Programming Thinking with Python Course from Udemy
“Everyone in this country should learn to program a computer because it teaches you to think.” – Steve Jobs.
Many view computer programming as a complex subject reserved for the very smart. However, with the right approach to thinking about programming, it becomes accessible to everyone.
In this course, “Programming Thinking,” we will demystify programming concepts by explaining them in simple terms. This will help build your understanding and shape the way you think about computer programs.
Benefits of Understanding Computer Programming
- Enhances Problem-Solving and Reasoning Skills: Learning to program boosts your ability to solve problems and reason logically.
- Job Application Advantage: Knowledge of programming makes you stand out in job applications.
- Comprehending Complex Systems: Programming knowledge helps you understand and work with complex systems.
- Automate Repetitive Tasks: Use Python to automate mundane tasks, saving time and effort.
- Build Confidence: Learning to program builds your confidence in tackling technical challenges.
- Gateway to Software Development Careers: Provides an entry point into numerous software development job opportunities.
Skills you will gain
Skills You Will Learn
- Programming Fundamentals
- Understanding Basic Concepts: Grasp fundamental programming concepts such as variables, data types, and operators.
- Control Structures: Learn to use if-else statements, loops (for and while), and logical operators to control the flow of programs.
- Python Proficiency
- Syntax and Semantics: Become proficient in Python’s syntax and semantics, enabling you to write clean and efficient code.
- Functions and Modules: Learn to write reusable code with functions and organize your code into modules.
- Data Structures
- Lists, Tuples, Dictionaries, and Sets: Understand and utilize Python’s built-in data structures to store and manipulate data effectively.
- Custom Data Structures: Implement and use custom data structures for more advanced data handling.
- Algorithmic Thinking
- Problem Decomposition: Break down complex problems into smaller, manageable components.
- Common Algorithms: Gain familiarity with essential algorithms such as sorting and searching.
- Debugging and Testing
- Error Detection: Develop skills to identify and fix errors in your code.
- Testing Techniques: Learn different testing methodologies to ensure your code works as expected.
- Object-Oriented Programming (OOP)
- Classes and Objects: Understand the principles of OOP and how to create and use classes and objects in Python.
- Inheritance and Polymorphism: Learn advanced OOP concepts like inheritance and polymorphism to write more modular and reusable code.
- File Handling and Data Persistence
- Reading and Writing Files: Learn to handle file input/output operations to read from and write to files.
- Data Persistence: Understand how to store and retrieve data in various formats.
- Automation
- Automating Repetitive Tasks: Use Python to automate repetitive tasks, improving efficiency and productivity.
- Basic Web Scraping: Learn to extract data from websites using libraries like BeautifulSoup and requests.
- Data Analysis
- Using Pandas and NumPy: Perform data manipulation and analysis with powerful Python libraries like pandas and NumPy.
- Data Visualization: Create basic visualizations to represent data insights.
- Intro to Machine Learning
- Scikit-learn Basics: Get a basic understanding of machine learning concepts and how to implement simple machine learning models using scikit-learn.
- Real-World Application Development
- Project Building: Gain practical experience by building small applications or games.
- Portfolio Creation: Develop projects that can be showcased in your portfolio to potential employers.
Additional Skills
- Critical Thinking and Problem-Solving: Enhance your ability to think critically and solve complex problems.
- Effective Communication: Learn to articulate programming concepts and solutions clearly.
- Continuous Learning: Develop the mindset and skills necessary for continuous learning and adapting to new technologies
What you will learn
What You Will Learn in the “Programming Thinking with Python” Course
1. Introduction to Programming Concepts
- Basic Programming Concepts:
- Understanding algorithms and flowcharts.
- Writing pseudocode.
- Introduction to the concept of programming languages and their importance.
- Python Basics:
- Setting up the Python environment.
- Python syntax and basic commands.
- Writing your first Python program.
2. Variables and Data Types
- Variables:
- What are variables and how to use them.
- Naming conventions and best practices.
- Data Types:
- Understanding different data types: integers, floats, strings, and booleans.
- Type conversion and typecasting.
3. Control Structures
- Conditional Statements:
- If-else statements.
- Nested and chained conditions.
- Loops:
- For loops.
- While loops.
- Nested loops.
4. Functions and Modules
- Functions:
- Defining and calling functions.
- Function arguments and return values.
- Scope and lifetime of variables.
- Modules:
- Importing and using standard Python libraries.
- Creating and using custom modules.
5. Data Structures
- Lists:
- Creating and manipulating lists.
- List comprehensions.
- Tuples:
- Understanding and using tuples.
- Differences between lists and tuples.
- Dictionaries:
- Creating and using dictionaries.
- Dictionary methods and operations.
- Sets:
- Creating and using sets.
- Set operations and methods.
6. String Manipulation
- String Operations:
- Basic string operations and methods.
- String formatting and concatenation.
- Regular Expressions:
- Introduction to regular expressions.
- Using regular expressions for pattern matching.
7. File Handling
- Reading and Writing Files:
- Opening, reading, and writing text files.
- Working with different file modes.
- File Operations:
- Managing file paths and directories.
- Handling exceptions during file operations.
8. Error Handling and Debugging
- Exceptions:
- Understanding exceptions and error handling.
- Using try-except blocks.
- Debugging:
- Common debugging techniques.
- Using debugging tools and IDE features.
9. Object-Oriented Programming (OOP)
- Classes and Objects:
- Defining and creating classes.
- Creating and using objects.
- OOP Principles:
- Inheritance and polymorphism.
- Encapsulation and abstraction.
10. Automation with Python
- Scripting:
- Writing scripts to automate repetitive tasks.
- Scheduling and running Python scripts.
- Web Scraping:
- Introduction to web scraping.
- Using libraries like BeautifulSoup and requests.
11. Data Analysis and Visualization
- Using Pandas and NumPy:
- Data manipulation with pandas.
- Numerical operations with NumPy.
- Data Visualization:
- Basic plotting with matplotlib.
- Creating graphs and charts.
12. Project Development
- Building Projects:
- Developing small applications or games.
- Real-world projects to apply learned concepts.
- Portfolio Development:
- Creating and showcasing projects.
- Preparing for job applications with a strong portfolio.
13. Continuous Learning and Problem-Solving
- Problem-Solving Techniques:
- Breaking down complex problems.
- Developing a problem-solving mindset.
- Resources for Continuous Learning:
- Exploring additional learning resources.
- Keeping up with new Python developments and libraries.