Python for Data Science

About Me

• Ph.D. in computer science
• 12 years working on data-related problems in different contexts (research, consulting, ...)
• Head of Data Science & Analytics at Intermarché & Netto
• Defining industrialization and coding practices (MLOps) for conducting data science projects
• Building solutions to a wide variety of business problems (churn, sales, stock, and in-store traffic prediction; sentiment analysis; basket analysis; ...)
• Managing a team of 10 Data Scientists/Analysts/Engineers
• ...
• Fell in love with Python after watching James Powell's “So you want to be a Python expert?” talk

Learning Objectives

Course Philosophy

• Code examples will often tease concepts that will be discussed later so don't worry if you don't understand something from the get-go
• Talking to a passive audience is not fun
• Interact with me
• Follow along the code examples and try to experiment with them
• No matter how stupid a question might seem, ask it anyway
• Don't be shocked if I don't have answers to all your questions (but I'll look them up)
• Your feedback is precious and crucial for improving the course

Evaluation

• Team project
• Exploratory data analysis of a tabular data set (data sets will be communicated at a later date)
• Conducted in pairs
• Expected deliverables
• Report (5–10 pages)
• Source code (preferably a github repo, zip otherwise)
• 10-min presentation of your main findings + 5-min for questions

Course Outline