Learning path

Change the traditional approach to learning Business Analyst. Instead of spending months on maths and theory, focus on projects, practical skills and tech that in in-demand

Key Features

DataisGood gives you a platform that will leave no stone unturned in our bid to make you a Rockstar Data Scientist. We have meticulously planned your journey for a promising and fulfilling Data Science career ahead.


100+ Hours of Instructor-Led Training


200+ Hours of Self Paced Training


500+ Exercises and Assessments


Dedicated Career Coach


Professional Certification Programme


24/7 Support


World-class faculty from top academic centres and corporates across Europe and USA.

Nilesh Sukalikar

Technical Lead at Union Data (Full-Stack)

Nikhil Garg

Leading Data Science, ML & Finance Instructor

Dipti Tandon

Co-Founder | AI Matchmaking for Business

Vidit Aggarwal

Analytics Manager at Compass Group

Course Curriculum

We brought together some of the of best data scientists, AI and ML entrepreneurs, Kaggle grand masters to create Industry best courses and projects for you to build a 🤘 ROCKSTAR Business Analyst in you.


Course 1

✔ Learn Basic formatting, and different Data Types in Excel.

✔ Learn Analytical and Aggregate Functions in Excel.

✔ Learn Text, Logical, and Statistical Functions in Excel.

Course 2

✔ Learn about Data Cleaning and Preparation Functions.

✔ Learn to make Pivot Tables and Pivot Charts in Excel.

✔ Learn Data Visualizations and Dashboarding in Excel.

Course 3

✔ Learn about SELECT, and WHERE Statements.

✔ Learn to use Logical Operators and aggregate Functions.

✔ Learn to use Order By and Group By Clauses.


Course 4

✔ Learn to create a Databases, and Tables with proper validations and Constraints.

✔ Learn different types of Joins in SQL.

✔ Learn to Handle Complex Queries using Sub Queries in SQL. 

Course 5

✔ You will learn to create simple dashboards.

✔ You will learn about the dimensions, measures and filtering data.

✔ You will learn to prepare the Charts, and Maps.

✔ You will learn about the Formatting Pane, Styling, Customizing tooltip and mark labels, etc.

Course 6

✔ You will learn about managing data, Data extraction, Joins and blending, etc.

✔ You will learn about sorting, groups, hierarchies, sets, data filters.

✔ You will learn about maps, layers, geocoded fields, WMS, etc.

✔ You will learn about storytelling, dashboards, Containers, dashboard actions.


Course 7

✔ Learn about Variables, Data Types, and Operators in Python.

✔ Manipulate Python strings using In-built functions.

✔ Understand the Concept of Loops and Conditionals.

Course 8

✔ Learn Data Structures for solving complex problems.

✔ Learn about Lists, Tuples, Dictionaries, Sets, Stacks and Queues.

✔ Learn Sorting, and Searching Algorithms.

Course 9

✔ Learn about Parameters and different Types of Arguments in a Function.

✔ Learn about Comprehensions and  Anonymous Functions.

✔ Learn about OOPs Concepts.

Course 10

✔ Learn about Date and Times and Regular Expressions.

✔ Learn Numpy for Complex Mathematical Operations.

✔ Learn Pandas in depth for Data Frame Manipulation.

Course 11

✔ Learn Bayes Theorem, Basic and Conditional Probabilities.

✔ Learn Normal Distributions, Skewness, and QQ Plots.

✔ Learn Central Limit theorem, and Confidence Intervals.

Course 12

✔ Learn the Types of Error in Hypothesis Testing.

✔ Learn to implement t-Test, z-Test and their types.

✔ Learn ANOVA, Chi squared Goodness Tests, and  Chi square Test of Independence.

Course 13

Data Exploration

✔ Learn to analyze the Target Data using the Dabl library.

✔ Learn Pandas Profiling for analyzing the whole data at once.

✔ Learn about the Sweet Viz for Comparing Datasets.

Course 14

✔ Learn to Handle Missing values in a Real-world Scenario.

✔ Learn to Handle Outliers in a Real-world Scenario.

✔ Learn Data Manipulation Functions for Cleaning the Data.

Course 15

✔ Learn Univariate, Bivariate and Multivariate Analysis.

✔ Learn Animated and Interactive Data Visualizations.

✔ Plot Charts used in Finance, Marketing etc.

Course 16

✔ Perform Grouping Operations and Filtering Operations.

✔ Perform Interactive Query Analysis using Ipy Widgets.

✔ Learn Cross Tabulation using Cross Tabs.

Course 17

✔ Learn to Extract Features from Dates and Times.

✔ Learn to Extract Features from Numerical Data and Categorical Data.

✔ Learn Advanced Functions to Extract New Features from the Data.

Course 18

✔ Learn advanced Data Transformations Techniques.

✔ Learn Encoding Techniques to deal with Categorical Data.

✔ Learn Cross Validation Techniques.


Course 19

✔ Implement Machine Learning Algorithms.

✔ Learn Regularization Techniques such as Ridge, Lasso, and Elastic Net.

✔ Learn Feature Selection,  Hyper Parameter Tuning for Improving the Model.

Course 20

✔ Implement Decision Trees and Random Forestsusing Sklearn.

✔ Learn Gini Index and Information Gain.

✔ Understand the working of Random Forests and Decision Trees in Depth.


Course 21

✔ Understand the Concept of Boosting using Ada Boosting Gradient Boosting.

✔ Learn to implement the XG Boost Model.

✔ Learn about the Ensembling Techniques used to Enhance Accuracy of Predictive Models.

Course 22

✔ Understand the Concept of Over Sampling and Under Sampling.

✔ Implement Over Sampling and Under Sampling Techniques.

✔ Using XG Boost for Imbalanced Data sets.

Course 23

✔ Understand the Working of K Means, Hierarchical, and DBSCAN Clustering.

✔ Implement K Means, Hierarchical, and DBSCAN  Clustering using Sklearn.

✔ Learn Evaluation Metrics for Clustering Analysis.

Course 24

✔ Learn Techniques used for Treating Dimensionality.

✔ Implement Correlation Filtering, VIF, and Feature Selection.

✔ Implement PCA, LDA, and t-SNE for Dimensionality Reduction.

Course 25

✔ Learn to Process and Prepare a Time Series Data.

✔ Learn Advanced AR Models ARIMA, ARIMAX, SARIMA, and SARIMAX.

✔ Learn Evaluation Metrics for Time Series Models.

Course 26

✔ Learn about different business tools to better collaborate, collect and sort data.

✔ Learn to keep track of the performance and strategy to grow for the businesses.

Course 27

✔ Learn understanding business problems using different frameworks.

✔ Learn to create hypotheses and learning about specialized business frameworks such as BANT framework, SWOT analysis.

✔ Implement them in real life.

Success Stories

Meet some of our Extremely Talented and Hardworking Alumnis at DataisGood Career Transition Programs who achieved their Dream Jobs as a Data Scientist and Data Analyst in some of the Most Reputed MNCs and Startups.

Data Analyst at Dhruv Research
Background: Content Manager
Education: MSc Maths

Data Scientist at Data Is Good
Background: Fresher
Education: B.Sc

Sarfaraz Ahmed

Software Developer at Betaout India
Background: Fresher
Education: B.Tech CSE

Prakash Narasanagi

Data Scientist at InViz AI
Background: Fresher
Education: B.Tech CSE

Our learners work at


We are on a mission to create Data Science courses that will make our students not just learn the subject, but fall in ❤️ love with that subject so that they become lifelong passionate learners and explorers of that subject.

Office Location

All rights reserved. © 2019-21. || Email: [email protected] || Phone: +91 88649 50180
Data is Good, B-33, 1st Floor, Sector 6, Noida – 201301
Terms | Privacy

Call us on +91 88649 50180

  (Nancy Bajaj, Senior Admission Councellor)