Join our counselling session
Book now

Python for Data Science

You will start with the basics of python programming, including python data structures, functions and classes. We follow this up by an introduction to Numerical Python (NumPy) and finally, the course will provide a basic introduction to linear regression from scratch.

Along the way, we will introduce foundational ideas of statistics, linear algebra and calculus.

At the end of this module, you will have the tools and the concepts needed to successfully undertake a rigorous course in machine learning.

Program image
Applications opening soon
Registration Closed

Starts

August 15, 2021
To be decided
Self-paced

Duration

5 weeks (classes only on weekends)

Time Investment

3-5 hours a week
Online

Format

Live Online
Online

Fee

Introductory Price: $100
List Price: $250

₹7,500

Registration closes

August 14, 2021
To be decided

Course Outcome

Program Overview

Program Overview

At the end of this sprint, you will have the tools and the concepts needed to successfully undertake a rigorous course in machine learning.

Who should apply

Prerequisites

Prior knowledge of programming is not necessary for this sprint

Class Timings

Course Structure

Live online classes
1. Live Online Classes

Bi-weekly live, cohort-based lessons with labs and quizzes

Mentorship
2. Mentor-Supported

Ten or more hours/week to interact with an experienced & accomplished mentor

Module end Project
3. End-of-Module Project

Complex problems that challenge you to apply what you learn

Capstone
4. Capstone

10–12 week long Capstone Project with one of our partner companies or faculty

Program Faculty

Dr Pavlos Protopapas

Founding faculty Univ.AI

Pavlos is the Scientific Program Director, Institute for Applied Computational Science (IACS) at Harvard University, and leads the data science masters program at Harvard.

View Profile

Topics Covered

PyDS

  • Introduction to Python
  • Data Types, iterators, python operations,
  • order of operations, logical operators
  • Python Data Structures - Lists, Dictionaries, Tuples
  • List/dictionary comprehensions
  • Enumeration
  • Python Functions - Arguments, keyword arguments, etc.
  • Anonymous functions (lambda function)
  • Classes: Constructors vs Instantiations
  • Methods vs. Attributes
  • Working with strings
  • String formatting
  • Reading & writing file
  • Debugging skills
  • Exception handling
  • Finding documentation
  • Process of elimination
  • Random Variable
  • Probability Density Function
  • Some ‘standard’ distributions and their mean/stdev (Normal, Binomial). Properties of mean and variance
  • Indexing / slicing
  • Shape & reshape
  • Zeros, ones, arbitrary array declaration
  • Derivatives (including partial)
  • Matrix Operations
  • Matrix Multiplication

Our Alumni

More reviews

Our Alumni

Our Alumni are at

Our Alumni are at

Tell a friend about our program

And we'll give you both Amazon vouchers worth ₹ 5,000

Learn more

Frequently Asked Questions

No items found.
More answers

Download Prospectus

Thank you! We will email you a copy of the Prospectus shortly.

Would you like to find out which Program or Sprint is right for you?
Join an info session
Oops! Something went wrong while submitting the form.