Introduction to Data Science


Introduction to Data Science

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.

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Data Science Overview

Introduction to Python
Understanding Operators
Variables and Data Types
Conditional Statements
Looping Constructs
Data Structure
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

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

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
Module Test - Predictive Modeling
Evaluate 3

Project 1 - Classification
Project 2 - Regression


Identifying the best agents

Your client is looking for help from data scientists like you to help them provide insigths using their past recruitment data. They want to predict the target variable for each potential agent, which would help them identify the right agents to hire.

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.

Student Evaluation

In this project, you will learn, how to implement the concepts of Clustering.



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

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.

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

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

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

The fee for this course is non-refundable.

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

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

Fee for this course is INR 7,999

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

Why take this course?

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.
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.
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
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.


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  • Status Active
  • Estimated Effort 08:00 (Hours per Week)


  • Videos 6 hrs
  • Projects 4 Real Life


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