Micro-courses

Since early 2019, I’ve been offering “micro-courses,” 90-minute courses on specific topics in Python and data science. Many (but not all) of these are based on my longer corporate training classes. These courses are perfect for companies with busy schedules who want to level up their employees’ knowledge without interfering too much with work.

Micro-courses are 100% online, and while they’re shorter than usual classes, they are done in my typical style: Live-coding into Jupyter, several exercises, and time for Q&A.

I’ve given these micro-courses to companies in North America, Europe, and Israel. The short time means that they’re generally easier to schedule than my full-day classes, given that my training calendar is typically booked 6-8 months in advance.

If you have an idea for a micro-course that doesn’t appear in this list, then please reach out to me and let me know! I’d be happy to discuss it with you. I’m also constantly adding new micro-courses, so be sure to check here on a regular basis to see what new topics I’m offering!

Beginner level

  • Python Function Parameters
  • Inheritance
  • Introduction to Python Modules
  • Object-Oriented Python Basics (3-hour micro-course)
  • Pandas Plotting
  • Strings, from A to Emojis

Intermediate level

  • Classification of Text using Sci-Kit learn
  • Command-line Arguments with “argparse”
  • Compiling Functions into Byte-Codes
  • Comprehensions
  • Configuring and Working with Virtual Environments
  • Data Analytics with NumPy and Pandas
  • Data Science and Machine Learning in Python
  • Generator Functions and Comprehensions
  • Introduction to Type Hints and “mypy”
  • Magic Methods
  • Making Your Classes Iterable
  • Functional Programming Techniques
  • Writing and Distributing Python Packages
  • pathlib: An Object-Oriented API for Files and Directories
  • Times and Dates in Pandas

Advanced level

  • Introduction to Decorators
  • Advanced Decorators
  • Introduction to Decorators
  • asyncio: The Newest Form of Python Concurrency
  • Advanced Pandas grouping
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