Free Live Courses: Full-Stack Machine Learning and Building Systems with LLMs

Following the popular hands-on courses and workshops that we taught last year at SciPy, ODSC, and Uplimit, today we are announcing two new live courses that you can join online for free!

The courses are taught by Hugo Bowne-Anderson whose courses on DataCamp and other platforms have been followed by over 4 million learners worldwide. The space is limited, so sign up to one or both of the courses below!

Course 1: Full-Stack Machine Learning with Metaflow

In this course, you’ll learn how to

  • ​Orchestrate machine learning workflows,
  • Use versioning, model reporting, and notebooks to inspect your workflows and models,
  • Leverage cloud compute resources to scale entire workflows and single steps,
  • Deploy workflows and models to production systems, and
  • Configure A/B tests to establish iterative AI development cycles.

Join this course if you know Python, have some background in ML and data science, and you want to learn how to build real-life, production-grade ML systems.

You will be able to hone your skills with a full stack of ML infrastructure using our sandbox environment, a browser-based VSCode environment powered by open-source Metaflow, so you don’t need to install anything locally. You can focus on building applications, not configuring infrastructure, as one of our previous students, Emily Ekdahl from Vouch Insurance observed:

“One standout feature of the class was the efficient use of Metaflow sandboxes to streamline the environment setup. This approach allowed participants to focus on learning rather than getting bogged down in complex configuration processes."

The best part is that you can deploy the same stack in your own environment after the course, following the footsteps of hundreds of other sophisticated ML organizations.

Course 2: LLMs, RAG, and Fine-Tuning: A Hands-On Guided Tour

If you are interested in learning about building systems powered by Generative AI and Large Language Models, join this course! This course is based on a well-received workshop we taught at Generative AI World last fall.

You will learn how to

  • ​Various proprietary off-the-shelf models and APIs,
  • Open-source LLMs,
  • Prompt engineering,
  • The Retrieval Augment Generation (RAG) pattern,
  • ​Vector databases, and
  • Building a constantly updating production RAG system with Metaflow.

We will give an overview of these techniques. If you know the basics already, this course will teach how to build actual systems powered by GenAI, going beyond the usual notebooks demos.

This course will leverage our sandbox environment similar to the first course, so you don’t need to install anything locally.

After our recent workshops, attended by 100s of working data scientists and MLEs, we're excited to be teaching them again in May and June:

You can also join the courses in May by clicking the images below!

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