Python Programming for Data Analysis
A comprehensive curriculum designed to take you from basics to professional data Analytics.
1
Module 1
Python Foundations
Build a strong base in Python programming.
Python installation and environment setup (Anaconda, VS Code, Jupyter Notebook)
Python syntax and structure, Variables, data types, and operators
Input and output operations
Control flow: Conditional statements (if, elif, else), Loops (for, while)
Functions and reusable code, Modules and packages
Error handling and debugging using exceptions
2
Module 2
Core Python Data Structures
Master how data is stored and manipulated in Python.
Lists, Tuples, Sets, and Dictionaries
Indexing and slicing
Iteration through collections
String manipulation and formatting
Practical exercises on real-world data structures
3
Module 3
Numerical Computing with NumPy
Perform fast and efficient numerical operations.
Introduction to NumPy, Creating and manipulating NumPy arrays
Indexing, slicing, and reshaping
Mathematical and statistical operations
Working with multi-dimensional arrays
4
Module 4
Data Analysis with Pandas
Analyze and process real-world datasets.
Introduction to Pandas: Series, DataFrames
Loading and saving data (CSV, Excel, JSON)
Data cleaning and preprocessing
Filtering, sorting, and grouping data
Merging, joining, and concatenating datasets
Descriptive statistics and data summarization
5
Module 5
Data Visualization with Matplotlib
Convert data into meaningful visual insights.
Introduction to data visualization
Line charts, bar charts, histograms, and scatter plots
Plot customization (labels, legends, colors, titles)
Visualizing trends and patterns in datasets
6
Module 6
Practical Data Analysis Projects
Apply everything you learn through hands-on projects.
Exploratory Data Analysis (EDA)
Sales data analysis
Stock price visualization
Customer behavior analysis
Mini capstone project using NumPy, Pandas, and Matplotlib
7
Module 7
Practical Data Analysis Projects
Apply everything you learn through hands-on projects.
Exploratory Data Analysis (EDA)
Sales data analysis
Stock price visualization
Customer behavior analysis
Mini capstone project using NumPy, Pandas, and Matplotlib
8
Module 8
Career Skills & Next Steps
Prepare for advanced analytics and data science roles.
Preparing datasets for Machine Learning
Best practices for data analysis in Python
Introduction to Data Science and AI workflows
Career roadmap: Data Analyst → Data Scientist → Machine Learning Engineer
Portfolio and project guidance