About the course
Where do I begin? Data science is such a huge field  where do you even start learning about Data Science?
These are careerdefining questions often asked by data science aspirants. There are a million resources out there to refer but the learning journey can be quite exhausting if you don’t know where to start.
Don’t worry, we are here to help you take your first steps into the world of data science! Here’s the learning path for people who want to become a data scientist in 2022. We have arranged and compiled all the best resources in a structured manner so that you have a unified resource to become a successful data scientist.
Moreover, we have added the most indemand skills for the year 2022 for data scientists including storytelling, model deployment, and much more along with exercises and assignments.
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: This is a beginnerfriendly course and has no prerequisites.

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.

Updated skillset for 2022: The knowledge of Machine Learning models is important but that won’t set you apart. We have included some of the top unique skills you’ll require to become a data scientist in 2022.

Assignments to test yourself: What’s the best way to test your knowledge? Each module comes with assignments and MCQs to give your memory a boost.
Prerequisites
This is a beginnerfriendly course and has no prerequisites.
Course curriculum

1
Overview of the Learning Path 2022
 Overview of Learning Path
 MonthonMonth Plan
 Your Personalized Learning Path for Data Science
 AI&ML Blackbelt Plus Program (Sponsored)

2
January 2022: Data Science Toolkit
 Plan for January 2022
 Understanding Machine Learning and its impact
 Job of Data Scientist
 Exercise
 Overview of the Course
 A brief introduction to Python
 Introduction to Python Test
 Installing Python
 Theory of Operators
 Exercise
 Understanding Operators in Python
 Operators Test
 Understanding variables and data types
 Variable Test
 Variables and Data Types in Python
 Understanding Conditional Statements
 Exercise
 Implementing Conditional Statements in Python
 Conditional Statements test
 Understanding Looping Constructs
 Exercise
 Implementing Looping Constructs in Python
 Looping Constructs test
 Understanding Functions
 Implementing Functions in Python
 Functions test
 A brief introduction to data structure
 Data Structure test
 Understanding the concept of Lists
 Lists test
 Implementing Lists in Python
 Exercise
 Understanding the concept of Dictionaries
 Exercise
 Implementing Dictionaries in Python
 Dictionaries test
 Understanding the concept of Standard Libraries
 Libraries test
 Reading a CSV File in Python  Introduction to Pandas
 Reading a CSV file in Python: Implementation
 Reading a csv file in Python test
 Understanding dataframes and basic operations
 DataFrames and basic operations test
 Reading dataframes and conduct basic operations in Python
 Reading dataframes and conduct basic operations in Python Test
 Indexing a Dataframe
 Indexing DataFrames test
 Exercise
 Sorting Dataframes
 Merging Dataframes
 Quiz: Sorting and Merging dataframes
 Apply function
 Aggregating data
 Quiz: Apply function and Aggregating data
 Basics of Matplotlib
 Data Visualization using Matplotlib
 Quiz: Matplotlib
 Basics of Seaborn
 Data Visualization using Seaborn
 Quiz: Seaborn
 Regular Expressions
 Understanding Regular Expressions
 Quiz: Regular Expressions
 Regular Expressions in Python
 Quiz: Regular Expressions in Python
 Cheatsheet for Python
 Instructions
 Quiz
 Python Coding Challenge

3
February 2022: Data Visualization
 The Power of Visualization FREE PREVIEW
 What is Data Visualization and Why Should we Use it FREE PREVIEW
 Exercise  Definition of Data Visualization
 Hans Rosling  200 Countries 200 Years 4 Minutes FREE PREVIEW
 4 Key Elements of Effective Data Visualizations FREE PREVIEW
 Why Tableau is a Powerful Tool for Professionals
 What We Will Cover in this Course FREE PREVIEW
 Compare Tableau Against Power BI and Qlik
 The Tableau Range of Products
 The 5 Tableau Products you should Know
 Installing Tableau Desktop on your System
 Installing Tableau Public on your System
 Difference Between Tableau Server and Tableau Online
 Navigating the Tableau Interface (Part 1)
 Navigating the Tableau Interface (Part 2)
 Connecting to Data Sources in Tableau
 Understanding the Problem Statement
 Download the Superstore Dataset
 Loading the Dataset and Getting Familiar with the Variables
 Build your First Visualization in Tableau!
 HandsOn with Labels and Formatting
 Playing Around with Colors
 Using Filters to Build a Pivot Structure in Tableau
 Exporting your Tableau Worksheet
 The Different Chart Types in Tableau
 Line Charts  Working with Time Series Data
 Building Line Charts in Tableau
 Exercise  Sales of Each Category MonthbyMonth
 Generating Map Visualizations for Geospatial Analysis
 Map Visualizations in Tableau
 Exercise  Sales by City Analysis
 Bar Charts, Histograms, Scatter Plots, Bubble Charts, Pie Charts
 Dual Axis Charts in Tableau
 Date Dual Axis Charts in Tableau
 What are Calculated Fields?
 Feature Engineering in Tableau  Average Shipping Time
 Exercise  Number of Orders per State
 Calculating the Average Order Value
 Average Order Value for Product SubCategories
 What are Parameters in Tableau?
 Using Parameters to find Top N Customers
 Using Parameters to Analyze Superstore's Variable Values
 Joins and their Different Types in Tableau
 Performing Data Joining in Tableau
 What is Blending? How is it Different from Joins?
 Blending Data in Tableau
 Download the Coffee Chain Dataset
 Introduction to Dashboards and their Use Cases
 Reading Material  Dashboards in Tableau
 Designing your First Dashboard in Tableau
 Using Parameters to Create Dynamic Dashboards
 How to Upload your Work to the Tableau Public Gallery
 Designing the Blueprint for a MultiDashboard View to Analyze Sales
 Building Multiple Interlinked Dashboards in Tableau for our Business
 The Art of Storytelling
 3Step Storytelling Framework
 Sketching the Story Blueprint
 Profits by Region Analysis using Storyboard in Tableau
 Capstone Project: Sales and Profit by Segment using Storyboards in Tableau
 Getting started with SQL
 Introduction FREE PREVIEW
 Why do we need databases? FREE PREVIEW
 What is a database? FREE PREVIEW
 Some properties of a Good Database FREE PREVIEW
 Types of Databases
 How data is Stored in Relational Databases
 How data is stored in NoSQL databases
 Companies using MySQL FREE PREVIEW
 Exercise 1
 Introduction
 Architecture: Client and Server
 MySQL Distributions
 Local Installation on Mac
 Local Installation on Linux
 Local Installation on Windows
 Licensing
 Accessing a remote MySQL server
 Graphical user interfaces
 Exercise 2
 SQL  Installation Guide
 Introduction
 What exactly is SQL?
 History of SQL
 Connecting to MySQL
 Types of Commands  DDL (Creation/ Deletion/ Updating of Schema
 Types of Commands  DML (Manipulating data in tables)
 Types of Commands  DCL (Managing Access control)
 Exploring databases
 Creating tables
 Inserting data in tables
 SELECT Statement  Introduction
 Datatypes in MySQL
 NULL vs NOT NULL
 Exercise 3
 Introduction
 Update command – Concept
 Update command – Example
 Delete command – Concept
 Delete command – Example
 Describe command – Concept
 Describe command – Example
 Alter command – Concept and Example
 Exercise 4
 Introduction
 Importing data from CSV to MySQL
 Exporting data from MySQL to CSV
 Backing up databases
 Restoring databases
 Exercise 5
 Importing and Exporting Datasets  Troubleshooting Guide
 Introduction
 Counting Rows and Items
 Aggregation Functions – SUM, AVG, STDDEV
 Extreme Values Identification – MIN, MAX
 Slicing data
 Limiting data
 Sorting data
 Filtering Patterns
 Groupings, Rolling up data and Filtering in Groups
 Exercise 6
 Introduction
 Data Eyeballing
 Data Dictionary
 Questions we need answers of
 Analyzing data and creating table structure
 Loading data to our MySQL table
 Data Analysis – Simple Queries
 Data Analysis – Advanced Queries
 FIFA19 Players dataset (cleaned) for this Project
 Introduction
 The need for joins
 Different type of joins
 The Left Join  Concept
 The Left Join – Practical Example
 The Inner Join
 The Cross Join
 The Right Join
 The Self Join
 Exercise
 Introduction
 Introduction to Indexing
 How indexing works (basics)
 Relationships
 Types of Relationships
 Table Constraints – PRIMARY KEY, FOREIGN KEY, UNIQUENESS and AUTO INCREMENT
 Exercise
 String functions  CONCAT
 String functions – Case Conversion
 String functions – Trimming Strings
 String functions – Extracting Substrings
 Date/ Time functions – Current date and time
 Date/ Time functions – Extracting date and time from field
 Date/ Time functions – Formatting date and time as Strings
 Numeric functions
 SQL CheatSheet
 Exercise
 Introduction
 Setting up a virtual environment
 Installing the required packages
 Connecting to MySQL
 Connecting to database table and pulling data
 Querying the database INSERT
 Querying the database DELETE
 Querying the database SEARCH
 Querying the database INDEXING
 Notes and Resources
 Subscribe to Data Science Newsletter and Podcast

4
March 2022: Data Exploration
 Overview of Statistics
 Important applications of Statistics
 What is Descriptive Statistics?
 Introduction to Design experiments
 Introduction to Design experimentsVideo
 Exercise
 Visualizing Data
 Visualizing Data
 Central tendency
 Exercise
 Variability
 Unimodal Distribution of Data
 Bimodal Distribution of Data
 Normal distribution – Part 1
 Normal distribution – Part 2
 ZScore
 Introduction to Probability An Overview
 Principal Of Counting
 Exercise
 Permutation
 Exercise
 Combination
 Exercise
 Conditional Probability – Part 1
 Conditional Probability – Part 2
 Exercise
 Binomial Distribution
 Random variable
 Expectation and variance
 Exercise
 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

5
April 2022: Basics of Machine Learning and art of storytelling
 Overview of Machine Learning
 Understanding Data Science Pipeline
 Get Familiarised with Command Line (Linux) Guide
 Linear Regression
 Linear RegressionVideo
 Exercise
 Logistic Regression Part 1
 Logistic Regression – Part 2
 Exercise
 Decision Tree Algorithm
 Exercise
 Naive Bayes
 Support Vector Machine
 Regression Project  Big Mart Sales
 Classification Project  Loan Prediction
 Introduction to Structured Thinking
 Commonly Asked Puzzles in Interviews
 How to solve Guesstimates?
 Excercise: Strategic Thinking
 Structured Thinking and Communication Course

6
May 2022: Advanced Machine Learning
 Ensemble Learning Basics
 Ensemble Learning BasicsVideo
 Bagging
 Boosting
 Random Forest  Simplified
 Random Forest  Detailed with implementation
 Exercise
 Boosting  Detailed with implementation
 XGBoost
 LightGBM
 CatBoost
 Exercise
 Advanced Ensemble Technique  Blending
 Advanced Ensemble Learning  Stacking
 Cheatsheet for Machine Learning
 Image data
 Text data
 Audio data
 Audio dataVideo
 Projects
 Participating in Competitions
 Introduction to validation
 Different Types of Validation Techniques
 Kfold Cross Validation  Implementation
 Summary  Validation Techniques
 Exercise
 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
 Feature Engineering
 Profile Building
 Building your Resume
 Up Level your Data Science Resume Course
 Ace Data Science Interview Course

7
June 2022: Other Machine Learning Concepts
 Basics of Matrix Algebra
 Matrix Calculus
 Dimensionality Reduction  Overview
 Principal Component Analysis (PCA)
 Singular Value Decomposition (SVD)
 Singular Value Decomposition (SVD)Text
 Unsupervised LearningK Means and Hierarchical Clustering
 Clustering  Project
 Learn Github
 Introduction to Recommendation Systems
 Introduction to Recommendation Systems  Video
 Project: Recommendation System
 Implementation in Python
 Introduction to Time Series Forecasting
 Handling a NonStationary Time Series in Python
 Time Series Modeling using ARIMA
 Time Series Modeling using Prophet Library
 Time Series Project
 Project  Black Friday

8
July 2022: Introduction to Deep Learning and Computer Vision
 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)
 Understanding Convolutional Neural Networks (CNNs)
 Build Image Classification Model using Keras
 Exercise
 Transfer Learning for Computer Vision
 Computer Vision Project 1 : Identify the Apparels
 Computer Vision Project 2: Scene Classification
 Computer Vision using Deep Learning Course
 Computer Vision Course (Sponsored)
 Cheatsheet for Keras
 Write for Analytics Vidhya's Medium Publication

9
August 2022: Basics of Natural Language Processing
 Recurrent Neural Network
 Long short Term Memory Networks (LSTM)
 Gated Recurrent Unit (GRU)
 Useful resourcesGRU
 Text Preprocessing
 Text Cleaning
 Text Classification
 Natural Language Processing (NLP) Using Python Course

10
September 2022: Model Deployment
 How to Deploy Machine Learning Models using Flask
 Tutorial to deploy Machine Learning models in Production as APIs
 Deploying machine learning models using Streamlit – An introductory guide to Model Deployment
 An Ode to Model Deployment using Streamlit – Open Sourcing “Typing Tutor for Programmers”
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.