Module 1: Introduction to Data Science
● Introduction to Data Science
● Applications & Career Opportunities
● Data Science Workflow

Module 2: Python for Data Science
● Python, PyCharm & Anaconda Installation
● Introduction to Jupyter Notebook
● Variables in Python
● Data Types in Python
● Operators in Python
● Python Tokens: Keywords, Identifiers, Literals & Operators
● Data Structures in Python: Tuple, List, Dictionary & Set
● Flow Control Statements
● Functions in Python
● Python Object-Oriented Programming: Class & Object
● Inheritance in Python

Module 3: SQL for Data Science
Basic SQL Concepts
● Introduction to SQL and Basic Queries
● Understanding RDBMS & Database Normalization
● SELECT Statement, WHERE Clause, ORDER BY Advanced SQL Operations
● Join Types: Inner, Left, Right, Full
● UNION, INTERSECT, EXCEPT

Module 4: Data Analysis with NumPy & Pandas
● Introduction to Python Libraries for Data Science
● Python NumPy
● Python Pandas

Module 5: Data Visualization
● Data Visualization with Matplotlib
● Data Visualization with Seaborn

Module 6: Data Analysis Projects
● Project 1: (Hands-on project with real data)
● Project 2: (Advanced case study)

Module 7: Machine Learning
● Supervised Learning
● Unsupervised Learning

Module 8: Statistics for Data Science
● Descriptive & Inferential Statistics
● Probability & Distributions

Module 9: Machine Learning Algorithms
● Linear Regression
● Logistic Regression
● Time Series Analysis

Module 10: Data Science Career
● Job Type
● Freelancing