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How do I get ready for the AI master program?

Caio Corro, one of our professors, compiled a nice page of advice for ML students in general: http://caio-corro.fr/advice/ .

If you want to prepare yourself over the summer, there are several classes that we recommend, which can help you:

- At M1 entry level, prepare for striving in the program

- At M2 entry level, replace missing prerequisites:

We HIGHLY RECOMMEND at least reading the THREE CRASH COURSES highlighted in red.

Advanced students will be interested in the Machine Learning Summer School

Replace, review, or prepare for:

  • PRE1: Applied statistics

[CRASH COURSE] Crash Course on Basic Statistics, Marina Wahl (28 pages + questions)

[ON-LINE BOOK w. exercises] Computational and Inferential Thinking, By Ani Adhikari and John DeNero

[BOOK] Think stats, AB Downey.

[BOOK] Statistics in a Nutshell. Sarah Boslaugh and Paul Andrew Watters

[BOOK] All of statistics: a concise course in statistical inference. Larry Wasserman

[CHEATSHEET] Harvard cheatsheet in statistics

  • PRE2: Mathematics for Data Science

A) LINEAR ALGEBRA

[CRASH COURSE] Linear Algebra Review and Reference. Zico Kolter and Chuong Do (26 pages)

[SHORT COURSES] Linear Algebra, Khan Academy

[COURSE] Mathematics for Machine Learning: Linear Algebra, David Dye, Coursera (19 hours)

B) CALCULUS

[CRASH COURSE] The matrix calculus you need for deep learning, T Parr, J Howard (33 pages)

[COURSE] Mathematics for Machine Learning: Multivariate Calculus,

Samuel J. Cooper, Coursera (19 hours)

[BOOK] Matrix Computations. Gene Golub and Charles van Loan

    • PRE3: Datacomp1

[COURSE] Databases and SQL for Data Science. Rav Ahuja

      • PRE4: Scientific programming

[COURSE] Data Analysis with Python. Joseph Santarcangelo

  • TC0 and TC1: Machine Learning

[TUTORIAL] An introduction to machine learning with scikit-learn

[TOTAL BEGINNER COURSE] Introduction to machine learning, Sebastian Thrun, Katie Malone, Udacity (10 lessons)

[BEGINNER COURSE] Machine Learning, Andrew Ng, Coursera (54 hours)

[BOOK] The Hundred-Page Machine Learning Book. Andriy Burkov.

[BOOK] Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow. Aurélien Géron.

[ADVANCED COURSE] How to win a data science competition. Dmitry Ulianov, Coursera, (4 weeks); Excellent summer program!

  • TC2: Optimization

[COURSE] Introduction to optimization, by the instructors of TC2: Anne Auger and Dimo Brockhoff

  • OPT7: Advanced optimization

[COURSE] Advanced optimization, by former instructors of OPT7: Anne Auger and Dimo Brockhoff

  • OPT13: Information Theory

[COURSE] Information Theory, Inference, and Algorithms, David MacKay