vuillaut/datascience_intro

Introductive Course to Data Science

Introductive Course to Data Science

Thomas Vuillaume

contact me at firstname.name[at]lapp.in2p3.fr

slides: https://mycore.core-cloud.net/index.php/s/LEUF1mdl2rkfCEx

Running online

• Google colab
• mybinder

Courses content:

Slides

https://lapp-owncloud.in2p3.fr/s/4YKq4Ko4C6gj5w6

Course 0: Python and environment setup

These are reminders of prerequisite for this course

Python basics:

• https://jckantor.github.io/CBE30338/01.02-Python-Basics.html
• https://www.kaggle.com/learn/python

Env. setup:

• conda

Git:

• https://education.github.com/git-cheat-sheet-education.pdf

Course 1

• Introduction and environment setup
• Introduction to Numpy

Course 2

• Exercices with Numpy
• Introduction to pandas
• Exercices with pandas

Course 3

• Exercices with pandas
• Introduction to matplotlib and visualisation
• Exercices with matplotlib
• Visualisation with pandas

Course 4

• Introduction to machine learning
• Exercices with scikit-learn

Course 5

• Machine learning #2
• Exercices
• Practical work on a real case

Course 6

• Practical work on a real case
• Getting scores for the real case
• Introduction to git pull requests
• Introduction to kaggle
• Wrap-up, going further in data science

Course 7

• Big tools for Big data

Homework

• TP on exoplanets

Resources

• A visual introduction to machine learning
• Machine Learning (Lecture 1) --- Michael Kagan (SLAC)
• Machine Learning (Lecture 2) --- Michael Kagan (SLAC)
• Deep Learning and Vision --- Jonathon Shlens (Google Research)
• Fidle - Deep Learning training course