4 Sections
13 Lessons
41 Weeks
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Module 6: Object-Oriented Programming
5
1.0
Introduction to OOP concepts: Building a simple class to model a real-life library with books and members.
1.1
Defining classes and creating objects: Implementing a class for a student that tracks their name, age, and grades.
1.2
Attributes and methods: Adding functionality to the student class to calculate average grades and age category.
1.3
Inheritance and polymorphism: Extending the student class to handle different types of students like high school and university students.
1.4
Encapsulation and abstraction: Designing a class that hides complex calculations but provides an easy method to get results.
Module 7: Data Handling with NumPy and Pandas
4
2.0
Introduction to NumPy library: Using NumPy arrays to simulate a classroom seating chart.
2.1
NumPy arrays: Performing operations to manipulate grades of a class of students.
2.2
Introduction to Pandas library: Exploring Pandas to analyze data from a school sports day event.
2.3
Data structures: Using Series and DataFrames to manage and analyze a library’s book checkout data.
Module 8: Data Visualization with Matplotlib
3
3.0
Introduction to Matplotlib library: Visualizing the trend of scores in different subjects throughout the school year.
3.1
Drawing basic plots: Creating bar graphs to compare the performance of classes in a sports meet.
3.2
Customizing plots: Enhancing visualizations with labels, titles, and custom colors to represent different school houses.
Module 9 : Projects
1
4.0
Students work on a small project applying the concepts learned throughout the course. Example projects could include a personalized school management system, a simple data analysis of local weather patterns, or a graphical representation of community survey results.
Advanced Python
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