Skip to main content

Introduction to Data Science


Get flat 20% Discount on this course. Use COUPON CODE: TODAY20 To Get 20% Discount Today (Apply this code at checkout)


Price: INR 6,399 (7,999)


Offer Ending Soon

About This Course

The role of a Data Scientist is one of the hottest in the industry. With this course, we aim to provide you with a comprehensive Introduction to Data Science.

We will cover the basics of Python, before moving to Statistics and finally going through various Modelling techniques. By the end of the course, you will have a solid understanding of Data Science and will be able to build an end-to-end predictive model.


This course assumes no past knowledge about Data Science or any tool.

Why take this course

  1. Easy to understand content

    The biggest challenge beginners face is that most of the courses explain data science as a difficult mathematical subject. Not us! We simplify the subject with easy to understand videos and help you build intuition on data science concepts.

  2. Experienced Instructors

    All the material in this course was created by Analytics Vidhya instructors who bring in immense experience of data science with them. Combined among us, we have more than a decade of teaching experience.

  3. Industry collaboration

    Entire course has been vetted by industry experts. This ensures relevance in industry and enabling you with the content which matters the most

  4. Real life problems

    All projects in the course are based on real life problems. No academic datasets are bring used to ensure that you are ready for real life problems.

Sample Videos

Course Projects

Identifying the best agents

This project is designed to teach you how to extract relevant information such as entities, ngrams, keywords and sentiments from social media data using NLP techniques. The project highlights the importance of nlp techniques to extract business insights from the text data.

Sales Prediction for a large Supermarket

The data scientists at BigMart have collected sales data for 1559 products across 10 stores in different cities for an entire year. Also, certain attributes of each product and store have been defined. You will build a predictive model to forecast the sales of each product at a particular store.

Predict the Titanic Survivors

You will analyse what kind of people were likely to survive in Titanic tragedy. You will apply machine learning tools to predict which passengers survived the tragedy.

Social Media Information Extraction

This project is designed to teach you how to extract relevant information such as entities, ngrams, keywords and sentiments from social media data using NLP techniques. The project highlights the importance of nlp techniques to extract business insights from the text data.


Introduction to Data Science
  • Data Science Overview

  • DataHack Summit 2018 (Sponsored)

Basic Python for Data Science
  • Introduction to Python

  • Understanding Operators

  • Variables and Data Types

  • Conditional Statements

  • Looping Constructs

  • Functions

  • Data Structure

  • Lists

  • Dictionaries

  • Understanding Standard Libraries in Python

  • Reading a CSV File in Python

  • Data Frames and basic operations with Data Frames

  • Indexing a Data Frame

  • Evaluate 1

Understanding Statistics for Data Science
  • Introduction to statistics

  • Measures of Central Tendency

  • Understanding the spread of data

  • Data Distribution

  • Introduction to Probability

  • Probabilities of discrete and continuous variables

  • Central Limit theorem and the Normal Distribution

  • Introduction to Inferential Statistics

  • Understanding the Confidence Interval and the margin of error

  • Hypothesis Testing

  • T tests

  • Chi Squared tests

  • Understanding the concept of Correlation

  • Module Test - Statistics

  • Evaluate 2

Predictive Modeling and the basics of Machine Learning
  • Introduction to Predictive Modeling

  • Understanding the types of Predictive Models

  • Stages of Predictive Models

  • Hypothesis Generation

  • Data Extraction

  • Data Exploration

  • Reading the data into Python

  • Variable Identification

  • Univariate Analysis for Continuous Variables

  • Univariate Analysis for Categorical Variables

  • Bivariate Analysis

  • Treating Missing Values

  • How to treat Outliers

  • Transforming the variables

  • Basics of Model Building

  • Linear Regression

  • Decision Trees

  • K-Means

  • Module Test - Predictive Modeling

  • Evaluate 3

Final Project
  • Project 1 - Classification

  • Project 2 - Regression

Course Projects

Kunal Jain

Kunal Jain is the founder of Analytics Vidhya. Analytics Vidhya is the community based Data Science portal. Before starting Analytics Vidhya, Kunal had worked in Analytics and Data Science for more than 8 years across various geographies and companies like Capital One and Aviva Life Insurance. He will introduce you to the field of Data Science through this course.

Neeraj Singh Sarwan

Neeraj is working as a data scientist at Analytics Vidhya. He has extensive experience in converting business problems to data problems. He has previously taken several corporate trainings and is also an avid blogger. He’s a graduate of IIT-BHU and will be your instructor for the ‘Python’ and ‘Modeling’ modules.

Pranav Dar

Pranav is the editor for Analytics Vidhya. He has experience in data visualization and has been previously involved in the learning & development departments of MNCs. He has taken various trainings on statistics & presentation skills and loves to read, write about anything from data science to machine learning. He will be your instructor for the statistics module.

Frequently Asked Questions

Who should take this course?

This course is meant for people looking to learn Data Science. We will start out to understand the pre-requisites, and then go on to solve case studies using Data Science concepts.

When will the classes be held in this course?

This is a self paced course, which you can take any time at your convenience over the 6 months after your purchase.

How many hours per week should I dedicate to complete the course?

If you can put between 6 to 8 hours a week, you should be able to finish the course in 4 to 6 weeks.

Do I need to install any software before starting the course ?

You will get information about all installations as part of the course.

What is the refund policy?

The fee for this course is non-refundable.

Do I need to take the modules in a specific order?

We would highly recommend taking the course in the order in which it has been designed to gain the maximum knowledge from it.

Do I get a certificate upon completion of the course?

Yes, you will be given a certificate upon satisfactory completion of the course.

What is the fee for this course?

The fee for this course is Rs. 7,999.

How long can I access this course?

You will be able to access the course material for 6 months since the start of the course.

Is there any placement support with this course?

This is a beginner course and comes without any placement support. You can check various opportunities on Analytics Vidhya Jobs portal and participate in our Hiring Hackathons


For people undergoing the course, you can call us any time between 9 a.m. - 5 p.m. on Weekdays Monday - Friday on +91-8368253068 or email us on

  1. Course Number

  2. Classes Start

  3. Classes End

  4. Estimated Effort

    08:00 (Hours per Week)
  5. Price

  6. Course Rating