Duration
3 weeksWeekly study
5 hours100% online
How it works
NLP in Practice: Deploying and Fine-Tuning LLMs with Open-Source Technologies
Stay at the forefront as a tech-savvy programmer with cutting-edge LLMOps skills
From Siri to Netflix, SMS to Google, the world wouldn’t be what it is today without Natural Language Processing (NLP) and Large Language Models (LLMs).
Be part of the AI revolution with this three-week course from PragmaticAI. Enhance your technical expertise in language models while gaining hands-on experience in deploying and fine-tuning advanced AI solutions.
You’ll work with cutting-edge open-source programs and platforms, equipping yourself with a unique skill set that will help you stand out in the competitive AI job market.
Harness cutting-edge tech tools
You’ll begin this course with an introduction to LLMs and how they work, exploring their benefits and risks, and understanding how foundation models serve as the backbone for a wide range of AI applications.
You’ll work with popular open-source NLP tools and projects, such as Llama and Whisper.cpp, and learn how to access other pre-trained models from repository platforms, like HuggingFace and Transformers.
Enhance production workflows and LLM performance
Next, you’ll explore best practices for deploying LLMs, focusing on serverless inference and efficient, Rust-based implementations that enable faster, scalable AI operations.
You’ll leverage tools like Skypilot, Lorax, and Ludwig, which streamline model fine-tuning and deployment in production environments.
Master RAG and navigate ethical challenges in Generative AI
You’ll also delve into Retrieval Augmented Generation (RAG), a powerful method for improving model performance, and learn to manage data for RAG applications and optimise LLM outputs.
With tools like Glaze, you’ll gain a deeper understanding of responsible AI deployment in real-world applications, as well as learn to navigate the ethical and regulatory challenges of Generative AI.
Syllabus
Week 1
Local LLMOps
About the Course
About the Course
Introduction to Large Language Models
Introduction to Large Language Models
Getting started with local models
Getting started with local models
Getting started with Rust Candle
Getting started with Rust Candle
Using Rust Candle
Using Rust Candle
Graded Quiz
Graded Quiz
Week 2
Production workflows and performance of LLMs
Evaluating Real-World Performance of LLMs
Evaluating Real-World Performance of LLMs
Exploring Production LLM Workflows
Exploring Production LLM Workflows
Retrieval Augmented Generation with local LLMs
Retrieval Augmented Generation with local LLMs
Graded Quiz
Graded Quiz
Week 3
Responsible Generative AI
Foundations of responsible Generative AI
Foundations of responsible Generative AI
Graded Quiz
Graded Quiz
When would you like to start?
Start straight away and join a global classroom of learners. If the course hasn’t started yet you’ll see the future date listed below.
Available now
Learning on this course
On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.
What will you achieve?
By the end of the course, you‘ll be able to...
- Apply best-practices to AI Engineering
- Assess fundamental concepts of AI development.
- Compare and contrast different LLM frameworks
- Debate ethical AI concepts and theory.
Who is the course for?
This course is for anyone looking to gain hands-on practice with language models and their deployment. If work in software engineering, data science, or machine learning, this course allows you to explore cutting-edge AI technologies and equips you with career-advancing skills to work with and operationalise LLMs.
It’s open to all, but having some experience with programming, machine learning, or natural language processing will help you get the most out of the course.
Who will you learn with?
Founder of Pragmatic AI Labs & Executive in Residence at Duke MIDS and Duke AIPI. Former Bay Area CTO and author of multiple O'Reilly books.
Former Olympic high jumper with 15 years of Software Engineering. He teaches ML, Rust, and Python at Duke University and is an expert in MLOps, Azure, and automation
Who developed the course?
Ways to learn | Subscribe & save | Buy this course | Limited access |
---|---|---|---|
Choose the best way to learn for you! | $349.99 for one year Automatically renews | $54/one-off payment | Free |
Develop skills to further your career | Fulfill your current learning need | Sample the course materials | |
Access to this course | tick | tick | Access expires 22 Dec 2024 |
Access to 1,000+ courses | tick | cross | cross |
Learn at your own pace | tick | tick | cross |
Discuss your learning in comments | tick | tick | tick |
Certificate when you're eligible | Digital only | Printed and digital | cross |
Cancel for free anytime |
Ways to learn
Choose the best way to learn for you!
Buy this course
$54/one-off payment
Fulfill your current learning need
- Access to this course
- Learn at your own pace
- Discuss your learning in comments
- Printed and digital certificate when you’re eligible
Subscribe & save
$349.99 for one year
Automatically renews
Develop skills to further your career
- Access to this course
- Access to 1,000+ courses
- Learn at your own pace
- Discuss your learning in comments
- Digital certificate when you're eligible
Cancel for free anytime
Limited access
Free
Sample the course materials
- Access expires 22 Dec 2024
Find out more about certificates, Unlimited or buying a course (Upgrades) |
Find out more about certificates, Unlimited or buying a course (Upgrades)
Learning on FutureLearn
Your learning, your rules
- Courses are split into weeks, activities, and steps to help you keep track of your learning
- Learn through a mix of bite-sized videos, long- and short-form articles, audio, and practical activities
- Stay motivated by using the Progress page to keep track of your step completion and assessment scores
Join a global classroom
- Experience the power of social learning, and get inspired by an international network of learners
- Share ideas with your peers and course educators on every step of the course
- Join the conversation by reading, @ing, liking, bookmarking, and replying to comments from others
Map your progress
- As you work through the course, use notifications and the Progress page to guide your learning
- Whenever you’re ready, mark each step as complete, you’re in control
- Complete 90% of course steps and all of the assessments to earn your certificate
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