## Foundations for ML & AI

This module slots before our Principles course. It is designed to bring you up to speed with mathematics, statistics, programming and infrastructural capabilities such as JupyterLab and Git/GitHub that will ensure that your further learning proceeds smoothly.

• High school level linear algebra upto matrix multiplication and vectors
• High school level calculus - caculus of one variable, derivatives, integrals
• Descriptive statistics: means, medians, etc
• Familiarity with atleast 1 programming language..basically you should have done some programming. This does not have to be Python.
• Basic statistics, including sampling, and the bernoulli, binomial, and Normal distributions
• Basic Data Science Infrastructure with Anaconda, conda, virtual environments, and pip; jupyterlab, and git+github
• Basic Python programming including classes and iteration
• numerical programming with numpy, pandas, matplotlib
• Basic linear algebra including matrix multiplication
• Basic calculus of multiple variables, including gradients
• Writing and testing a software library in python, organizing code in modules

By the time you finish this module, you will have learnt, using examples from deep learning and election prediction, how to :

a) Set up a working data science environment

b) How to write python libraries to do simple deep learning

c) Basic Numerical python programming, including the basic use of numpy, matplotlib and pandas and basic python data structures and input/Output iteration.

You will have also learned all the basic linear algebra, statistics, calculus of multiple variables, and optimization to prepare you to be an ace at machine learning and deep learning.

### Schedule

#### Students

##### Summer Cohort

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Conducted alongside elective

##### Winter Cohort

Intake 1:

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Conducted along with elective

Intake 2:

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Conducted along with elective

#### Working Professionals

##### Summer Cohort

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Conducted along with elective

##### Fall Cohort

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Conducted along with elective

##### Winter Cohort

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Conducted along with elective