Here's a course syllabus for a 20-hour introductory Python programming course:

Course Overview

This 20-hour course is designed to introduce beginners to Python programming.

By the end of this course, students will have a solid foundation in Python syntax and programming concepts, and be able to create simple programs and applications.

Here's a breakdown of each class:

Class 1: Introduction to Python

• Overview of the course and its objectives
• Explanation of the Python programming language and its uses
• Installation and setup of Python on your computer
• Running your first Python program
• Introduction to Python syntax
• Data types in Python: strings, integers, and floats
• Exercise and homework

Class 2: Data types and variables

• Recap of previous class
• Different types of data in Python: lists, tuples, and dictionaries
• Variables in Python and how they work
• Type conversion in Python
• Manipulating strings in Python
• Exercise and homework

Class 3: Control flow statements

• Recap of previous class
• Conditional statements in Python: if, elif, else
• Loops in Python: for and while loops
• Iteration and range function
• The break and continue statements in loops
• Exercise and homework

Class 4: Error Handling

• Recap of previous class
• Introduction to error handling
• Syntax errors
• Using the try-except block to catch and handle exceptions
• Raising exceptions with the raise statement
• Handling multiple exceptions with the except clause
• Common exceptions and their causes (e.g. NameError, TypeError, ValueError)
• Logging errors and exceptions
• Exercise and homework

Class 5: Functions

• Recap of previous class
• Writing functions in Python
• Parameters and arguments in functions
• Return statements in functions
• Local and global variables in Python functions
• Exercise and homework

Class 6: Lists and Tuples

• Recap of previous class
• Creating and modifying lists and tuples in Python
• Indexing and slicing lists and tuples
• List and tuple operations and methods
• Combining data types in Python
• Exercise and homework

Class 7: Dictionaries and Sets

• Recap of previous class
• Creating and modifying dictionaries and sets in Python
• Dictionary and set operations and methods
• Iterating over dictionaries and sets
• Combining data types in Python
• Exercise and homework

Class 8: File Input/Output

• Recap of previous class
• Reading and writing text files in Python
• File modes and permissions in Python
• Using with statements for file input/output
• Working with CSV files in Python
• Exercise and homework

Class 9: Object-oriented Programming

• Recap of previous class
• Introduction to object-oriented programming in Python
• Creating classes and objects in Python
• Class inheritance and polymorphism in Python
• Encapsulation and abstraction in Python
• Exercise and homework

Class 10: Modules and Packages

• Recap of previous class
• Introduction to modules and packages in Python
• Creating modules and importing modules in Python
• Using third-party modules and packages in Python
• Installing and managing packages with pip
• Exercise and homework

Class 11: Final Project

• Recap of previous classes
• Final project assignment and instructions
• Working on the final project in class
• Submission and presentation of final project in class

That's it! I hope this syllabus and breakdown help you in planning your course. Good luck with intro Python programming!

Note: The above syllabus is tentative and may be modified as per the instructor's discretion.

Here is a course syllabus for a 20-hour advanced Python programming course:

Course Overview

This 20-hour course is designed for students who already have a solid understanding of Python programming and want to take their skills to the next level. By the end of this course, students will be able to write complex programs and understand key concepts such as object-oriented programming, advanced data structures, and algorithms.

Here's a breakdown of each class:

Class 1: Object-Oriented Programming

• Overview of the course and its objectives
• Review of basic Python syntax
• Introduction to object-oriented programming
• Classes and objects
• Properties and methods
• Access modifiers
• Exercise and homework

Class 2: Inheritance

• Recap of previous class
• Understanding inheritance
• Base and derived classes
• Overriding methods
• Multiple inheritance
• Method resolution order
• Exercise and homework

Class 3: Polymorphism

• Recap of previous class
• Understanding polymorphism
• Duck typing
• Operator overloading
• Abstract classes
• Exercise and homework

Class 4: Abstract Classes and Interfaces

• Recap of previous class
• Abstract classes and interfaces
• Defining abstract classes and interfaces
• Implementing abstract classes and interfaces
• Multiple inheritance with abstract classes and interfaces
• Exercise and homework

Class 5: Decorators

• Recap of previous class
• Introduction to decorators
• Function decorators
• Class decorators
• Method decorators
• Nested decorators
• Exercise and homework

Class 6: Generators

• Recap of previous class
• Understanding generators
• Generator functions
• Generator expressions
• Coroutines
• Synchronous and asynchronous programming
• Exercise and homework

Class 7: Advanced Data Structures

• Recap of previous class
• Advanced data structures in Python
• Stacks and queues
• Heaps and priority queues
• Trees and graphs
• Red-black trees
• Exercise and homework

Class 8: Recursion

• Recap of previous class
• Understanding recursion
• Recursive functions
• Tail recursion
• Recursive data structures
• Handling recursion errors
• Exercise and homework

Class 9: Searching and Sorting Algorithms

• Recap of previous class
• Searching algorithms in Python
• Linear search
• Binary search
• Hash tables
• Sorting algorithms in Python
• Bubble sort
• Selection sort
• Insertion sort
• Quick sort
• Merge sort
• Exercise and homework

Class 10: GUI Programming with Tkinter

• Recap of previous class
• Understanding layout management in Tkinter
• Understanding event handling in Tkinter
• Binding events to widgets
• Creating your own gui programme
• Exercise and homework

Class 11: Project: Building a Web Scraper

• Recap of previous classes
• Assignment of a project to build a web scraper
• Working on the project in class
• Submission and presentation of the project in class

That's it! I hope this syllabus and breakdown help you in planning your course. Good luck with your advanced Python programming!

Note: The above syllabus is tentative and may be modified as per the instructor's discretion.

By the end of the Software Development course students will have usable knowledge of the following:

• Intro Python Course objectives.
• Intermediate Python Course objectives.
• Advanced Python Course objectives.
• Project & test.

Note: The above syllabus is tentative and may be modified as per the instructor's discretion.

By the end of the Software Engineering course (Python + 1 other programming language of choice), students will have usable knowledge of the following:

• Intro Python Course objectives.
• Intermediate Python Course objectives.
• Advanced Python Course objectives.
• Project & test.
• Intro of programming language 2 (your choice) fundamentals
• Intermediate programming language 2.
• Advanced programming language 2 objectives.
• Project & test.

Note: The above syllabus is tentative and may be modified as per the instructor's discretion.

By the end of the Full Stack Web Development course with python, students will have usable knowledge of the following:

• Understand the Fundamentals of web design
• Be able to understand classes coupled with Objects.
• Understand of datatypes together with operators.
• Understand variable declaration including initialization.
• Learn Methods, functions coupled with sequential code.
• Decision making: If statements not to mention switch cases.
• Learn about Loops, namely a do while, for loop and while loop.
• How to use Django and Python Fundamentals.
• Create Websites using Django Framework and best development principals & standards
• IDE's, applets coupled with publishing applications.
• Including HTML, CSS, JavaScript and Web Services.

Note: The above syllabus is tentative and may be modified as per the instructor's discretion.

By the end of the Data Science course, students will have usable knowledge of the following:

• Apply statistical methods to data
• Be able to understand Python to explore and transform data.
• Create,validate machine learning models with Azure Machine Learning.
• Thoroughly Understand Python code to build machine learning models.
• Apply data science techniques to common scenarios.
• Implement a machine learning solution for a given data problem.
• Learn advanced Python and Data Analysis to implement computer science algorithms.
• Implement a BioInformatics and natural language processing.
• Acquire the skills needed to find structure in data and how to use the python libraries.
• Matplotlib.
• SciKit Learn.
• NumPy.
• NLTK,

Note: The above syllabus is tentative and may be modified as per the instructor's discretion.