Go to Course: https://www.coursera.org/learn/introduction-python-functions
**Course Review: Introduction to Python Functions** If you've ever aspired to learn a programming language only to find yourself overwhelmed and defeated, you're certainly not alone. Many learners share this experience, particularly when facing the complexities of coding. Fortunately, Coursera's "Introduction to Python Functions" course is here to bridge that gap, particularly for those embarking on their Python programming journey for data-related tasks. ### Course Overview "Introduction to Python Functions" is an invaluable module within a broader specialization tailored specifically for learners with little or no prior programming experience. This course provides a nurturing environment for beginners, allowing them to explore the fundamental aspects of Python functions while preparing them to dive into data analysis and manipulation. The course's focus is on the building blocks of Python programming—functions. By the end of this module, you’ll be equipped to leverage predefined functions, create your own, and utilize them effectively in your data projects. ### Syllabus Breakdown 1. **Hello, Functions!** - The course kicks off with an engaging introduction to functions. This foundational module emphasizes the significance of functions in programming. You’ll revisit familiar functions and take your first steps in defining simple functions of your own. The module encourages an interactive learning experience, making it perfect for beginners who may need to build confidence. 2. **Functions with Parameters** - Building on the basics, this module delves deeper into the realm of functions by introducing parameters—critical for tailoring function behavior. You'll learn how to craft functions that can accept inputs, which is an essential skill for any data-oriented project. The practical examples provided make understanding this concept much easier. 3. **Functions with Return Values** - In data science, it isn’t just about performing tasks; it’s also about obtaining results that can be used further down the line. This module introduces functions that return values, a crucial aspect of programming that allows you to gather outcomes from function execution. The clarity in explanations helps demystify this concept for all learners. 4. **Functions in Functions** - Finally, the course culminates in the exploration of nested functions. You’ll grasp the idea of encapsulating functions within other functions, including hierarchical and recursive functions. This advanced concept adds a layer of complexity but is essential for more intricate programming tasks. ### Why You Should Take This Course **Comprehensive Learning Experience**: The course is structured to progressively build your skills, from basic functions to more complex nested functions, making it accessible and engaging. **Focus on Practical Application**: The emphasis on applying functions in data science projects ensures that you’re not just learning theory, but also understanding how to use Python in real-world scenarios. **Supportive Environment for Beginners**: Given its design for learners with no programming background, the course provides an encouraging atmosphere that promotes exploration and growth. **Flexible Learning Pace**: As with most Coursera offerings, you can learn at your own pace, revisiting challenging concepts as necessary. ### Final Thoughts Coursera's "Introduction to Python Functions" is an excellent starting point for anyone looking to delve into Python programming, particularly in the context of data science. With its user-friendly approach, practical examples, and thorough explanation of functions, learners are set up for success as they continue their programming journey. I highly recommend this course for novices eager to unlock the potential of Python and start manipulating data effectively. Whether you are aiming to enhance your skills for personal projects or professional development, this course will lay a solid foundation for your coding ambitions. So, are you ready to embark on this exciting adventure? Let’s go!
Hello, functions!
Welcome on board! This first module shows the reasons why we need functions and introduces basic function definitions. You are going to recall some functions we have learned before, and you are going to define some simple functions of your own! Are you ready? Let's go!
Functions with ParametersNow you should be comfortable with simple functions. This module introduces you more about functions with parameters, which are the majority ones you are going to call when you do your data science projects. Are you ready? Let's go!
Functions with Return ValuesFor data science projects, not only we need to execute some functions, but also we expect some results from the execution so we can use the results for next step. This module introduces you the functions with return values. Are you ready? Let's go!
Functions in FunctionsWith the knowledge you have learned about simple functions, functions with parameters, and functions with return values, you should be able to learn nested functions. This module introduces you the general idea of nested functions, as well as two specific categories of them: hierarchical functions and recursive functions. Are you ready? Let's go!
How many times have you decided to learn a programming language but got stuck somewhere along the way, grew frustrated, and gave up? This specialization is designed for learners who have little or no programming experience but want to use Python as a tool to play with data. In the second course, Introduction to Python Functions, you are going to learn and use functions predefined in Python and Python packages, you also are able to define functions as well. You will create and use functions to
some concepts could be explained more thoroughly, and i am confused why we haven't learned about lists in the first or second section.
I have practiced C++, Java, assembly and quite a few other languages but still I feel I have learned a lot from this course.
Excellent. I wish they could provide a book/reading materials.