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FREE Master Class in
Data Science & A.I.

How To Land Your First Job In Data Science Without Having A Zero Knowledge Of Coding

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Join more than 400,000+ Data Science Aspirants worldwide

This webinar is best for:

Data Science Aspirants

Data Science aspirant who wants laser-focused guidance to start a high-demand Data-Science career.

Non-Technical Background

Comes from a completely non-technical background who has never done coding before

Zero-Coding Experience

Even if you have done a little bit of coding, but never worked as a Data Scientist

Working Professionals

Working professional who wants to upskill and to get into high paying Data Science role.

Wants Recession-Free Career

Build a recession-free career where market ups and downs don’t affect you in any way

Attendees of the cohort

A 12-month, immersive program that will help you build a growth mindset and the skills you need to succeed in your career.

Testimonials

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.

But, why Become a Data Scientist?

₹34.7 LPA

Experienced Data Scientist earn
an average of ₹35 Lakhs per annum

35000+

There are more than 35000 openings
for the role of Data Scientist

6000+

There are more than 6000 remote opportunities for Data Scientist

"The goal is to turn data into information, and information into insight."

Carly Fiorina

Course Curriculum

Module 1 : Python Fundamentals

Introduction to Python and Data Science
Working with Python Data Structures
Control Flow Statements
Functions in Python
File Handling in Python
Regular Expressions
Object Oriented Programming
Advanced-Data Structures in Python

Module 2 : Data Analysis with SQL

Introduction to SQL and MySQL
Data Creation and Retrieval
Data Filtering
Data Analysis using aggregate functions and group by
Joins and Keys
MySQL Joins
Subqueries and Views
Window/Analytical Functions
Case Study

Module 3 : Statistics and Probability

Introduction to Statistics
Probability Theory
Statistical Inference I
Statistical Inference II
Regression Analysis I
Regression Analysis II

Module 4 : Data Analysis with Excel

Unleashing the Power of Excel
Data Analysis with MS Excel
Summarizing and Forecasting
Macros and Dashboarding
Excel Project Session

Module 5 : Python for Data Science Visualization

Extracting and Aggregating Pandas
Matplotlib and Seaborn
Plotly and Cuffinks

Module 6 : Data Cleaning and Preparation

Introduction to Data Cleaning and Data Types
Exploring and Visualization the missing values
Advanced-Data Cleaning Concepts
Introduction to Feature Engineering
Feature Extraction and Transformation
Feature Selection and Dimensionality Reduction

Module 7 : Machine Learning (scikit)

Modeling with Linear Regression
Evaluating Models & Feature selection
Regularisation Techniques
Modeling with Logisitc Regression
Understanding other classification
algorithm like KNN & SVM
Advanced Model Evaluation Techniques
Introduction to Clustering and K Means
Advanced Clustering Techniques

Module 8 : Tree Based and Boosting Models

Introduction to Decision Trees
Implementation of Decision Trees
Introduction to the Concept of Bagging
Introduction to Concept of Random Forest
Introduction to Boosting
Introduction to extreme Gradient Boosting
Introduction to Imbalanced Machine Learning models
Introduction to Recommendation Engines

Module 9 : Time Series Analysis and Forecasting

Introduction to Time Series Analysis
Preprocessing and Visualization of Time Series Data
Time Series Forecasting using ARIMA
Exponential Smoothing Models for Time Series Forecasting
Machine Learning Models for Time Series Forecasting

Time Series Forecasting using Prophet

Module 10 : Natural Language Processing

NLP Fundamentals
Feature Engineering in NLP & Text Classification
Advanced-Data Cleaning for NLP text classification
Feature Extraction & Feature encoding for NLP
Introduction to Word Embeddings
Advanced word embeddings used to solve NLP problems
More about advanced NLP
NLP text classification end to end project from kaggle

Module 11 : Deep Learning Fundamentals

Building blocks of Deep Learning
Understanding the Components of a Neural Network
Introduction to Recurrent Neural Networks
Overview of LSTM and GRU
Introduction to Bidirectional Networks
RNN Use Cases in the Industry
Introduction to Convolutional Neural Networks (CNN)
Overview of Transfer Learning
Introduction to Transformers
Overview of AutoEncoders

This internship is a part of the course curriculum to help you gain real experience in the Data Science domain.During this internship, you will go through various challenges which you allow to explore new skills and push your limits while learning something new during the projects.

Topics Covered :

Technical skillset and your soft skills combine to make you employable. In order to make our learners employable, dedicatedly placement-oriented sessions are conducted while highlighting the use of Github, Linkedin, and other tools during the job search.

Topics Covered :

Select any one elective from list mention below

Comprehensive Curriculum

The curriculum has been designed by faculty from Expert Industry Professionals and NASSCOM

400+

Hours of Content

150+

Live Sessions

15+

Tools & Software

Instructed by

Ankit Maheshwari

Data Scientist, Serial Entrepreneur (20+ years of experience)

Ankit Maheshwari is a serial entrepreneur and a proud bootstrapper who has founded and sold multiple internet companies including Betaout (exited to Bluecore), Instamedia (exited to Valent) etc. He is listed as Asia’s one of the most inspiring young entrepreneurs and social change maker by Paragon 100 Asia, featured in BusinessWeek in BusinessWorld’s Top 30 Young Entrepreneurs in India.

His current venture is Dataisgood where he is following his life-long passion of helping students and working professionals to build a Career in Tech and data Science through engaging and specialised professional cohort based courses.

He has also served as Founding Director of Bluecore India and also Director of Data Engineering at Bluecore. Bluecore acquired his last startup Betaout in 2018. Prior to Betaout, he founded Instamedia Network – a lifestyle blog network. Instamedia was serving over 20 Million page views before it was acquired by a Dubai based Media Company. He has over 15 years of experience building startups specialised in Data Science, Big Data and AI.