This is the first course in the four-course specialization Python Data Products for Predictive Analytics, introducing the basics of reading and manipulating datasets in Python. In this course, you will learn what a data product is and go through several Python libraries to perform data retrieval, processing, and visualization.
Basic Data Processing and Visualization
This course is part of Python Data Products for Predictive Analytics Specialization
Instructors: Julian McAuley
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(188 reviews)
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What you'll learn
Develop data strategy and process for how data will be generated, collected, and consumed
Load and process formatted datasets such as CSV and JSON.
Deal with data in various formats (e.g. timestamps, strings) and filter and “clean” datasets by removing outliers etc.
Basic experience with data processing libraries such as numpy and data ingestion with urllib, requests
Skills you'll gain
Details to know
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There are 5 modules in this course
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.
What's included
6 videos6 readings2 quizzes2 discussion prompts
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.
What's included
6 videos3 quizzes1 discussion prompt
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.
What's included
4 videos3 quizzes1 discussion prompt
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.
What's included
5 videos3 quizzes1 assignment1 peer review2 discussion prompts
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!
What's included
1 video2 readings1 peer review1 discussion prompt
Instructors
Offered by
Recommended if you're interested in Data Analysis
University of California San Diego
University of California San Diego
University of Colorado Boulder
University of Colorado Boulder
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