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Di Wu

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.

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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 make your programs reusable and adaptive.

Are you ready? Let's go!

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What's inside

Syllabus

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!
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Functions with Parameters
Now 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 Values
For 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 Functions
With 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!

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Focuses on data science using Python, appealing to individuals pursuing this career path
Designed for non-programmers, making it accessible to individuals with no prior programming experience
Introduces core Python concepts such as functions, ensuring a strong foundation for further learning
Taught by Di Wu, whose expertise in data science adds credibility to the course

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introduction to Python Functions with these activities:
Review the course syllabus and make a study plan
A study plan can help you stay on track and make the most of your time in the course.
Browse courses on Course Syllabus
Show steps
  • Go to the course website and download the syllabus.
  • Read through the syllabus and identify the key topics that will be covered.
  • Create a study plan that outlines when you will study each topic.
Review high school Algebra II
Python is a math-based language, so it's important to make sure your algebra is solid before you start learning Python.
Browse courses on Trigonometry
Show steps
  • Review your notes from Algebra II.
  • Take a practice test to identify areas where you need more practice.
  • Find some online resources or textbooks to help you brush up on the topics you need to review.
Complete the Python Tutorial on the official Python website
The official Python tutorial is a great way to get started with the basics of Python and learn the syntax.
Browse courses on Python Basics
Show steps
  • Go to the official Python website and find the tutorial.
  • Read through the tutorial and complete the exercises.
  • If you get stuck, there are plenty of online resources and forums where you can get help.
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Learn Functions With Examples
Get a solid grasp of Python functions and their various uses through the guidance of video tutorials.
Show steps
  • Watch a series of video tutorials that comprehensively cover functions in Python.
  • Follow along with the demos and code examples provided in the tutorials.
  • Take notes and experiment with the different function concepts introduced.
Practice Writing Functions
Enhance your understanding of functions by actively writing and testing your own code.
Show steps
  • Set up a Python development environment and create a new project.
  • Write Python code to define and call functions.
  • Experiment with different function parameters and return values.
  • Test your functions using print statements or the Python debugger.
Solve Python coding challenges on LeetCode
Coding challenges are a great way to practice your Python skills and learn new techniques.
Show steps
  • Go to the LeetCode website and create an account.
  • Choose a coding challenge that you want to solve.
  • Read the problem statement carefully and come up with a solution.
  • Implement your solution in Python and submit it.
  • If your solution is correct, you will earn points and move on to the next challenge.
Join a Python Study Group
Engage with peers to discuss concepts, share knowledge, and work on projects related to Python functions.
Show steps
  • Find or create a study group with other Python learners.
  • Meet regularly to discuss Python functions and related topics.
  • Collaborate on projects that involve using functions.
Create a Python Function Library
Solidify your knowledge by creating a personal library of reusable Python functions.
Show steps
  • Identify commonly used tasks or operations in your Python projects.
  • Create Python functions for each of these tasks.
  • Organize and document your functions in a structured library.
  • Test your library functions and make improvements as needed.
Help other students in the course
Helping others is a great way to solidify your understanding of the material and develop your communication skills.
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Show steps
  • Go to the course forum or discussion board.
  • Look for students who are asking questions or struggling with the material.
  • Offer your help and answer their questions.
Contribute to an open-source Python project
Contributing to an open-source project is a great way to give back to the community and learn from more experienced Python developers.
Browse courses on Open Source
Show steps
  • Find an open-source Python project that you are interested in.
  • Read the project's documentation and understand how it works.
  • Identify an area where you can contribute.
  • Make your changes and submit a pull request.
  • If your pull request is accepted, your changes will be merged into the project and you will become a contributor to the project.

Career center

Learners who complete Introduction to Python Functions will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts gather and interpret data to help businesses make informed decisions. This course will provide you with the foundational skills in Python functions, which are essential for data analysis. You will learn how to define and use functions to make your programs reusable and adaptive, which is crucial for handling large and complex datasets. Additionally, the concepts of functions with parameters and return values will equip you to extract meaningful insights from data and communicate your findings effectively.
Software Engineer
Software Engineers design, develop, and maintain software systems. This course will provide you with a strong foundation in Python functions, which are essential for writing efficient and maintainable code. You will learn how to define and use functions to modularize your code and improve its reusability. Furthermore, the concepts of functions with parameters and return values will enable you to design flexible and adaptable software components.
Data Scientist
Data Scientists use scientific methods and algorithms to extract knowledge and insights from data. This course will provide you with the necessary skills in Python functions to effectively manipulate and analyze data. You will learn how to define and use functions to automate data processing tasks, making your workflow more efficient. Additionally, the concepts of functions with parameters and return values will enable you to create reusable and modular code, which is crucial for handling large and complex datasets.
Web Developer
Web Developers design and develop websites and web applications. This course will provide you with a solid understanding of Python functions, which are essential for building dynamic and interactive web applications. You will learn how to define and use functions to handle user input, process data, and generate dynamic content. Furthermore, the concepts of functions with parameters and return values will empower you to create modular and reusable code, making your web development process more efficient.
Machine Learning Engineer
Machine Learning Engineers design and develop machine learning models to solve real-world problems. This course will provide you with a strong foundation in Python functions, which are essential for building and deploying machine learning models. You will learn how to define and use functions to preprocess data, train models, and evaluate their performance. Additionally, the concepts of functions with parameters and return values will enable you to create flexible and reusable code, which is crucial for developing and maintaining machine learning systems.
Business Analyst
Business Analysts analyze business processes and data to identify areas for improvement. This course will provide you with the skills in Python functions to effectively analyze data and communicate your findings. You will learn how to define and use functions to automate data processing tasks, making your workflow more efficient. Additionally, the concepts of functions with parameters and return values will enable you to create reusable and modular code, which is crucial for handling large and complex datasets.
Statistician
Statisticians collect, analyze, interpret, and present data. This course will provide you with a strong foundation in Python functions, which are essential for statistical data analysis. You will learn how to define and use functions to automate data processing tasks, making your workflow more efficient. Additionally, the concepts of functions with parameters and return values will enable you to create reusable and modular code, which is crucial for handling large and complex datasets.
Actuary
Actuaries use mathematical and statistical methods to assess risk and uncertainty. This course will provide you with a strong foundation in Python functions, which are essential for building actuarial models. You will learn how to define and use functions to automate data processing tasks, making your workflow more efficient. Additionally, the concepts of functions with parameters and return values will enable you to create reusable and modular code, which is crucial for developing and maintaining actuarial models.
Financial Analyst
Financial Analysts use financial data to make investment recommendations. This course will provide you with the skills in Python functions to effectively analyze financial data. You will learn how to define and use functions to automate data processing tasks, making your workflow more efficient. Additionally, the concepts of functions with parameters and return values will enable you to create reusable and modular code, which is crucial for handling large and complex datasets.
Operations Research Analyst
Operations Research Analysts use mathematical and analytical methods to improve the efficiency of organizations. This course will provide you with a strong foundation in Python functions, which are essential for building optimization models. You will learn how to define and use functions to automate data processing tasks, making your workflow more efficient. Additionally, the concepts of functions with parameters and return values will enable you to create reusable and modular code, which is crucial for developing and maintaining optimization models.
Risk Analyst
Risk Analysts assess and manage risks for organizations. This course will provide you with a strong foundation in Python functions, which are essential for building risk assessment models. You will learn how to define and use functions to automate data processing tasks, making your workflow more efficient. Additionally, the concepts of functions with parameters and return values will enable you to create reusable and modular code, which is crucial for developing and maintaining risk assessment models.
Data Engineer
Data Engineers design and implement data pipelines to manage and process large datasets. This course will provide you with a strong foundation in Python functions, which are essential for building and maintaining data pipelines. You will learn how to define and use functions to automate data processing tasks, making your workflow more efficient. Additionally, the concepts of functions with parameters and return values will enable you to create reusable and modular code, which is crucial for developing and maintaining data pipelines.
Database Administrator
Database Administrators manage and maintain databases. This course will provide you with a strong foundation in Python functions, which are essential for automating database administration tasks. You will learn how to define and use functions to perform data manipulation and management tasks, making your workflow more efficient. Additionally, the concepts of functions with parameters and return values will enable you to create reusable and modular code, which is crucial for developing and maintaining database administration scripts.
Systems Analyst
Systems Analysts analyze and design computer systems. This course will provide you with a strong foundation in Python functions, which are essential for building and maintaining software systems. You will learn how to define and use functions to modularize your code and improve its reusability. Furthermore, the concepts of functions with parameters and return values will enable you to design flexible and adaptable software components.
Software Tester
Software Testers evaluate the quality of software systems. This course will provide you with a strong foundation in Python functions, which are essential for automating software testing tasks. You will learn how to define and use functions to perform test case generation, test execution, and test result analysis, making your workflow more efficient. Additionally, the concepts of functions with parameters and return values will enable you to create reusable and modular code, which is crucial for developing and maintaining software testing scripts.

Reading list

We've selected 15 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Introduction to Python Functions.
Provides a comprehensive introduction to Python programming, covering the basics of the language, data structures, algorithms, and object-oriented programming.
Comprehensive introduction to Python programming, covering the basics of the language, data structures, algorithms, and object-oriented programming.
Provides practical advice on how to write better Python code, covering topics such as code readability, performance, and testing.
Comprehensive guide to Python programming, covering advanced topics such as decorators, generators, and metaprogramming.
Comprehensive introduction to Python programming, covering the basics of the language, data structures, algorithms, and object-oriented programming.
Concise reference to Python programming, covering the basics of the language, data structures, algorithms, and object-oriented programming.
Comprehensive introduction to Python programming, covering the basics of the language, data structures, algorithms, and object-oriented programming.
Concise reference to Python programming, covering the basics of the language, data structures, algorithms, and object-oriented programming.
Practical guide to Python programming for data analysis, covering topics such as data cleaning, data manipulation, and data visualization.
Practical guide to Python programming for machine learning, covering topics such as data preprocessing, model selection, and model evaluation.

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