Python programming, data structures, Matplotlib, Seaborn, data storytelling.
Unit 1 — Python Programming — OOP, Modules and Libraries
6 classes
1.1 Understand Object-Oriented Programming Concepts in Python
1.2 Create Classes and Objects in Python
1.3 Implement Inheritance and Polymorphism in Python
1.4 Explore Python Modules: Importing and Utilizing Libraries
1.5 Develop a Simple Project Using Custom Modules
1.6 Apply Data Visualization Techniques with Python Libraries
Unit 2 — Data Structures — Lists, Dicts, DataFrames (pandas)
6 classes
2.1 Understand the Basics of Lists in Python
2.2 Manipulate Lists: Adding, Removing, and Sorting Elements
2.3 Introduction to Dictionaries: Key-Value Pairs in Python
2.4 Explore and Modify Dictionaries: Accessing and Updating Values
2.5 Introduction to DataFrames using pandas Library
2.6 Data Analysis with DataFrames: Filtering and Visualizing Data
Unit 3 — Data Visualisation — Matplotlib, Seaborn, Plotly
6 classes
3.1 Understand the Basics of Data Visualization with Matplotlib
3.2 Create Your First Line Plot Using Matplotlib
3.3 Explore Data Distribution with Seaborn's Histogram and Box Plot
3.4 Enhance Visual Appeal with Seaborn Themes and Color Palettes
3.5 Build Interactive Visualizations Using Plotly
3.6 Apply Data Visualization Techniques to Real-World Data Sets
Unit 4 — Statistical Analysis and Hypothesis Testing in Python
6 classes
4.1 Understand Key Statistical Concepts in Python
4.2 Explore Descriptive Statistics Using Python Libraries
4.3 Visualize Data Distributions with Histograms and Boxplots
4.4 Formulate Hypotheses for Statistical Testing
4.5 Conduct Hypothesis Tests Using SciPy in Python
4.6 Interpret and Report Statistical Findings Effectively
Unit 5 — Data Visualisation Project — Dashboard and Storytelling
6 classes
5.1 Understand the Principles of Effective Data Visualization
5.2 Explore Python Libraries for Data Visualization
5.3 Design an Interactive Dashboard Layout
5.4 Implement Data Source Connections in Python
5.5 Craft a Narrative Using Visual Storytelling Techniques
5.6 Present and Evaluate Your Data Visualization Project