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A Hands-On Introduction to Fine-Tuning LLM

Fine-tuning Large Language Models (LLMs) can be daunting, especially for newcomers.

Are you struggling with the complexities and lack of practical guidance in fine-tuning LLMs? Enroll in our comprehensive course to gain hands-on experience and master the art of fine-tuning LLMs for various tasks and enterprise applications.

Intermediate

 | 1 Course | 

6 Hours

Earn a verified certificate from University of New Mexico Continuing Education.
University of New Mexico | LLM Bootcamp | Data Science Dojo

Why Fine-Tuning LLM

Decode the Fine-Tuning Puzzle:
  • Unravel the “why” behind fine-tuning: rationale & limitations.
  • Optimize resource usage with parameter efficient methods.
  • Explore advanced techniques like LoRA & QLoRA quantization.
Hands-On with Real-World Models:
  • Fine-tune & deploy LLaMA2-7B & OpenAI GPT in class exercises.
  • Gain practical experience with applications & evaluation methods.
  • Apply your skills to solve diverse NLP challenges.
Master Advanced Techniques:
  • Understand fine-tuning vs. RAG: when to choose each approach.
  • Push boundaries with cutting-edge parameter efficient methods.
  • Stay ahead with the latest advancements in fine-tuning technology.
Become a Fine-Tuning Pro:
  • Stand out with in-demand LLM expertise in the job market.
  • Boost your NLP skillset to handle complex tasks.
  • Future-proof your career by contributing to fine-tuning’s evolution.
Join the LLM Community:
  • Connect with experts & peers, learn from shared experiences.
  • Collaborate on projects in a supportive learning environment.
  • Stay informed with exclusive resources & updates.

Curriculum

Introduction to Fine-Tuning Large Language Models

In-depth discussion on fine-tuning of large language models through theory discussions, exploring rationale, limitations, and Parameter Efficient Fine Tuning.

  • Fine Tuning Foundation LLMs
    • RLHF, Transfer learning and Fine tuning
    • Limitations for fine tuning
    • Parameter efficient fine tuning
    • Quantization of LLMs
    • Low Rank Adaptation (LoRA) and QLoRA
    • Fine tuning vs. RAG: When to use one or the other. Risks and limitations.
  • Hands-on Exercise:
    • In-Class: Instruction fine-tuning, deploying and evaluating a LLaMA2-7B 4-bit quantized model
    • In-Class: Fine-tuning and deploying OpenAI GPT

Testimonials

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Alessya Visnjic | WhyLabs | Data Science Dojo
Partnering with Data Science Dojo aligns with our mission to make data science accessible. Their bootcamps contribute to safe AI deployment education.
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Jeff Fong | Hover | Data Science Dojo
LLM bootcamp provides exceptional, hands-on initiation into LLMs and practical applications. A deep dive into the subject with theoretical knowledge.
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Six months of course material access post-training is valuable. Instructors ensure success, making it a top-notch learning experience in AI.
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Fatemeh Shah Mohammadi | Health University of Utah | Data Science Dojo
Instructors simplified complex topics effectively. Hands-on learning enhanced my LLM understanding in 5 days. Intensive but immeasurable rewards.
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A rewarding opportunity to help students of all backgrounds learn new techniques. Being part of a passionate data science community was a real privilege.
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Fahad Alswaina | KAPSARC | Data Science Dojo
The effort in providing resources was commendable. Teachers and assistants were helpful, making it one of the best courses. I learned a lot for future use.
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Top-notch speakers, hands-on workshops, and networking make it a wonderful tech experience. Raja's in-depth teaching focuses on learning concepts.
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Comprehensive curriculum in generative AI, prompt engineering, and data retrieval. Excited about practical training opportunities.
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Instructor Harrison Chase from LangChain, guiding participants through the LLM Bootcamp.
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This boot camp provided great content, equipping me with skills and confidence for efficient job execution. Enjoyable class and projects, a rewarding decision.
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Frequently Asked Questions

Will I get a certificate upon completion?

Yes, you will get a certified upon completion.

How many Continuing Education Credits (CEUs) will I receive?

Yes, you will receive 0.6 CEU’s after completing the course. You will be able to request a transcript from the University of New Mexico by paying a fee of ten US Dollars.

How long does the course take to complete?

Our quickest learners have completed the course as quickly as in 6 hours.

What software and subscriptions are included in the registration fee?

An assortment of software subscriptions worth $500, enhancing the value of the program.

A repository of practice materials.

A 12-month unlimited access to all learning resources, allowing for continuous learning and review.

Are there prerequisites for enrollment?

No specific prerequisites are required. The course is tailored to accommodate participants with varying levels of programming knowledge, providing a comprehensive learning path.

Can I get support and guidance after the course?

Yes, Data Science Dojo provides ongoing support and guidance to the course participants even after the program ends. This includes access to a community of fellow participants and instructors who can help answer questions and provide further assistance.

If I have questions during the live instructor-led sessions or while working on homework?

Yes, our live instructor-led sessions are interactive. During these sessions, students are encouraged to ask questions, and our instructors respond without rushing. Additionally, discussions within the scope of the topic being taught are actively encouraged. We understand that questions may arise during homework, and to assist with that, we have a discord channel to help unblock students between sessions. Rest assured, you won't have to figure everything out by yourself – we are committed to providing the support you need for a successful learning experience.

Are the live sessions recorded for viewing later?

Yes, each live session is recorded and made available to students for review a few days after it has taken place.

How do I access the learning portal?

Once you are registered for the program, you will receive a few emails from us. One of those emails will contain steps to create your learning portal account and access the program content.

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