Basic Data Processing and Visualization

University of California, San Diego via Coursera

Coursera based on 196 ratings

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Overview

This course introduces the fundamental techniques of data processing and visualization essential for analyzing and interpreting data effectively. It covers the initial steps of cleaning, organizing, and transforming raw data into usable formats. Learners explore basic tools and methods to handle datasets, including sorting, filtering, and summarizing data. The visualization segment teaches how to represent data visually through charts, graphs, and plots, enabling clearer communication of insights. Students gain hands-on experience with popular software or programming libraries to create bar charts,...

Syllabus

Week 1: Introduction to Data Products

This week, we will go over the syllabus and set you up with the course materials and software. We will introduce you to data products and refresh your memory on Python and Jupyter notebooks.

Week 2: Reading Data in Python

This week, we will learn how to load in datasets from CSV and JSON files. We will also practice manipulating data from these datasets with basic Python commands.

Week 3: Data Processing in Python

This week, our goal is to understand how to clean up a dataset before analyzing it. We will go over how to work with different types of data, such as strings and dates.

Week 4: Python Libraries and Toolkits

In this last week, we will get a sense of common libraries in Python and how they can be useful. We will cover data visualization with numpy and MatPlotLib, and also introduce you to the basics of webscraping with urllib and BeautifulSoup.

Final Project

Create your own Jupyter notebook with a dataset of your own choosing and practice data manipulation. Show off the skills you've learned and the libraries you know about in this project. We hope you enjoyed the course, and best of luck in your future learning!