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Data Science Program

for Data Analyst & Data Scientist

Accelerate your career with a data science program

About the Program

Choose from the 5 sets, receive career assistance and mentorship from our experts, learn programming tools & languages & much more.


Introduction to R-Programming

Getting Data Into R

R Objects

Accessing Variables & Managing Subsets of Data.


Plotting Graph (Visualization)

Programs & Loops

Application – Exploratory Data Analysis

Need to learn Statistics

Descriptive Statistics

Introduction to Probability

Hypothesis Testing

Categorical Data Analysis

Comparing Two Means

Comparing Several Means (One-Way ANOVA)

Linear Regression

Factorial ANOVA

Gateway to Machine learning
Introduction to Machine Learning.

Lazy learning – Classification using Nearest Neighbours.

Case 1 – diagnosing breast cancer with the k-NN algorithm.

Probabilistic Learning – Classification using Naïve Bayes

Case 2 – filtering mobile phone spam with Naïve Bayes Algorithm.

Classification Using Decision Trees and Rules.

Regression Methods

Black Box Methods – Neural Networks.

Finding Patterns – Market basket analysis using Association Rules.

Finding Groups of Data – Clustering with k-Means

Case 8 – finding the teen market segment using k-means clustering

Evaluating Model Performance:

Improving Model Performance:

Data Analytics using Python

Machine Learning Algorithms

Machine Learning

Linear Regression

Logistic Regression

Decision Trees and Random Forests

Support Vector Machines
K-Means Clustering

Principal Component Analysis

Neural Networks, Deep Learning and TensorFlow

Understanding the Basics

Connecting to data

Data Transformation

Calculations in Tableau

More Calculations

Creating Maps

Filters & Parameters


Groups, Sets & Bins

Creating Visualization

Dashboard’s & Visual Story

About Trainer

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Mr. Mithun Radhakrishnan

Data Science AI Enthusiast
Mr. Radhakrishnan frequently conducts R-Programming, Tableau training sessions and sessions on Exploratory Data Analysis, Statistics and Machine Learning...
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Mr. Rahul Rampurkar

Certified Data Scientist (DP-100), Expert in Java & Python
Mr. Rampurkar is an AWS Certified Solutions Architect with 23+ years of experience in IT industry....

Programming Languages and Tools Covered

Industry Projects

Learn through real-life industry projects sponsored by top companies across industries

Engage in collaborative projects with student-mentor interaction
Benefit by learning in-person with expert mentors
Project # 1

Filtering mobile phone spam with Naïve Bayes Algorithm...

Project # 2

Identifying risky bank loans using C5.0 decision tree....

Project # 3

Identifying poisonous mushrooms with the rule learners

Project # 4

Predicting medical Expenses using Linear regression ...

Project # 5

Modelling the strength of concrete with ANNs.


How You Benefit From This Program

- Knowledge and expertise on the Data Science tools & technologies

- Skills that can help you land a dream job in Data Science

- Cutting-edge curiculum designed by industry experts

- Career transition with 58% average salary hike

I’m Interested in this program

Frequently Asked Questions

A Data scientist is the top ranking professional in any analytics organization. In today’s market, Data Scientists are scarce and in demand. As a Data Scientist, you are required to understand the business problem, design a data analysis strategy, collect and format the required data, apply algorithms or techniques using the correct tools, and make recommendations backed by data. What is the time commitment expected for the program? At least 12-15 hours per week of time commitment is expected to be able to complete the program. Will I receive special different career services in each specialization? Each specialization is designed to give you the best outcome based on your background and help you venture into the data domain. The services and support for all the tracks will remain the same. Every student will have live sessions, preparatory support, and access to relevant opportunities according to the requirements in their specialization track.
In today’s era of “big data”, data science has critical applications across most industries. This gives students with data science backgrounds a wide range of career opportunities, from general to highly specific. Some companies may hire data scientists to work on the entire data life cycle, while larger organizations may employ an entire team of data scientists with more specialized positions such as data engineers to build data infrastructure or data analysts, business intelligence analysts, decision scientists to interpret and use this data.
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