Harvard University · edX
Fundamentals of TinyML
4.567 ratingsFocusing on the basics of machine learning and embedded systems, such as smartphones, this course will introduce you to the “language” of TinyML.
Overview
Become an expert in modern data engineering on Databricks' unified lakehouse platform. Master ETL pipelines, data transformations with Apache Spark, and Delta Lake for reliable data management.
What you'll learn
- Use Databricks for data engineering and ML workloads
- Create and design ML pipelines
- Use Llamafile and other local LLMs like Mixtral
Skills you'll practise
Advantages and disadvantages
Advantages
- University courses you can audit for free, with lectures, readings and practice quizzes.
- A verified certificate from the university if you pay for it.
- Self-paced: start any time.
Disadvantages
- Graded assignments and the certificate need the paid track.
- Audit access can expire a few weeks after the course ends.
- Learning is free, but the certificate costs money.
- Some parts (graded work, certificate) are paid.
Some points apply to every course of this kind; see how we rank.
Free to audit
- Free: Choose "Audit this course" when you enrol: lectures, readings and practice are free.
- Paid: Graded assignments and the verified certificate (Certificate $249). Audit access may end after the course closes.
Before you start
Beginner experience in programming languages. Git for version control. Using a text editor for development.
Taught by
- Noah GiftExecutive in Residence and Founder of Pragmatic AI Labs
- Alfredo DezaAdjunct Assistant Professor in the Pratt School of Engineering
Pragmatic AI Labs is in Tier 4: commercial training companies and platform-made courses of our institution ranking (58/100).
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