Python for Data Science

A Crash Course



General Info



Khalil El Mahrsi
2022
Creative Commons License

About Me

  • Ph.D. in computer science
  • 12 years working on data-related problems in different contexts (research, consulting, ...)
  • Currently: Head of Data Science at Intermarché
    • Defining industrialization and coding practices 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; ...)
    • Mentoring Data Scientists
    • ...
  • Fell in love with Python after watching James Powell's “So you want to be a Python expert?” talk

Learning Objectives

By the end of this course, you will be able to
  • Write and understand entry-level to intermediate-level code in the Python programming language
  • Use NumPy for scientific computing and efficient manipulation of multi-dimensional arrays and matrices
  • Use pandas to load, manipulate, and analyze tabular data
  • Use Matplotlib and seaborn to visualize data

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

Introduction to Python Programming
Scientific Computing With NumPy
Processing Tabular Data With pandas
Visualizing Data With Matplotlib and seaborn
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