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
May 2019
 Introduction to validation
 Different Types of Validation Techniques
 Kfold Cross Validation  Implementation
 Summary
 Different methods for finding best hyperparameters of an algorithm
 Hyperparameter tuning for Random Forest
 Hyperparameter tuning for GBM
 Hyperparameter tuning for XGBoost
 Hyperparameter tuning for LightGBM
 Bayesian Hyperparameter Optimization
 Advanced Ensemble LearningStacking
 Blending
 Feature Engineering
 Project  Black Friday

6
June 2019
 Basics of Matrix Algebra
 Matrix Calculus
 Dimensionality Reduction  Overview
 Principal Component Analysis (PCA)
 Singular Value Decomposition (SVD)
 Singular Value Decomposition (SVD)Text
 Image data
 Text data
 Audio data
 Audio dataVideo
 Projects
 Introduction to Recommendation Systems
 Introduction to Recommendation Systems  Video
 Implementation in Python
 Project

7
July 2019
 Profile Building
 Learn Github
 Building your Resume
 Up Level your Data Science Resume  Course (Sponsored)
 Ace Data Science Interview Course (Sponsored)
 Participating in Competitions
 Setting up the System for Deep Learning
 Introduction to Deep Learning
 Build your first Neural Network in Numpy
 Why are GPUs necessary for Deep Learning?
 The Evolution and Core Concepts of Deep Learning & Neural Networks
 An Introduction to Implementing Neural Networks using TensorFlow
 Introduction to Keras
 Optimizing Neural Networks using Keras (with Image recognition case study)
 Cheatsheet for Keras

8
August 2019
 SQL for Data Science  Overview
 SQL Questions for Aspiring Data Scientists
 Understanding Convolutional Neural Networks (CNNs)
 Build Image Classification Model using Keras
 Transfer Learning

9
September 2019
 Computer Vision Project 1
 Computer Vision Project 2
 Computer Vision Course (Sponsored)
 Computer Vision Course (Sponsored)

10
October 2019
 Introduction to Structured Thinking
 Commonly Asked Puzzles in Interviews
 How to solve Guesstimates?
 Excercise: Strategic Thinking
 Recurrent Neural Network
 Long short Term Memory Networks (LSTM)
 Gated Recurrent Unit (GRU)
 Useful resourcesGRU
 Text Preprocessing
 Text Cleaning
 Text Classification

11
November 2019
 Topic Modeling  Overview
 Latent Semantic Analysis
 Latent Dirichlet Allocation (LDA)
 Text Summarization  Overview
 TextRank for Automatic Summarization
 Resources
 NLP Course (Sponsored)
 NLP Course Video
 Word Embeddings
 Word EmbeddingsText

12
December 2019
 Jobs and Internships
 Up Level your Data Science Resume  Course (Sponsored)
 Ace Data Science Interview Course (Sponsored)
 Way Forward
Instructor

Analytics Vidhya
Analytics Vidhya provides a community based knowledge portal for Analytics and Data Science professionals. The aim of the platform is to become a complete portal serving all knowledge and career needs of Data Science Professionals.
Here's what our students have to say about our A comprehensive Learning path to become a data scientist in 2019 course

DS Learning Path
ABDULRAHEEM ADESINA
Great tutorial structure and systematic approach to knowledge transfer. I rate the course 93%
Great tutorial structure and systematic approach to knowledge transfer. I rate the course 93%
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good one to learn from basics
prabhas_kulkarni prabhas_kulkarni
good
good
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January 2019
candra saputra
it's awesome, i hope each video in the lesson have the subtitle
it's awesome, i hope each video in the lesson have the subtitle
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Methodical training plan
Ravi Sankar Kodamarti
This learning path is both methodical and practical. Strongly recommend newbies to check this one.
This learning path is both methodical and practical. Strongly recommend newbies to check this one.
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Very Much Useful course
Vaibhav Kumar
Very Much Useful course for beginners. Every newbie must attend this course.
Very Much Useful course for beginners. Every newbie must attend this course.
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Good for data science
Taghreed Hamdy
I think this successful step for me to start my career
I think this successful step for me to start my career
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Good beginning
Vengala Reddy Illuri
Very good beginning to start analytics
Very good beginning to start analytics
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Precise
Shashank Upadhyay
A very intuitive beginner level course!
A very intuitive beginner level course!
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Well arranged
Godfrey Njoka
The learning material is in a very procedural way, it is easy to follow. Thanks
The learning material is in a very procedural way, it is easy to follow. Thanks
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A comprehensive Learning path to become a data scientist ...
Abhishek Shrivastava
A very great platform for learning.
A very great platform for learning.
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Contains nicely organized flow of contents from the best ...
Manasvini Ganesh
Contains nicely organized flow of contents from the best resource from each topic.
Contains nicely organized flow of contents from the best resource from each topic.
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FAQ

What web browser should I use?
Our training platform works best with current versions of Chrome, Firefox or Safari, or with Internet Explorer version 9 and above. See our list of supported browsers for the most uptodate information.

How do I need to pay for this course?
Nothing! Yes  you read it right. This course is free for our community members as a way to get them started in Data Science.

Do I get certificate upon completion of the course?
No, we do not provide certificate with this course.

Where do I ask my queries?
You can post your queries on the discussion for the course or share them on the discuss portal at discuss.analyticsvidhya.com
Support for A comprehensive Learning path to become a data scientist in 2019
Support for A comprehensive Learning path to become a data scientist in 2019 course can be availed through any of the following channels:
 Phone  10 AM  6 PM (IST) on Weekdays Monday  Friday on +918368253068
 Email [email protected]
analyticsvidhya.com (revert in 1 working day)  Live interactive chat sessions on Monday to Friday between 7 PM to 8 PM IST.