Dr. Franziska Horn

Data, with Love

ML for Data Scientists Workshop

This course is aimed at practitioners, who want to analyze data with machine learning algorithms.

The four-week workshop follows a "flipped classroom" format, where the participants study the theory and solve the exercises at their own speed and the results are then discussed in the group sessions.

Learning Outcomes



The course consists of six group sessions, where we discuss questions and results, and a self-study part before each group session, where you read through the chapters of the book, take notes in the workbook, test yourself with short quizzes, and work through the programming exercises. Your answers to the questions in the workbook are the basis for the group discussions.

ml workshop schedule

Important: While this course is meant to be taken in parallel to your normal job, you should block at least six hours in your calendar for each self-study part to make sure you have enough time to work through all of the materials and come prepared to the group discussions. Please complete the Preparation part before the first group session!

The group sessions take place remotely via Microsoft Teams, Google Meet, Zoom, Slack, or similar. Please join the calls with your camera turned on so the sessions feel a bit more personal.

How to get the most out of this course

Think of the questions in the workbook as questions an interested colleague might ask you after the course. Following the Feynman Technique, try to explain what you've learned in your own words, which is the easiest way to identify any gaps in your knowledge.
Don't try to memorize any facts, but instead connect them with what you already know and make sure you understand the "why" behind the answers.
And if anything seems confusing, please make a note of it and ask in the next meeting!

Preparation before the course (~20min)

1st Group Session (~1h):

Self-Study Part 1: What is ML?

Block 1.1:
Block 1.2:
Block 1.3:

2nd Group Session (~3h):

Self-Study Part 2: Your first algorithms

Block 2.1:
Block 2.2:

3rd Group Session (~3h):

Self-Study Part 3: Avoiding common pitfalls

Block 3.1:
Block 3.2:
Block 3.3:

4th Group Session (~3h):

Self-Study Part 4: Advanced topics

Block 4.1:
Block 4.2:
Block 4.3:

5th Group Session (~3h):

Self-Study Part 5: Conclusion

Block 5.1:

6th Group Session (~3h):