Data Science & AI

Course with Placement Support

4.71/5 | 2 Lakh+ Ratings

A 6-month industry-focused program designed to turn you into a job-ready Data Scientist / AI Engineer.
You’ll master:
• Master Python, Statistics, SQL, ML, DL, Data Engineering & Big Data.
• Build end-to-end ML pipelines and real AI applications.
• Work on real-world datasets and create production-ready models.
• Learn MLOps & AI tools to boost automation, accuracy and productivity
• Train exactly like modern Data Science teams work today

Business Analyst

SDE II @ Microsoft

Data Analyst

SDE II @ Microsoft

Our Client Partners

and many more

Key Features

6 months live online instructor-led session

168 Hours of Self-paced Videos

25+ Industry Projects

Certification by iHub, IIT Roorkee

Learn from IIT Faculty & Top Industry Experts

Certification by Microsoft

3 Guaranteed Job Interviews*

Top 2 performers per batch will receive Rs 80000 in fellowship*

4.7 Skills You’ll Gain

Our Role In Your Success

Frontend: HTML, CSS, JavaScript, Bootstrap, React / Angular
Backend: Core Java, Spring Boot, Hibernate
Database: MySQL, Oracle T ools & AI: Git, JIRA, Jenki
Tools & AI: Git, JIRA, Jenkins, AI-powered coding tools
Practices: Agile, SDLC, MVC Architecture

Resume & LinkedIn optimization
Technical & HR mock interviews
Personalized career counselling
Access to exclusive job networks and hiring partners
Lifetime mentorship for continuous growth and upskilling

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Our Hiring Partners

Data Science Trends

Our Hiring Partners

13 % CAGR

Estimated growth by 2026

30 %

Increase in Job demand

Data Science

Annual Salary

Source : Glassdoor

Top Companies Hiring Globally

Hiring Companies

Source : Indeed

The India has 80,000 job opportunities available for Data Science

LinkdIn

Data Science earns an average annual salary of ₹6,08,328

Glassdoor

Cognizant, Spotify, etc. are recruiting Data Science across the world

Indeed

Course Syllabus

Module 01 - Fundamentals of Data Science & AI

Data Science and its concepts
Artificial Intelligence and its types
Machine Learning and its types
Essence of data in Data Science
Various Data Formats , Data Storage
Data Warehousing, Big Data
Application of statistics in Data Science

Module 02 - Python Programming

Introduction to Python
Variable and constants
Conditional constructs and loops
List, Tuples , Sets and Dictionary
Function, Modules and Packages
Object Oriented Programming
Exception Handling

Database handling in Python
String and Regular Expressions
Lambdas and Higher Order Functions
Generator and iterators
Map, Filter and Decorators
Capstone Project

Module 03 - SQL

Introduction to RDBMS concepts
Retrieving data
Filtering and Sorting data
Single row functions
Aggregate functions
Joins, Sub-queries
CRUD using SQL syntax
DDL, constraints

Module 04 - Excel for Data Analysis

Introduction to Excel for BI
Data Entry and Cleaning
Essential Formulas and Functions
Data Analysis Tools
Pivot Tables and Pivot Chart
Power Pivot and Data Modeling
Data Visualization- Excel Graphs
Excel BI Dashboards
Integration and Automation

Module 05 - Data Science Libraries

A. Numpy

Introduction to Numpy
Creating Numpy Arrays
Manipulation Numpy Arrays
Indexing, Slicing
Broadcasting and Reshaping
Arithmetic, Trigonometric functions
Statistical Function in Numpy

B. Pandas

Introduction to Pandas
Pandas Data Structures
Handling Pandas Data Series
Pandas Data Frames
Import & Exporting data from Excel files
Import & Exporting data from CSV files
Querying Data Frames

Indexing, Slicing Data Frames
Pandas Statistical Functions
Exploratory Data Ananlysis In Pandas
Data Cleansing functions in Pandas
Query() and groupby() in Pandas
Filter with loc and iloc in Pandas

C. Data Visualization Libraries

Introduction to Matplotlib
Data Visualization with Numpy & Matplotlib
Line graph, Bar Graph, and Histogram
Scatter plots, Box Plots and Pie charts
Confusion Matrix Heatmaps using SNS library
Object Oriented Programming

Module 06 - Python Powered Statistic

Statistic Sand its Types
Descriptive statistical concepts
Measures of Central tendency
Measures of Dispersion
Measures of Relationship
Measures of Shape
Moments, Correlation and Regression
Probability and its Types
Naïve Bayes - Conditional probability
Probability Distributions
Sampling Theory
Hypothesis Testing
Confidence Interval

Module 07 - Data Science–Machine Learning

Artificial Intelligence and its Types
Introduction to Machine learning(ML)
Applications of Machine Learning
Supervised Machine learning(SML)
Supervised Machine Learning algorithms
Linear Regression, Logistic Regression
Decision Tree, Random Forest
Support vector Machine and KNN
Working of ML algorithms
Performance metrics of Regression Supervised ML
Data Visualisation
Performance metrics of Unsupervised ML
Confusion Matrix and Heatmap for Classifications

And Hyper parameter in Classification SML
Hyper parameter tuning & GridSerachCV
K-fold Cross Validation technique
Applications of Supervised Machine Learning
Unsupervised Machine Learning
Unsupervised Machine Learning Algorithms
Clustering - K-Means Clustering
Dimensionality Reduction - PCA
Applications of Unsupervised Machine Learning
Introduction to Neural Networks
Introduction to Deep Learning
Natural Language Processing (NLP)
Overview of Generative AI

Module 08 - R Programming for Data Science

Module 09 - Capstone Project

Module 10 - Gen AI

Module 11 - Employability Lab

Module 12 - Quantitative Aptitude

Data Science Tools

Build Industry projects from Scratch

RetailPro: Smart Inventory Manager

Optimize inventory levels and reduce waste across retail chains by analyzing sales trends, restock cycles, and seasonal demand.

Technology: Data Analytics

FinScope: Business Expense Tracker

Track, visualize, and optimize company-wide expenses and revenues for better budgeting and forecasting.

Technology: Business Analytics

MetroCommute: City Transport Analysis

Evaluate public transport performance using ticket data and route occupancy trends to recommend route optimization.

Technology: Data Analytics

DineSmart: Restaurant Order Manager

Create a complete restaurant order management and billing solution with admin and kitchen modules.

Technology: .Net

ShopTrend: Online Store Insights Dashboard

Build an interactive dashboard that showcases online product trends, customer preferences, and category performance.

Technology: .Net

QuizBash: Interactive Coding Quiz Platform

A real-time coding quiz platform with scoring and feedback, designed to test job-ready skills.

Technology: Java

WeatherSnap: Forecast Dashboard System

Build a system that fetches and displays real-time and historical weather data with filtering options.

Technology: Java

The Learning Journey

Every learner at ITROOTS follows a path that ensures real progress and measurable results:

Step 1

Begin your transformation with a clear career roadmap

Step 2

Master Java and AI through focused, daily sessions.

Step 3

Work on real, AI-integrated projects that sharpen your skills.

Step 4

Strengthen your performance with assessments and mock interviews.

Step 5

Land your dream job with our 100% placement support.

Step 6

Enjoy lifetime mentorship and career guidance - always.

Our Placed Students

Results Speek Volumes

Priya Wagh Software Developer

ITROOTS is one of the best institutes for training and placement. The trainers are experienced, supportive, and always approachable. I completed my Full Stack Java Certification from ITROOTS and got placed as a Software Developer. Grateful to the entire ITROOTS team for their constant guidance.

Harsh Patil Full Stack Developer

Joining ITROOTS was the best decision for my IT career. In just six months, I learned Frontend, Backend, and Database technologies and got placed within a week after completing the course. The placement team is truly dedicated and helpful throughout the process.

Mayur Aware Software Tester

ITROOTS is an excellent place for learning and placement. The team is very supportive and helps you build knowledge from the basics, even if you come from a non-IT background. Thank you, ITROOTS, for helping me start my career with confidence.

Enquire For Demo Class

Data Science & AI Course - FAQs

How many hours will the Data Science & AI Online/Offline classes in Pune conducted each day?

For newcomers and working individuals, the duration will be 2 to 2.5 hours, and it will extend further if we incorporate daily doubt-clearing and interview preparation sessions

How can I enroll in the Data Science & AI course?