Introduction to Python
Master the basics of data analysis with Python in just four hours. This online course will introduce the Python interface and explore popular packages.
Master the basics of data analysis with Python in just four hours. This online course will introduce the Python interface and explore popular packages.
Level up your data science skills by creating visualizations using Matplotlib and manipulating DataFrames with pandas.
Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.
Continue to build your modern Data Science skills by learning about iterators and list comprehensions.
Learn to write efficient code that executes quickly and allocates resources skillfully to avoid unnecessary overhead.
Dive into data science using Python and learn how to effectively analyze and visualize your data. No coding experience or skills needed.
Master the fundamentals of programming in Python. No prior knowledge required!
Dive in and learn how to create classes and leverage inheritance and polymorphism to reuse and optimize code.
Learn to use best practices to write maintainable, reusable, complex functions with good documentation.
Explore data structures such as linked lists, stacks, queues, hash tables, and graphs; and search and sort algorithms!
Dive into the Python ecosystem, discovering modules and packages along with how to write custom functions!
Learn about modularity, documentation, and automated testing to help you solve data science problems more quickly and reliably.
Learn how to work with dates and times in Python.
Prepare for your next coding interviews in Python.
Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.
Learn to create your own Python packages to make your code easier to use and share with others.
Learn efficient techniques in pandas to optimize your Python code.
Master Python testing: Learn methods, create checks, and ensure error-free code with pytest and unittest.
Use your knowledge of common spreadsheet functions and techniques to explore Python!
Learn how to use Python to analyze customer churn and build a model to predict it.
This course is for R users who want to get up to speed with Python!
Discover the power of discrete-event simulation in optimizing your business processes. Learn to develop digital twins using Python's SimPy package.
Learn how to use Python parallel programming with Dask to upscale your workflows and efficiently handle big data.
Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.
Define functions to catch errors when new users register for an app!
Create custom Python functions to validate user input!
Manipulate date and time using Python
Review a data analysis workflow for adherence to Python standards and best-practices.
Dive into agriculture using supervised machine learning and feature selection to aid farmers in crop cultivation and solve real-world problems.
Use web scraping and NLP to find the most frequent words in classic literature: Herman Melville's novel, Moby Dick.
Tidy a bank marketing campaign dataset by splitting it into subsets, updating values, converting data types, and storing it as multiple csv files.
Use coding best practices and functions to improve a script!