                    import pandas as pd
                
                    from sklearn.model_selection import train_test_split
                
                    model = RandomForestClassifier(n_estimators=100)

High-Demand Career

Complete Data Science Mastery

Master Data Science from fundamentals to advanced machine learning. Learn Python, statistics, data visualization, and predictive modeling to solve real-world business problems.

4 Months Duration

Live Project Sessions

12+ Real Projects

Data Scientist Certificate

₹24,000 ₹96,000 75% OFF

Enroll Now View Curriculum

Sales Data Analysis

Jan Feb Mar Apr May

Model Accuracy

Accuracy: 94.2%
Precision: 92.8%
Recall: 95.1%
F1-Score: 93.9%

37% annual job growth

Curriculum

Data Science Mastery Curriculum

Complete data science programming from basics to advanced machine learning

Module 1: Python for Data Science

3 Weeks • 15 Hours

Python Fundamentals & Libraries
NumPy for Numerical Computing
Pandas for Data Manipulation
Data Cleaning & Preprocessing
Working with CSV, Excel, JSON
Web Scraping with BeautifulSoup
Project: Data Cleaning Pipeline

Module 2: Statistics & Mathematics

3 Weeks • 15 Hours

Descriptive & Inferential Statistics
Probability Distributions
Hypothesis Testing
Linear Algebra for ML
Calculus for Optimization
Correlation & Regression Analysis
Project: Statistical Analysis Report

Module 3: Data Visualization

2 Weeks • 10 Hours

Matplotlib & Seaborn
Plotly for Interactive Charts
Geospatial Data Visualization
Dashboard Creation
Tableau Fundamentals
Storytelling with Data
Project: Business Dashboard

Module 4: Machine Learning Fundamentals

4 Weeks • 20 Hours

Supervised vs Unsupervised Learning
Linear & Logistic Regression
Decision Trees & Random Forest
SVM, KNN, Naive Bayes
Model Evaluation Metrics
Cross-Validation Techniques
Project: Customer Churn Prediction

Module 5: Advanced ML & Deep Learning

4 Weeks • 20 Hours

Clustering Algorithms
Dimensionality Reduction (PCA)
Neural Networks Basics
TensorFlow & Keras
CNN for Image Processing
NLP Fundamentals
Project: Image Classifier

Module 6: Deployment & Cloud

2 Weeks • 10 Hours

Model Deployment with Flask
Docker for Containerization
AWS/Azure for ML
MLOps Fundamentals
REST APIs for ML Models
CI/CD for Data Science
Capstone: End-to-End ML Pipeline

Applications

Data Science Application Domains

Master data science across multiple industries

E-commerce & Retail

Customer segmentation, recommendation systems, demand forecasting, and price optimization.

Recommendation Forecasting Clustering

Healthcare & Medicine

Disease prediction, medical image analysis, drug discovery, and patient outcome prediction.

Medical Imaging Predictive Models NLP

Finance & Banking

Fraud detection, credit scoring, algorithmic trading, and risk assessment models.

Fraud Detection Risk Analysis Time Series

Automotive & Manufacturing

Predictive maintenance, quality control, supply chain optimization, and autonomous systems.

Predictive Maintenance Computer Vision Optimization

Roadmap

Data Scientist Roadmap

Your path to becoming a professional data scientist

Month 1-2: Foundations

Master Python programming, statistics, and data manipulation. Learn data cleaning, exploratory analysis, and visualization techniques.

Month 3: Machine Learning

Learn supervised and unsupervised algorithms, model evaluation, and feature engineering. Build predictive models.

Month 4: Advanced Topics

Dive into deep learning, NLP, and big data technologies. Work with TensorFlow and cloud platforms.

Month 5: Projects & Deployment

Build portfolio projects, learn model deployment, and master data storytelling. Prepare for interviews.

Projects

Real-World Data Science Projects

Build portfolio-worthy projects during the course

Customer Churn Prediction

Predict which customers are likely to leave a subscription service using machine learning algorithms and recommend retention strategies.

Python Scikit-learn Pandas Flask

Sentiment Analysis System

Build an NLP system that analyzes customer reviews and social media posts to determine sentiment and extract key insights.

NLP TensorFlow NLTK FastAPI

House Price Prediction

Create a regression model that predicts house prices based on features like location, size, and amenities with high accuracy.

Regression Feature Engineering XGBoost Streamlit

Tools

Essential Data Science Tools

Master the industry-standard tools for data science

Python

The most popular programming language for data science with extensive libraries for ML and analytics.

Industry Standard • 75% Usage

SQL

Essential for data extraction, transformation, and working with relational databases in production environments.

Essential • 90% Usage

TensorFlow

Google's open-source library for numerical computation and large-scale machine learning.

Deep Learning • 40% Usage

AWS/Azure

Cloud platforms for scalable data processing, model training, and deployment of ML solutions.

Cloud • 60% Usage

Algorithms

Machine Learning Algorithms

Master essential algorithms for real-world applications

Random Forest

Ensemble learning method that operates by constructing multiple decision trees for classification and regression.

Supervised Learning

Neural Networks

Computational models inspired by biological neural networks, capable of learning complex patterns.

Deep Learning

Linear Regression

Statistical method that models the relationship between a dependent variable and one or more independent variables.

Regression

K-Means Clustering

Unsupervised learning algorithm that partitions data into K distinct clusters based on feature similarity.

Clustering

Comparison

Data Science vs Traditional Roles

How data science differs from traditional IT roles

Role Primary Focus Key Skills Salary Range Growth Outlook Data Scientist Predictive Modeling ML, Statistics, Python ₹8-25 LPA 37% Growth Data Analyst Descriptive Analytics SQL, Excel, Visualization ₹5-15 LPA 25% Growth ML Engineer Model Deployment MLOps, Cloud, DevOps ₹10-30 LPA 40% Growth Business Analyst Business Insights Requirements, Domain ₹6-18 LPA 20% Growth Data Engineer Data Pipelines Big Data, ETL, Cloud ₹9-22 LPA 32% Growth

Careers

Data Science Career Pathways

High-demand roles for data science professionals

Data Scientist

₹8-25 LPA

Build predictive models and extract insights from complex data

ML Engineer

₹10-30 LPA

Deploy and maintain machine learning models in production

Data Engineer

₹9-22 LPA

Design and build data pipelines and infrastructure

Data Analyst

₹5-15 LPA

Analyze data to provide business insights and reports

Requirements

Prerequisites & Certification

What you need and what you'll achieve

Basic Programming

Understanding of any programming language (Python basics will be covered)

Mathematical Aptitude

Basic understanding of mathematics (concepts will be taught from scratch)

Analytical Thinking

Ability to think logically and solve problems systematically

Certification

Receive Data Science Professional certificate upon completion

Industry Recognized