OBJECTIVES

Why Choose This Course

100% Placement Assistance

Get support with resume building, mock interviews, and job connections.

Expert Trainers from Industry

Learn from experienced developers working with real-world technologies.

Hands-On Projects

Build real-time applications and a capstone project to showcase your skills.

Comprehensive Curriculum

Covers everything from Frontend to Backend, including the latest Frameworks.

Certification & Internship

Earn a recognized certificate and gain practical experience through internships.

Flexible Batches

Choose between online and offline formats that suit your schedule.

Data Science Course Overview

Embark on a transformative journey into the world of data science with our NASSCOM FutureSkills Prime Certified program. This course is meticulously crafted to equip you with the skills and knowledge required to excel in data-driven industries.

Our Hiring Partners

Data Science with Python Course Curriculum Syllabus

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Python Core & Advanced

INTRODUCTION

Variables, Data Types, and Strings
Lists, Sets, Tuples, and Dictionaries

Control Flow and Conditional Statement, Functions, Modules and File Handling
Class and Objects

Data Analysis using Python

Numpy – NUMERICAL PYTHON
Data Manipulation with Pandas

DATA VISUALIZATION

Data Visualization using Matplotlib and Pandas
Exploratory Data Analysis

UNSTRUCTURED DATA PROCESSING

Regular Expressions

Project On Web Scraping: Data Collection And Exploratory Data Analysis

Advanced Statistics

Introduction to Statistics and Data Types
Descriptive Statistics
Probability Distribution
Inferential Statistics

Data Base (SQL) + Reporting Tool (Power BI)

Introduction to SQL
Data Exploration and Data Filtering (DQL and OPERATORS)
SQL Fundamentals
SQL Database Objects
Advanced Topics
Introduction To Power BI
Data Import And Data Visualizations
Power Queries
Power Pivot And Introduction To Dax
Data Analysis Expressions
Login, Publish To Web And RLS
Miscellaneous Topics

Machine Learning - Supervised & Un-Supervised Learning

Introduction
Validation Methods

Supervised Learning

Probability-Based Approach – Naive BayesPolynomial Regression
Introduction And Linear Algebra
Distance Based Approach – K Nearest Neighbors
Rule / Decession Boundary Based Approach – Decision Trees
Boundary-Based Linear Model – Linear Regression
Multiple Linear Regression
Evaluation Metrics for Regression Techniques
Polynomial Regression
Regularization Techniques
Logistic regression
Support Vector Machines
Ensemble Methods in Tree Based Models
Random Forest
Boosting: Adaboost, Gradient Boosting, XG Boosting:
Machine Learning Applications for Data Analysis

Un Supervised Learning

Dimensionality Reduction Techniques – PCA & t-SNE
K-Means Clustering
Hierarchical Clustering

Deep Learning

Introduction to Deep Learning
Principal Components Analysis
Neural Network Architecture and Activation Functions
Forward and Backward Propagation Optimizers
Neural Network Architecture and Activation Functions
Keras Hands-on – Regression and Classification

CNN & Computer Vision

Intro to Images and Image Preprocessing with OpenCV CNN Architecture
Image Classification Case Study
Transfer Learning
Case Study with Transfer Learning
Object Detection
YOLO – Case Study

Natural Language Processing

Introduction to text and Text Preprocessing with nltk and spacy
Vectorization Techniques
Project – Text Classification
RNNs
Project – Sequence Tagging
LSTMs
Auto Encoders
Transformer and Attention
BERT

Gen AI

Intro To Gen AI
Intro To LLM
Prompt Engineering and Working with LLM
Open AI
Gemini
LLaMA
LangChain

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Eligibility Criteria

✅Education: Bachelor’s degree in any field.

✅ Helpful Skills: Basic knowledge of programming and statistics is a plus (not required).

✅ Who Can Join? Beginners, analysts, or working professionals looking to transition into data science.

Job Opportunities in Data Science

Data Science professionals are essential across nearly every industry today. From healthcare and finance to e-commerce and entertainment, organizations rely on data-driven insights to stay competitive.

Here are some of the top career roles in the field of Data Science:



Business Intelligence Developer



Data Scientist



Applications Architect



Enterprise Architect



Data Architect



Data Engineer

Our Success Stories

Frequently Asked Questions

Got questions? Find quick answers about the course structure, eligibility, certification, and career support—all in one place.

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What are the prerequisites for joining this Data Science course?

No prior experience is required. However, basic knowledge of programming and statistics is helpful.

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Is this course suitable for beginners?

Absolutely. The course is designed to start from basics and gradually progress to advanced topics.

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What tools and technologies will I learn?

You’ll work with Python, NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Keras, and more.

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Do I get a certificate after course completion?

Yes, you will receive a course completion certificate from Innomatics Research Labs.

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Will I get placement assistance?

Yes, we offer resume building, mock interviews, and placement support.

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Can I enroll if I am from a non-IT background?

Yes, the course is designed to accommodate learners from various backgrounds, including non-IT professionals, with a focus on practical, hands-on training.