Python for Excel Users

In this live online course we’ll leverage basic data literacy to learn the industry-standard tools for data processing and visualization. This course will cover an introduction to Jupyter Notebook, pandas, and Matplotlib. The skills you’ll learn in this course will let you apply your Excel data manipulation skills in Python. Finally, this course will provide an overview of the capabilities in the Python ecosystem for data (including big data) processing and visualization.

What you'll learn—and how you can apply it

By the end of this hands-on course, you’ll understand:

• The basics of using Jupyter Notebooks
• Data manipulation and processing with Pandas
• Data visualization with Matplotlib

And you’ll be able to:

• Launch an interactive programming environment
• Load data from the web or downloaded files and in multiple formats
• Create visualizations and graphs

This training is for you because...

• You’re someone who enjoys studying data
• You work with data in any form, but mostly tabular
• You want to become a skilled data analyst using Python

Prerequisites  

• Basic familiarity with Python or recommend completing the first five Introduction to Python Programming on-demand course modules:
  • Strings
  • Numbers
  • Bools
  • Collections
  • Imports

Jupyter Notebooks / Setup 

• Get set up with Anaconda Notebooks. Watch this video to learn how. 
• Or, if you prefer to use a Jupyter Notebook on your machine, you can install Anaconda Distribution (free) and open JupyterLab. Instructions can be found within the Get Started with Anaconda course or in our online documentation. 
• Alternatively, you can use any preferred Jupyter Notebook service.

Recommended follow-up  

• Introduction to Python Programming on-demand course (remaining modules)
• Introduction to Pandas for Data Analysis on-demand course
• Introduction to Data Visualization on-demand course

About the Instructor

Albert DeFusco is a data scientist who also does some development, analytics, DevOps, predictive modeling, and MLOps. He specializes in scientific and high-performance computing and has taught introductory and advanced data science topics, using Anaconda products and open-source packages in many different industries and sectors. He holds a Ph.D. in theoretical chemistry.