The Course Curriculum

Module 1: Introduction to Python Programming

• Overview of Python: history, features, and applications
• Installing Python and setting up the development environment
• Basics of Python syntax: variables, data types, operators, and expressions

Module 2: Control Flow and Functions

• Conditional statements: if, elif, else
• Looping constructs: for loops, while loops
• Writing functions in Python: defining functions, arguments, return values

Module 3: Data Structures in Python

• Lists, tuples, and dictionaries
• Understanding sets and their operations
• List comprehensions and generator expressions

Module 4: File Handling and Error Handling

• Reading from and writing to files
• Handling exceptions: try-except blocks, raising exceptions
• Context managers and the 'with' statement

Module 5: Object-Oriented Programming (OOP) in Python

• Introduction to OOP concepts: classes, objects, methods, and attributes
• Encapsulation, inheritance, and polymorphism
• Advanced OOP features: class methods, static methods, properties

Module 6: Advanced Python Techniques

• Decorators and closures
• Generators and iterators
• Working with modules and packages

Module 7: Introduction to NumPy

• Overview of NumPy and its advantages
• Creating NumPy arrays: arrays vs. lists
• Indexing and slicing arrays

Module 8: Array Operations with NumPy

• Performing mathematical operations on arrays
• Broadcasting and vectorized operations
• Array manipulation and reshaping

Module 9: Introduction to Pandas

• Introduction to Pandas: Series and DataFrames
• Loading and exploring data with Pandas
• Indexing and selecting data in DataFrames

Module 10: Data Manipulation with Pandas

• Working with missing data: handling null values
• Data cleaning and preprocessing techniques
• Combining and merging DataFrames

Module 11: Data Visualization with Matplotlib

• Introduction to Matplotlib: basic plots and customization
• Creating line plots, scatter plots, bar plots, and histograms
• Adding titles, labels, and legends to plots

Module 12: Advanced Visualization with Seaborn

• Introduction to Seaborn: enhancing data visualization
• Creating advanced plots: pair plots, heatmaps, violin plots
• Customizing aesthetics and styles in Seaborn

Module 13: Interactive Visualization with Plotly

• Overview of Plotly: creating interactive plots and dashboards
• Building line charts, scatter plots, and bar charts with Plotly
• Adding interactivity and annotations to Plotly visualizations

Module 14: Real-World Data Analysis Project

• Applying Python programming and data analysis skills to a real-world dataset
• Data exploration, visualization, and analysis using Pandas, NumPy, and visualization libraries
• Presenting findings and insights from the analysis

Module 15: Best Practices and Tips for Python Programming

• Writing clean and efficient Python code
• Code optimization techniques and performance tuning
• Documenting code and following PEP 8 guidelines