University of California San Diego
Basic Data Processing and Visualization
University of California San Diego

Basic Data Processing and Visualization

This course is part of Python Data Products for Predictive Analytics Specialization

Taught in English

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Julian McAuley
Ilkay Altintas

Instructors: Julian McAuley

20,610 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

4.3

(187 reviews)

|

94%

Intermediate level

Recommended experience

10 hours (approximately)
Flexible schedule
Learn at your own pace

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

Details to know

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Assessments

12 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.3

(187 reviews)

|

94%

Intermediate level

Recommended experience

10 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Python Data Products for Predictive Analytics Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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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 videos4 quizzes1 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

Instructor ratings
4.5 (32 ratings)
Julian McAuley
University of California San Diego
5 Courses30,178 learners
Ilkay Altintas
University of California San Diego
14 Courses485,103 learners

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Showing 3 of 187

4.3

187 reviews

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    62.03%

  • 4 stars

    21.92%

  • 3 stars

    7.48%

  • 2 stars

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  • 1 star

    4.81%

PA
5

Reviewed on Jun 29, 2022

SR
5

Reviewed on Nov 19, 2020

SS
4

Reviewed on Feb 27, 2020

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