In this course, you’ll continue to learn the fundamentals of Python for data science. We divided these courses into four parts to make mastering the fundamentals quicker and easier. This fourth part builds on the knowledge you acquired in our Variables, Data Types, and Lists in Python course, our For Loops and Conditional Statements in Python course, and our Dictionaries, Frequency Tables, and Functions in Python course.The demand for data science has never been higher — take advantage of this opportunity, and level up your career with Dataquest.
This course focuses on the following:
- Developing additional data science fundamentals in Python, like writing functions with multiple inputs
- Discovering how to use and install Jupyter Notebook
- Performing real-world data analysis tasks in a guided project that you can add to your portfolio
- Python Functions: Built-in Functions and Multiple Return Statements.
- Python Functions: Returning Multiple Variables and Function Scopes.
- Project: Learn and Install Jupyter Notebook.
- Guided Project: Profitable App Profiles for the App Store and Google Play Markets.
What will you learn
- How to define function arguments.
- How to employ Jupyter notebook.
- How to write functions that return multiple variables.
- How to build a portfolio project.