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Data Science + Artificial Intelligence

Master Data.
Build Intelligent Solutions.
Become Industry Ready.

Learn Data Science and Artificial Intelligence through Python, statistics, SQL, data visualization, machine learning, generative AI, and real-world projects. Build the skills to turn raw data into insights, predictions, and intelligent applications.

Enroll in Data Science + AI →Explore Curriculum
6–9 MonthsDuration
Beginner → AdvancedLevel
12+Projects
2Capstones
COURSE FEE
₹1,00,000
data_science.py
01import pandas as pd
02import numpy as np
03model = train_model(data)
04prediction = model.predict(X)
05await ai.generate(prompt)
06<DeployAI />
07"Data. Model. Intelligence."
🐍 Python + Data⚙ Machine Learning✦ Generative AI
The complete data stack

Why Data Science + AI?

Modern organizations need professionals who can understand data, build predictive models, and apply AI to solve real business problems.

01
◫

Python

Build your data foundation.

02
∑

Statistics

Understand patterns and uncertainty.

03
◉

Data Analytics

Turn raw data into insights.

04
↗

Machine Learning

Build predictive solutions.

05
✦

Artificial Intelligence

Create intelligent applications.

06
⇄

Deployment

Take models into production.

Skill builder

What You'll Learn

Python Programming

Build strong programming and problem-solving fundamentals.

NumPy & Pandas

Manipulate, transform, analyze, and prepare real datasets.

SQL & Databases

Query business data using joins, aggregations, subqueries, and more.

Statistics & Probability

Understand distributions, hypothesis testing, correlation, and inference.

Data Cleaning & EDA

Find patterns, handle missing values, detect outliers, and explore data.

Data Visualization

Create meaningful dashboards and stories using modern visualization tools.

Power BI

Build interactive business dashboards and decision-ready reports.

Machine Learning

Train supervised and unsupervised models for real-world problems.

Feature Engineering

Prepare better model inputs and improve predictive performance.

Model Evaluation

Measure, compare, tune, and validate machine learning models.

Generative AI

Understand LLMs, prompting, embeddings, and AI application workflows.

RAG & AI Applications

Build knowledge-grounded AI systems using retrieval and vector search.

Your toolkit

Tools & Technologies

Work with technologies used across the modern Data Science, ML, analytics, and AI workflow.

Programming

PYPythonJUJupyterGIGitGHGitHub

Data Science

NUNumPyPAPandasSKScikit-learnMAMatplotlibSESeaborn

Analytics & BI

SQSQLPBPower BIDAData StorytellingEXExcel

Machine Learning

SKScikit-learnMLRegressionCLClassificationCLClustering

AI & GenAI

LLLLMsPEPrompt EngineeringEMEmbeddingsRGRAGVDVector Databases
12 modules

Course Curriculum

Learn the complete Data Science and AI lifecycle from fundamentals to intelligent applications.

01Python FundamentalsView module+
  • Python syntax & data types
  • Conditions & loops
  • Functions
  • Lists, tuples & dictionaries
  • Object-oriented basics
  • File handling
  • Error handling
BuildPython problem-solving projects
02NumPy & PandasView module+
  • NumPy arrays
  • Vectorized operations
  • Series & DataFrames
  • Filtering & sorting
  • GroupBy & aggregation
  • Merge & join datasets
  • Data transformation
BuildReal-world data analysis notebook
03SQL & Data ManagementView module+
  • SELECT, WHERE & ORDER BY
  • Joins
  • GROUP BY & HAVING
  • Subqueries
  • CTEs
  • Window functions
  • Database design basics
BuildBusiness analytics SQL project
04Statistics & ProbabilityView module+
  • Descriptive statistics
  • Probability fundamentals
  • Distributions
  • Sampling
  • Correlation & covariance
  • Hypothesis testing
  • Confidence intervals
  • A/B testing fundamentals
BuildStatistical analysis case study
05Data Cleaning & EDAView module+
  • Missing values
  • Duplicates
  • Outlier detection
  • Data types
  • Feature distributions
  • Univariate & bivariate analysis
  • EDA workflow
BuildEnd-to-end EDA project
06Data Visualization & Power BIView module+
  • Matplotlib & Seaborn
  • Chart selection
  • Dashboard principles
  • Power BI basics
  • Data modeling
  • DAX fundamentals
  • Interactive dashboards
  • Business storytelling
BuildExecutive business intelligence dashboard
07Machine Learning FundamentalsView module+
  • ML workflow
  • Train-test split
  • Linear & logistic regression
  • Decision trees
  • Random forests
  • KNN
  • Classification & regression
BuildPredictive machine learning application
08Advanced Machine LearningView module+
  • Feature engineering
  • Feature selection
  • Hyperparameter tuning
  • Cross-validation
  • Model comparison
  • Clustering
  • PCA fundamentals
  • Model interpretability
BuildCustomer segmentation + prediction project
09AI FundamentalsView module+
  • AI vs ML vs Deep Learning
  • Neural network concepts
  • AI use cases
  • Model lifecycle
  • AI ethics & responsible AI
  • Intelligent automation
BuildAI-powered business use-case prototype
10Generative AI & LLMsView module+
  • Generative AI concepts
  • LLM fundamentals
  • Prompt engineering
  • System & user prompts
  • Structured outputs
  • Embeddings
  • Vector search
BuildLLM-powered AI assistant
11RAG & AI ApplicationsView module+
  • Retrieval-augmented generation
  • Document ingestion
  • Chunking & embeddings
  • Vector databases
  • Retrieval workflows
  • Grounded responses
  • AI application architecture
BuildKnowledge-base RAG application
12Deployment & CareerView module+
  • Model packaging
  • API deployment concepts
  • Environment management
  • Git & GitHub workflow
  • Portfolio development
  • Resume optimization
  • Technical interview preparation
  • Mock interviews
BuildProduction-ready Data Science + AI portfolio
Build while learning

Projects You'll Build

Practical projects turn concepts into a portfolio you can actually showcase.

PROJECT 01

Sales Analytics Dashboard

Analyze business sales data and create an interactive decision-making dashboard.

SQL · Python · Pandas · Power BI
PROJECT 02

Customer Churn Prediction

Build a machine learning model to identify customers at risk of churn.

Python · Pandas · Scikit-learn
PROJECT 03

Customer Segmentation

Use clustering techniques to identify meaningful customer groups.

Python · EDA · K-Means · Visualization
PROJECT 04

Demand Forecasting

Analyze historical business data and build a predictive forecasting workflow.

Python · Statistics · Machine Learning
PROJECT 05

AI Document Assistant

Build an AI assistant that answers questions from uploaded business documents.

Python · LLM · Embeddings · RAG
PROJECT 06

AI Business Insights

Combine analytics and generative AI to turn business data into useful insights.

Python · SQL · Power BI · GenAI
Go beyond the basics

Capstone Projects

Two substantial applications bring Data Science, Machine Learning, analytics, and AI together.

CAPSTONE 01

End-to-End Business Intelligence & ML Platform

Build a complete data solution that moves from raw business data to dashboards and predictive insights.

✓ Data ingestion✓ SQL analytics✓ Data cleaning✓ EDA✓ Power BI dashboard✓ Feature engineering✓ ML prediction✓ Model evaluation✓ Business insights✓ Deployment workflow
STACK · Python · SQL · Pandas · Scikit-learn · Power BI
CAPSTONE 02

Generative AI Knowledge Assistant

Build a grounded AI application that retrieves information from a knowledge base and generates useful responses.

✓ Document ingestion✓ Text chunking✓ Embeddings✓ Vector search✓ RAG pipeline✓ Prompt engineering✓ Context retrieval✓ Response generation✓ Evaluation✓ AI application deployment
STACK · Python · LLM · Embeddings · Vector DB · RAG
From raw data to intelligence

Your Learning Journey

01

Learn

Build Python, SQL, statistics, and data fundamentals.

02

Analyze

Clean datasets, explore patterns, and communicate insights.

03

Model

Train and evaluate machine learning models.

04

Build

Create AI and Generative AI applications.

05

Deploy

Move analytics and intelligent solutions toward production.

06

Showcase

Build a portfolio that demonstrates real data and AI skills.

More than a curriculum

What You Get

01

Structured Learning

A clear path from Python fundamentals to Data Science and AI.

02

Hands-On Projects

Learn through practical analytics, ML, and AI applications.

03

12+ Projects

Build a portfolio across analytics, machine learning, and AI.

04

2 Capstone Applications

Develop substantial projects that bring the complete workflow together.

05

Mentorship & Guidance

Get support throughout your learning and project journey.

06

Career Preparation

Prepare your portfolio, resume, LinkedIn, GitHub, and interviews.

Who can join

Who Is This Course For?

Beginners

Start Data Science and AI from the fundamentals.

College Students

Build industry-relevant data and AI skills alongside your degree.

Graduates

Bridge the gap between academics and practical data work.

Career Switchers

Follow a structured path into analytics, ML, and AI roles.

Working Professionals

Add modern analytics and AI capabilities to your profile.

Start from zero

Prerequisites

No advanced programming or mathematics knowledge is required. We'll take you from fundamentals to practical Data Science and AI step by step.

✓Basic computer knowledge
✓A laptop or desktop
✓Willingness to learn
✓Consistent practice
✓Commitment to building projects
Where it can lead

Career Paths

Your career outcome depends on your skills, portfolio, experience, and interview performance.

Data Analyst ↗Business Analyst ↗Data Scientist ↗Machine Learning Engineer ↗AI Engineer ↗BI Developer ↗GenAI Developer ↗
Questions, answered

Frequently Asked Questions

Is this course beginner-friendly?+
Yes. The course starts with Python, SQL, statistics, and data fundamentals before moving into machine learning and AI.
Do I need a CS or mathematics degree?+
No. A CS or mathematics degree is not required. The required concepts are taught progressively.
Will I learn both Data Science and AI?+
Yes. The curriculum covers analytics, machine learning, AI fundamentals, Generative AI, LLMs, embeddings, and RAG.
Will I build real projects?+
Yes. Projects are integrated throughout the curriculum, including two major capstone applications.
Will I learn Power BI and SQL?+
Yes. SQL and business intelligence are included so you can work with real business data and communicate insights effectively.
Will I learn Generative AI and RAG?+
Yes. You'll learn LLM fundamentals, prompt engineering, embeddings, vector search, and RAG application workflows.
Is placement guaranteed?+
IT Pratha focuses on technical skill development and career preparation. Employment cannot be guaranteed because hiring depends on the candidate, employer, market conditions, and interview performance.
Your next chapter starts here

Don't Just Analyze Data.
Build Intelligence.

Develop practical skills to analyze data, build predictive models, create AI applications, and take your first step toward a career in Data Science and Artificial Intelligence.

Enroll in Data Science + AI →Explore Other Courses →