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Python for MATLAB Users

Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.

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4 Hours15 Videos51 Exercises
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Course Description

Transition from Matlab to Python

Python is a versatile programming language that is becoming more and more popular for doing data science. Companies worldwide are using Python to harvest insights from their data and get a competitive edge. This course focuses on helping Matlab users learn to use Python specifically for data science. You will quickly learn how to migrate from Matlab to Python for data analysis and visualization.

Explore NumPY and Matplotlib Libraries

Learn the fundamentals of Python syntax, and how to use NumPy arrays to store and manipulate data. You will learn how to use matplotlib to discover trends, correlations, and patterns in real datasets, including bicycle traffic in the city of Seattle and avocado prices across the United States.

Learn to Use If, Else, and Elif in Python

In the final chapters, you’ll learn how to control your Python flow. You’ll look at how to use a variety of Python contingencies such as if, else, and elif, as well as comparison operators to define which lines of your code will be executed.

By the end of this course, you’ll have a fundamental understanding of Python, its popular dictionaries and libraries, and hands-on experience in using both so you can confidently apply your new skills to your work, personal projects, or further learning.
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  1. 1

    From MATLAB to Python

    Free

    This chapter gets you started moving from MATLAB to Python. You'll learn about some of the similarities and differences between MATLAB and Python, how to use methods and packages, and be introduced to the popular NumPy package.

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    Welcome to Python!
    50 xp
    Basic calculations
    100 xp
    Forecasting an investment
    100 xp
    Types of variables
    100 xp
    Methods and packages
    50 xp
    Manipulating strings with methods
    100 xp
    Using Python packages
    100 xp
    Arrays & plotting
    50 xp
    Getting started with NumPy arrays
    100 xp
    Plotting bicycle traffic
    100 xp
    What predicts animal longevity?
    100 xp
  2. 2

    NumPy and Matplotlib

    In this chapter, you will build on your new NumPy knowledge. You will dive into NumPy arrays, the Python analog to matrices by performing mathematical operations and indexing. You will also begin to explore another important Python data structure, the list, and then round out the chapter by making customs plots of your arrays using Matplotlib.

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  3. 3

    Dictionaries and pandas

    This chapter introduces some powerful Python data structures: the dictionary and the pandas DataFrame. You will learn to create dictionaries by setting key-value pairs, and view then how to view and modify your dictionary. Then you will be introduced to one of the most important packages in the Pythonista's toolbox, pandas. Specifically, you'll focus on the pandas' structure, the DataFrame, which organizes tabular data in an easily accessible way. Lastly, you'll learn how to transform different data types into DataFrames to make your data easier to work with.

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  4. 4

    Control Flow and Loops

    You'll finish the course by controlling your Python flow. You will learn how to iterate through different Python data structures using for loops. You will also learn about Python contingencies using if, else, and elif and the Python comparison operators (greater than, less than, etc.) that will decide which lines of your code will be executed. Lastly, you'll circle back to NumPy arrays by using Python comparison operators to filter your arrays.

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Datasets

FAA Wildlife StrikesFremont Bridge - hourly trafficFremont Bridge - daily trafficAnimal taxonomyHistorical avocado data

Collaborators

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Mari Nazary
Collaborator's avatar
Becca Robins
Justin Kiggins HeadshotJustin Kiggins

Product Manager

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