DATA SCIENCE

★★★★★

(2,095 ratings) 50,000+ Student

DATA SCIENCE AND MACHINE LEARNING USING PYTHON

Data Science and Machine Learning with Python is a field of study and practice that combines data analysis, statistical modeling, and machine learning techniques using the Python programming language. Data Science and Machine Learning with Python involve the use of Python programming along with statistical analysis and machine learning techniques to extract insights, build predictive models, and solve complex data-related problems across various domains, including finance, healthcare, marketing, and more.

Radical Technologies

50,000+ English 60 hours Weekdays / Weekends Classroom / Online / Corporate

Online / Classroom

IT Training Programme

Duration 60 hours

Batch Type Weekdays / Weekends

Mode of Training Classroom / Online / Corporate

Locations Pune, Bangalore, Kochi

Language English

Certification Globally Recognized

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100% placement assistance

What you'll learn

Understand core concepts and architecture from the ground up

Get hands-on with the tools used by working professionals

Build real-world projects you can add to your portfolio

Learn industry best practices and coding standards

Practice with real datasets and real-world scenarios

Prepare for certification and technical interviews

Work on collaborative, team-based exercises

Apply performance tuning and optimization techniques

Understand how the technology fits into a larger ecosystem

Complete assignments reviewed by mentors

Programme Overview

23 sections covering the complete curriculum — a single, progressive learning arc.

60 hours

Training Duration

Core Modules

289

Total Lessons

4.4★

Average Rating

50K+

Students Trained

Foundations & Core Concepts

Get hands-on with the fundamentals and architecture — the building blocks for everything that follows.

Fundamentals Architecture Setup

Hands-On Practical Training

Work through real exercises and assignments designed to mirror what you will do on the job.

Practicals Assignments Labs

Real-World Projects

Apply what you have learned to end-to-end projects that go straight into your portfolio.

Projects Portfolio Case Studies

Advanced Techniques

Go beyond the basics with advanced concepts, integrations and production-grade practices.

Advanced Integration Best Practices

Ecosystem Integration

Understand how this technology connects with the broader tools and platforms used in the industry.

Ecosystem Tools Platforms

Performance & Interview Prep

Master optimization techniques and prepare for the technical interview questions employers actually ask.

Optimization Interview Prep Certification

Who is this programme for?

Whether you're already writing code, working with data, or supporting applications today — this programme is built to take you into a DATA SCIENCE role.

Software Developers

Engineers who want to add this skill set to their toolkit

Analysts & Consultants

Professionals moving into a more technical, hands-on role

IT Professionals

System admins and support engineers upskilling into a new domain

Fresh Graduates

CS/IT graduates aiming for a job-ready technical role

Course Curriculum

23 sections • 289 lessons • 60 hours

Jump to Section

Total Duration

60 hours

100% Practical · Unlimited Doubt Sessions

01 Module 1: Introduction to Data Science & AI

Topics

What is Data Science?

Data Science Lifecycle

Data Analytics vs Data Science vs AI vs Machine Learning

Applications of Data Science

CRISP-DM Methodology

Data Science Project Lifecycle

Industry Use Cases

Data Science Roles and Responsibilities

AI and Generative AI Fundamentals

Data Science Career Roadmap

Assignments

›Analyze Data Science Use Cases Across Industries
›Research AI Applications in Healthcare and Banking

Job-Oriented Scenarios

›Customer Churn Prediction Requirements Gathering
›Business Problem to Data Science Solution Mapping

02 Module 2: Python Programming Fundamentals

Topics

Python Installation and Setup

Jupyter Notebook

Python Syntax

Variables and Data Types

Operators

Conditional Statements

Loops

Functions

Modules and Packages

Exception Handling

File Handling

Object-Oriented Programming

Lambda Functions

Iterators and Generators

List Comprehensions

Labs

Employee Management System

Student Record Processing

Assignments

›Banking Transaction Processing
›Inventory Management System

Job-Oriented Scenarios

›Data Processing Automation
›Log File Analysis
›

03 Module 3: Python Libraries for Data Science

Topics

NumPy

Arrays

Vectorization

Broadcasting

Mathematical Operations

Linear Algebra

Pandas

DataFrames

Series

Data Cleaning

Data Transformation

GroupBy

Merge & Join

Pivot Tables

Matplotlib

Line Charts

Bar Charts

Histograms

Scatter Plots

Seaborn

Heatmaps

Pairplots

Distribution Analysis

Labs

Sales Data Analysis

Assignments

›Employee Attrition Analysis

Job-Oriented Scenarios

›Data Cleaning of Enterprise Datasets
›

04 Module 4: SQL for Data Science

Topics

Database Fundamentals

SQL Queries

Filtering

Joins

Aggregations

Subqueries

Window Functions

CTEs

Stored Procedures

Views

Labs

Customer Database Analysis

Assignments

›Retail Data Analytics

Job-Oriented Scenarios

›Data Extraction from Data Warehouses

05 Module 5: Exploratory Data Analysis (EDA)

Topics

Data Profiling

Missing Value Treatment

Outlier Detection

Correlation Analysis

Feature Understanding

Statistical Summaries

Data Visualization Techniques

Business Insights Extraction

Labs

Loan Dataset Analysis

Assignments

›E-Commerce Sales Analysis

Job-Oriented Scenarios

›Customer Segmentation Analysis

06 Module 6: Statistics for Data Science

Topics

Descriptive Statistics

Probability Theory

Probability Distributions

Normal Distribution

Central Limit Theorem

Hypothesis Testing

Confidence Intervals

Correlation

Covariance

Chi-Square Test

ANOVA

A/B Testing

Labs

Marketing Campaign Analysis

Assignments

Customer Behavior Analysis

Job-Oriented Scenarios

›Product Performance Testing

07 Module 7: Machine Learning Fundamentals

Topics

Introduction to Machine Learning

Supervised Learning

Unsupervised Learning

Reinforcement Learning

Training and Testing Data

Bias and Variance

Model Evaluation

Cross Validation

Feature Engineering

Model Deployment Concepts

Assignments

›Predict Customer Purchases

Job-Oriented Scenarios

›Build Prediction Models for Business Decisions

08 Module 8: Data Preprocessing & Feature Engineering

Topics

Data Cleaning

Missing Value Handling

Outlier Treatment

Feature Scaling

Encoding Techniques

Feature Selection

Dimensionality Reduction

Data Transformation

SMOTE

Data Balancing

Labs

Insurance Dataset Preparation

Assignments

›Banking Dataset Feature Engineering

09 Module 9: Supervised Machine Learning

Topics

Regression Algorithms

Linear Regression

Multiple Regression

Ridge Regression

Lasso Regression

Polynomial Regression

Classification Algorithms

Logistic Regression

KNN

Naive Bayes

Decision Trees

Random Forest

Support Vector Machines

Labs

House Price Prediction

Customer Churn Prediction

Assignments

›Credit Risk Analysis

Job-Oriented Scenarios

›Loan Approval Prediction
›Insurance Claim Prediction

10 Module 10: Ensemble Learning

Topics

Bagging

Boosting

Random Forest

AdaBoost

Gradient Boosting

XGBoost

LightGBM

CatBoost

Stacking

Labs

Fraud Detection

Assignments

›Telecom Churn Prediction

11 Module 11: Unsupervised Learning

Topics

Clustering Fundamentals

K-Means Clustering

Hierarchical Clustering

DBSCAN

PCA

Market Basket Analysis

Association Rule Mining

Labs

Customer Segmentation

Assignments

›Retail Product Recommendations

Job-Oriented Scenarios

›Customer Behavior Analysis

12 Module 12: Time Series Analysis

Topics

Time Series Fundamentals

Trend Analysis

Seasonality

ARIMA

SARIMA

Prophet

Forecasting Techniques

Labs

Sales Forecasting

Assignments

›Stock Price Analysis

Job-Oriented Scenarios

›Demand Forecasting

13 Module 13: Natural Language Processing (NLP)

Topics

Text Processing

Tokenization

Stemming

Lemmatization

TF-IDF

Word Embeddings

Sentiment Analysis

Text Classification

Topic Modeling

Labs

Sentiment Analysis Project

Assignments

›Social Media Analytics

Job-Oriented Scenarios

›Customer Feedback Analysis

14 Module 14: Deep Learning Fundamentals

Topics

Neural Networks

Perceptrons

Activation Functions

Backpropagation

TensorFlow

Keras

PyTorch Introduction

Model Optimization

Labs

Image Classification

Assignments

›Handwritten Digit Recognition

15 Module 15: Computer Vision

Topics

Image Processing

OpenCV

CNN Fundamentals

Object Detection

Face Detection

Image Classification

Transfer Learning

Labs

Face Recognition System

Assignments

›Defect Detection System

16 Module 16: Generative AI & LLM Fundamentals

Topics

Introduction to Generative AI

Large Language Models

Transformers

Prompt Engineering

RAG Architecture

Vector Databases

LangChain

AI Agents

Fine-Tuning Concepts

Labs

AI Chatbot Development

Assignments

›Document Search Assistant

Job-Oriented Scenarios

›Enterprise AI Assistant

17 Module 17: MLOps

Topics

ML Lifecycle

Model Versioning

MLflow

DVC

Docker for ML

Kubernetes Basics

CI/CD for ML

Monitoring Models

Model Retraining

Labs

ML Deployment Pipeline

Assignments

›End-to-End MLOps Project

18 Module 18: Model Deployment

Topics

Flask

FastAPI

REST APIs

Docker Containers

Cloud Deployment

Azure ML

AWS SageMaker

GCP Vertex AI

Labs

Deploy ML API

Assignments

›Production Deployment

19 Module 19: Data Visualization & BI

Topics

Power BI Integration

Tableau Fundamentals

Dashboard Design

KPI Reporting

Storytelling with Data

Labs

Executive Dashboard

Assignments

›Sales Analytics Dashboard

20 Module 20: Capstone Projects

Project 1

Customer Churn Prediction System

Project 2

Loan Approval Prediction Engine

Project 3

Fraud Detection System

Project 4

Retail Recommendation Engine

Project 5

Stock Market Prediction Platform

Project 6

Healthcare Disease Prediction System

Project 7

Sentiment Analysis Platform

Project 8

AI-Powered Resume Screening System

Project 9

Customer Segmentation Platform

Project 10

Generative AI Enterprise Chatbot

Project 11

Predictive Maintenance System

Project 12

End-to-End MLOps Deployment Project

21 Real-Time Job-Oriented Scenarios

Data Analyst Scenarios

›50 SQL Analysis Scenarios
›50 EDA Scenarios
›30 Dashboard Scenarios

Data Scientist Scenarios

›100 Predictive Modeling Scenarios
›50 Feature Engineering Scenarios
›50 Statistical Analysis Scenarios

Machine Learning Engineer Scenarios

›75 Model Development Scenarios
›50 Model Optimization Scenarios
›30 Deployment Scenarios

AI Engineer Scenarios

›50 NLP Scenarios
›30 Computer Vision Scenarios
›30 Generative AI Scenarios
›20 Agentic AI Scenarios

MLOps Scenarios

›30 MLflow Scenarios
›25 Docker Scenarios
›25 Kubernetes Scenarios
›20 CI/CD Scenarios

22 Interview Preparation

Data Science

500+ Data Science Interview Questions

Machine Learning

500+ Machine Learning Interview Questions

Python

300+ Python Coding Questions

SQL

300+ SQL Interview Questions

AI & Generative AI

200+ LLM and GenAI Questions

Mock Interviews

HR Interview Preparation

Technical Interviews

Case Study Discussions

Resume Building Workshops

23 Recommended Certifications

Microsoft Certified: Azure Data Scientist Associate

AWS Certified Machine Learning Engineer – Associate

Google Professional Machine Learning Engineer

TensorFlow Developer Certificate

Databricks Certified Machine Learning Professional

Tools & Technologies

Every tool listed here is installed, configured and used in a hands-on lab session.

Core Tools

Hands-On Labs

Practical Environment

Industry-Standard Tools

Real-World Setup

Guided Exercises

Skill Building

Sample Datasets

Practice Material

Practice & Projects

Mini Projects

Applied Practice

Assignments

Mentor Reviewed

Doubt Sessions

Live Support

Career Readiness

Resume Building

Career Support

Mock Interviews

Interview Prep

Certification Prep

Global Recognition

Deployment & Delivery

Production Practices

Real-World Ready

Best Practices

Industry Standards

289+

Hands-On Lessons

Core Modules

60 hours

Training Duration

100%

Practical Training

You don't just learn DATA SCIENCE AND MACHINE LEARNING USING PYTHON. You ship it.

Three major projects, each mirroring how production teams actually work — from guided foundations to a portfolio-ready capstone.

PROJECT // 01

Guided Foundation Project

→Requirement Analysis

→Guided Implementation

→Mentor Review

→Iteration

Foundation Beginner

Apply the fundamentals in a structured, mentor-reviewed project

Take the core concepts from the first half of the curriculum and apply them to a realistic scenario, with guidance and feedback from your mentor at every step.

Structured project brief

Step-by-step implementation

Mentor feedback and review

Documented outcome

Stack Core Concepts Best Practices

PROJECT // 02

Applied Practice Project

→Scenario Design

→Independent Build

→Testing & Validation

→Peer Review

Applied Intermediate

Build a more independent project mirroring real production scenarios

Work through a project that combines multiple concepts from the curriculum, closer to how work is actually structured on the job — less hand-holding, more ownership.

End-to-end implementation

Testing and validation

Documentation

Peer/mentor review

Stack Applied Skills Testing

PROJECT // 03

Capstone Project

→Planning

→End-to-End Build

→Review & Refinement

→Presentation

Capstone Advanced

Take a project from requirements to a polished, portfolio-ready deliverable

Your final project — plan, build, test and present a complete solution using everything covered in the curriculum, reviewed by mentors before you graduate.

Complete working solution

Presentation-ready documentation

Mentor sign-off

Portfolio-ready deliverable

Stack Full Curriculum Portfolio

All 3 projects go directly into your portfolio & resume — reviewed by mentors before you graduate.

See Sample Project Reports

Upcoming Batches

No upcoming batches scheduled right now. Enquire to get notified.

Why Radical Technologies

Live Online Training

Highly practical oriented training
Installation support on your system
24/7 Email and Phone support
100% Placement Assistance
Global Certification Preparation
Trainer-Student Interactive Portal
Assignments and Projects by Mentors

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Live Classroom Training

Weekend / Weekdays / Morning / Evening batches
80:20 Practical and Theory ratio
Real-life Case Studies
Easy make-up for missed sessions
PSI | Kryterion | Redhat Test Centers
Lifetime Video Classroom Access (coming soon)
Resume Prep and Mock Interviews

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Self-Paced Training

Learn 300+ courses at your own time
50,000+ Satisfied Learners
Course Completion Certificate
Practical Labs available
Mentor Support available
Doubt Clearing Session available
10% Discounted Global Certification

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Global Certification

Radical Technologies is the leading IT certification institute in Pune, offering globally recognized certifications across various domains. With expert trainers and comprehensive materials, we ensure students gain in-depth knowledge and hands-on experience to excel in their careers. Our certification programs are tailored to meet industry standards — from cloud technologies to data science — empowering individuals to stay ahead in the ever-evolving tech landscape.

Career Services

At Radical Technologies, we are committed to your success beyond the classroom. Our 100% Job Assistance program ensures that you are not only equipped with industry-relevant skills but also guided through the job placement process. With personalised resume building, interview preparation, and access to our extensive network of hiring partners, we help you take the next step confidently into your IT career.