Course Curriculum

📘 Module 1: Data Science Foundation

What is Data Science & AI? 

Role of a Data Scientist in Industry 

Understanding Data Types & Data Lifecycle 

Business Applications of Data Science 

📊 Module 2: Excel for Data Analysis

Advanced Excel for Data Handling 

Data Cleaning & Formatting 

Pivot Tables & Dashboards 

Data Visualization using Excel 

🐍 Module 3: Python for Data Science

Python Basics (Variables, Loops, Functions) 

Working with Libraries: NumPy, Pandas 

Data Cleaning & Manipulation 

File Handling (CSV, Excel, JSON) 

📈 Module 4: Data Visualization

Visualization using Matplotlib & Seaborn 

Creating Business Dashboards 

Storytelling with Data 

Real-life Case Studies 

🧠 Module 5: Statistics for Data Science

Descriptive Statistics 

Probability Concepts 

Hypothesis Testing 

Correlation & Regression Basics 

🤖 Module 6: Machine Learning Fundamentals

Introduction to Machine Learning 

Supervised vs Unsupervised Learning 

Regression & Classification Models 

Model Training & Evaluation 

⚙️ Module 7: AI Tools & Automation

Using AI Tools for Data Analysis 

ChatGPT for Data Science Tasks 

Automation of Data Workflows 

Prompt Engineering for Data Experts 

🗄️ Module 8: SQL & Database Management

Introduction to Databases 

Writing SQL Queries 

Data Extraction & Filtering 

Joins, Group By & Aggregations 

📊 Module 9: Power BI / Tableau

Business Intelligence Concepts 

Creating Interactive Dashboards 

Data Reporting & Insights 

Real Business Use Cases 

🧩 Module 10: Real-World Projects

Sales Forecasting Project 

Customer Segmentation Project 

Marketing Data Analysis 

Financial Data Insights Project 

💼 Module 11: Career & Placement Preparation

Resume Building for Data Science 

LinkedIn Optimization 

GitHub Portfolio Creation 

Interview Questions & Mock Interviews 

🎯 Module 12: Freelancing & Earning with Data Science

How to Get Freelance Projects 

Platforms: Upwork, Fiverr 

Client Communication 

Pricing & Proposal Strategy