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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