Python Functions, Files, and Dictionaries course Offered by University of Michigan from Coursera

Expand your Python programming skills by diving into essential concepts that will help you build more efficient and effective code. In this course, you’ll explore advanced Python techniques and data structures, focusing on functions, file handling, and dictionaries. This course is designed to enhance your understanding of Python and provide you with the tools needed to tackle more complex programming challenges.

Skills you will gain

Skills You Will Gain

  1. Advanced Python Programming
    • Function Design and Usage: Master the art of defining and using functions to make your code modular, reusable, and organized. Understand how to use function parameters effectively, including positional, optional, and keyword arguments.
    • Lambda Expressions: Learn how to create anonymous functions with lambda, useful for quick, small-scale operations without needing to formally define a function.
  2. Data Structure Mastery
    • Dictionaries: Gain expertise in using dictionaries for managing key-value pairs. Learn how to create, access, update, and delete dictionary entries, and work with nested dictionaries to handle complex data structures.
    • Dictionary Methods: Utilize various dictionary methods such as .get(), .keys(), .values(), and .items() to perform operations and retrieve data efficiently.
  3. File Handling Proficiency
    • Reading and Writing Files: Acquire skills in reading data from and writing data to files. Understand different file modes and how to manage file pointers.
    • CSV File Manipulation: Handle CSV files for data storage and processing, including reading from and writing to CSV formats, which is essential for data analysis tasks.
  4. Data Sorting and Evaluation
    • Sorting with sorted(): Learn how to use Python’s sorted() function to arrange data in a specified order. Control sorting behavior by passing custom functions or lambda expressions to sort data according to specific criteria.
    • Data Analysis: Apply sorting and data manipulation techniques to analyze and interpret data effectively.
  5. Code Debugging and Optimization
    • Error Handling: Develop skills in managing and debugging errors that arise during file operations and function execution. Learn how to handle exceptions and implement error-checking mechanisms.
    • Code Optimization: Improve code efficiency and readability through better function design, data handling practices, and optimization techniques.
  6. Practical Application
    • Project Implementation: Apply your knowledge to a final project that involves analyzing social media data. Compute sentiment scores and manipulate CSV files, integrating various Python concepts into a cohesive, real-world application.
  7. Data Processing and Management
    • Sentiment Analysis: Learn how to process textual data to extract meaningful insights, such as sentiment scores, which can be useful for understanding opinions and trends in social media or other textual data sources.
    • File Operations: Gain experience in handling large datasets and performing data manipulation tasks necessary for real-world data processing and analysis.

These skills will not only enhance your Python programming capabilities but also prepare you for more complex data analysis tasks and real-world programming challenges.

What you will learn

What You Will Learn

  1. Functions in Python
    • Defining and Using Functions: Learn how to create functions using the def keyword, and understand the role of parameters and return values in making your code modular and reusable.
    • Local vs. Global Variables: Understand the difference between local and global variables, and how to manage their scope within your functions.
    • Parameter-Passing Techniques: Explore different ways to pass parameters to functions, including positional arguments, default values, and keyword arguments.
    • Lambda Expressions: Discover how to use lambda expressions to create anonymous functions for concise, one-off operations.
    • Higher-Order Functions: Learn about functions that take other functions as arguments or return functions, enhancing your ability to write flexible and reusable code.
  2. Dictionary Data Structure
    • Creating and Using Dictionaries: Learn how to define dictionaries in Python, store key-value pairs, and perform operations such as adding, updating, and deleting entries.
    • Dictionary Methods and Operations: Explore various dictionary methods, including .get(), .keys(), .values(), and .items(), to efficiently manage and access data.
    • Nested Dictionaries: Work with nested dictionaries to handle complex data structures, enabling you to organize and manipulate hierarchical data.
  3. File Handling
    • Reading and Writing Files: Understand how to open, read from, and write to files in Python. Learn about different file modes and how to manage file pointers.
    • Context Managers: Use the with statement to ensure files are properly opened and closed, even in the case of errors.
    • CSV Files: Gain experience working with CSV (Comma-Separated Values) files, including reading data from and writing data to CSV format, which is common for data storage and interchange.
  4. Data Sorting
    • Using the sorted() Function: Learn how to sort lists and other iterable data structures using Python’s built-in sorted() function.
    • Custom Sorting Order: Understand how to control the sorting order by passing custom functions or lambda expressions to the key parameter of sorted(), allowing for flexible and precise data sorting.
  5. Practical Application and Projects
    • Social Media Data Analysis: Apply your knowledge to a final project that involves analyzing simulated social media data. Compute sentiment scores to understand user opinions and trends.
    • CSV File Manipulation: Practice reading from and writing to CSV files as part of the final project, reinforcing your file handling skills and demonstrating your ability to handle real-world data.

Additional Learning Outcomes

  • Enhanced Python Programming Skills: Build on your foundational Python knowledge with advanced concepts and techniques.
  • Problem-Solving: Develop problem-solving skills by applying Python functions, file handling, and dictionary operations to practical scenarios.
  • Data Management: Improve your ability to manage and process data efficiently, a valuable skill in various programming and data analysis tasks.