Data Science & Analytics

Master Python, Machine Learning, Deep Learning, Power BI, SQL, Generative AI & LLMs — with Live Datasets, Industry Projects & Placement Assistance.

Mode

Online Only

Duration

3 Months Training + 3 Months Internship

Fees

Rs. 30,000

⏤ learning path ⏤

Curriculum Excellence

A comprehensive journey — from Python fundamentals to AI model building and career readiness

Python Programming for Data Science

Python basics & data types
Functions, loops & OOP concepts
File handling & libraries
Jupyter Notebook environment

Data Analysis with Pandas & NumPy

DataFrames & Series operations
Data filtering & aggregation
NumPy arrays & math operations
Merging, joining & reshaping data

Data Visualization using Power BI

Power BI Desktop & Service
Interactive dashboards & reports
DAX formulas & calculations
Data storytelling best practices

SQL for Data Analysis

SQL queries, joins & subqueries
Aggregation & window functions
Database design & normalization
Real-world data extraction

Statistics & Mathematics for AI

Probability & distributions
Hypothesis testing & p-values
Linear algebra essentials
Correlation & regression basics

Data Cleaning & Feature Engineering

Handling missing & noisy data
Outlier detection & treatment
Feature scaling & encoding
Feature selection techniques

Machine Learning Fundamentals

Supervised & unsupervised learning
Classification & regression models
Decision trees & random forests
Clustering & dimensionality reduction

Build AI Models using Python

Scikit-learn model pipelines
TensorFlow & Keras basics
Model building end-to-end
Hyperparameter tuning

Model Training, Testing & Evaluation

Train-test split & cross-validation
Accuracy, precision, recall & F1
Confusion matrix & ROC curves
Overfitting & regularization

Deep Learning & Neural Networks

Neural network architecture
CNNs for image recognition
RNNs & sequence models
Transfer learning basics

Predictive Analytics & Real-World AI

Time series forecasting
Recommendation systems
NLP & sentiment analysis
Real-world AI applications

Generative AI & LLMs

Large Language Models overview
ChatGPT & GPT API integration
RAG & vector databases
Building AI-powered applications

AI Model Fine-Tuning & Prompt Engineering

Prompt design & optimization
Fine-tuning pre-trained models
Chain-of-thought prompting
Custom GPT & system prompts

Live Datasets & Industry Projects

Real-world dataset analysis
End-to-end ML project pipeline
Portfolio-ready project work
Model deployment basics

Internship Opportunity

3-month internship program
Work on live company projects
Internship completion certificate
Industry exposure & mentorship

Interview Prep & Placement

Resume & portfolio preparation
Mock interviews & HR rounds
Job referrals & placement support
Career guidance & counselling

Frequently Asked Questions

Quick answers about the Data Science & Analytics Course

No, this course is designed for beginners. We start from Python basics and essential statistics, then progressively build up to Machine Learning, Deep Learning, and Generative AI — all with hands-on practice.

You'll work with Python, Pandas, NumPy, Power BI, SQL, Scikit-learn, TensorFlow, Keras, Jupyter Notebook, ChatGPT API, and more. The course covers everything from data analysis to building and deploying AI models.

Yes! The program includes a 3-month internship opportunity where you work on real industry datasets and projects, plus comprehensive placement assistance including resume building, mock interviews, and job referrals.

Absolutely. You'll work with live datasets, build end-to-end ML pipelines, create predictive models, and develop portfolio-ready projects that demonstrate your skills to employers.

Graduates can pursue roles like Data Analyst, Data Scientist, ML Engineer, AI Creator & Digital Marketing, Business Intelligence Analyst, and Data Engineer across industries like finance, healthcare, e-commerce, and tech.