Green Biotec UG Bremen Germany
Python Programming
| Python Programming | |
|---|---|
| Course Description | This course provides an in-depth introduction to Python, one of the most versatile and widely used programming languages today. Python is known for its simplicity and readability, making it an excellent choice for beginners and experienced developers. The course covers fundamental programming concepts, data structures, and applications in data analysis, web development, and machine learning. By the end of the course, students will be equipped with the skills to solve real-world problems using Python. |
| Recommended Books | 1. “Python Crash Course” by Eric Matthes. 2. “Automate the Boring Stuff with Python” by Al Sweigart. 3. “Fluent Python” by Luciano Ramalho. 4. “Python Programming: An Introduction to Computer Science” by John Zelle. |
| Course Learning Outcomes | After completing this course, students will be able to: 1. Write efficient Python programs using basic and advanced constructs. 2. Understand and implement Python’s data structures and algorithms. 3. Develop real-world applications using libraries like pandas, NumPy, and matplotlib. 4. Debug and optimize Python code effectively. 5. Explore Python’s capabilities in web development, automation, and machine learning. |
| Assessment System | Quizzes: 10-15% Assignments: 5-10% Midterms: 30-40% End Semester Exam: 40-50% |
| Lecture Plan | ||
|---|---|---|
| S.No. | Description | Quizzes/Assignment |
| 1 | Introduction to Python: Installation, Syntax, and IDEs | |
| 2 | Python Basics: Variables, Data Types, and Operators | Quiz 1 |
| 3 | Control Structures: Conditional Statements and Loops | |
| 4 | Functions: Writing and Using Functions in Python | |
| 5 | Data Structures: Lists, Tuples, Dictionaries, and Sets | Assignment 1 |
| 6 | Working with Strings and Regular Expressions | Quiz 2 |
| 7 | File Handling: Reading and Writing Files | |
| 8 | Exception Handling: Debugging and Error Management | |
| 9 | Introduction to Object-Oriented Programming (OOP) | Assignment 2 |
| 10 | Modules and Libraries: Importing and Using Python Packages | |
| 11 | Data Analysis with pandas and NumPy | Quiz 3 |
| 12 | Data Visualization with matplotlib and seaborn | |
| 13 | Introduction to Web Development with Flask | Assignment 3 |
| 14 | Introduction to Machine Learning with scikit-learn | |
| 15 | Capstone Project: Real-World Python Application | |
