicated class forum and teaching assistants who can answer questions outside of the live sessions.
Instructors will ensure that all questions are addressed promptly
What is the refund policy?
You can request a full refund at least three business days before the start date of the training.