Data science and Machine Learning for Engineering Applications
Courses

Data science and Machine Learning for Engineering Applications

General Information

SSD: ING-INF/05

CFU: 6

Professor: Daniele Quercia – daniele.quercia@polito.it

Teaching Assistants: Matteo Berta, Giordano Paoletti: [name].[surname]@polito.it

Class Schedule: Monday 1:00 pm – 2:30 pm (classroom 8D) – Friday 8:30 am – 11:30 am (classroom 8I)

Teaching Material

This section contains the slides of the Data Science and Machine Learning for Engineering Applications course.

  1. Course introduction: pdf

Laboratory Material

This section contains the slides and the lecture notes of the laboratory lectures

  1. Python Basics: slides lecture_notes
  2. Numpy: slides lecture_notes

Laboratory Exercises

This section contains the texts and the solutions to the laboratory exercises

  1. Python installation guide: pdf
  2. Python Basics (Lab 1):
    • Text: zip folder with the Jupyter notebook containing the text exercises of lab 1 (zip)
    • Solutions: Zip folder with the Jupyter notebook (solutions_zip), and PDF (solutions_pdf) containing the solutions to lab 1

Final Projects

Suggested Books

E. Matthes. Python Crash Course, 2nd Edition: A Hands-On, Project-Based Introduction to Programming. No Starch Press, 2019. isbn: 9781593279288

Jake VanderPlas. 2016. Python Data Science Handbook: Essential Tools for Working with Data (1st. ed.). O’Reilly Media, Inc.

McKinney Wes. 2017. Python for data analysis (2nd. ed.). O’Reilly Media, Inc.