About the course
The most common question we get from beginners in the field of Data Science is  Where to begin? The journey to becoming a Data Scientist can be diffficult if one does not have the right resources to follow. There are a million resources to refer and it is tough to decide where to start from.
We are here to help you take your first steps into the world of Data Science. Here is a free learning path for people who want to become a data scientist in 2019. We have arranged the best resources in a logical manner along with exercises to make sure that you only need to follow one single source to become a data scientist.
Key takeaways of this course?
The course is ideal for beginners in the field of Data Science. Several features which make it exciting are:
Beginner friendly course: The course assumes no prerequisites and is meant for beginners
Curated list of resources to follow: All the necessary topics are covered in the course, in an orderly manner with links to relevant resources and hackathons.
Prerequisites
This is a beginner friendly course and has no prerequisites.
Course curriculum

1
January 2019
 Getting Started
 Knowing Each Other
 Overview of Learning Path
 MonthonMonth Plan
 Understanding Data Science
 Job of Data Scientist
 How to setup your machine?
 Python for Data Science
 Cheatsheet for Python
 Overview
 Important applications of Statistics
 What is Descriptive Statistics?
 Introduction to Design experiments
 Introduction to Design experimentsVideo
 Visualizing Data
 Visualizing Data
 Central tendency
 Variability
 Unimodal Distribution of Data
 Bimodal Distribution of Data
 Normal distribution – Part 1
 Normal distribution – Part 2
 ZScore
 Introduction to Pandas/NumPy Part1
 Introduction to Pandas/NumPy Part2

2
February 2019
 Join Data Science Communities
 Introduction to Probability An Overview
 Principal Of Counting
 Permutation
 Combination
 Conditional Probability – Part 1
 Conditional Probability – Part 2
 Binomial Distribution
 Random variable
 Expectation and variance
 Cheatsheet for Probability
 Statistics: InferentialHypothesis Testing
 Ttest
 One Way ANOVA
 Chisquare
 Cheatsheet on Statistics
 Exploratory Data Analysis (EDA) Data Exploration
 Cheatsheet on EDA
 Project1  Loan Prediction
 Project2  Big Mart Sales
 Linear Algebra
 Free Course

3
March 2019
 Understanding Data Science Pipeline
 Get Familiarised with Command Line (Linux) Guide
 Linear Regression
 Linear RegressionVideo
 Logistic Regression Part 1
 Logistic Regression – Part 2
 Decision Tree Algorithm
 Naive Bayes
 Support Vector Machine
 Unsupervised LearningK Means and Hierarchical Clustering
 Project
 Cheatsheet for Machine Learning
 Regression Project  Big Mart Sales
 Classification Project  Loan Prediction

4
April 2019
 Ensemble Learning Basics
 Ensemble Learning BasicsVideo
 Bagging
 Boosting
 Random Forest  Simplified
 Random Forest  Detailed with implementation
 Boosting  Detailed with implementation
 XGBoost
 LightGBM
 CatBoost
 Introduction to Time Series Forecasting
 Handling a NonStationary Time Series in Python
 Time Series Modeling using ARIMA
 Time Series Modeling using Prophet Library
 Project

5