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URL: https://www.coursera.org/learn/data-analysis-and-visualization-with-python

⇱ Data Analysis and Visualization with Python | Coursera

Data Analysis and Visualization with Python

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Data Analysis and Visualization with Python

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Gain insight into a topic and learn the fundamentals.
4.7

15 reviews

Beginner level

Recommended experience

2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.7

15 reviews

Beginner level

Recommended experience

2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Students will learn how to perform data analysis and visualization using python.

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

12 assignments¹

AI Graded see disclaimer
Taught in English

Build your subject-matter expertise

This course is part of the Python: A Guided Journey from Introduction to Application 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

There are 3 modules in this course

In this course, you will learn how to read and write data from and to a file. You will also examine how to manipulate and analyze the data using lists, tuples, dictionaries, sets, and the pandas and Matplot libraries.

As a developer, it's important to understand how to deal with issues that could cause an application to crash. You will learn how to implement exceptions to handle these issues. You do not need a programming or computer science background to learn the material in this course. This course is open to anyone who is interested in learning how to code and write programs in Python. We are very excited that you will be learning with us and hope you enjoy the course!

In this module, we will discuss lists, tuples, dictionaries and sets.

What's included

5 videos15 readings5 assignments

5 videos•Total 53 minutes
  • Introduction to the Course•1 minute
  • Creating and Using Lists•17 minutes
  • Creating and Using Tuples•12 minutes
  • Creating and Using Dictionaries•12 minutes
  • Creating and Using Sets•13 minutes
15 readings•Total 185 minutes
  • Course Introduction•1 minute
  • Weekly Lesson PowerPoint•10 minutes
  • Python Recommended Links and Readings•10 minutes
  • Lesson 1 Overview•1 minute
  • Weekly Lesson PowerPoint•10 minutes
  • Building Lists Code Example•30 minutes
  • Lesson 2 Overview•1 minute
  • Weekly Lesson PowerPoint•10 minutes
  • Building Tuples Code Examples•30 minutes
  • Lesson 3 Overview•1 minute
  • Weekly Lesson PowerPoint•10 minutes
  • Building Dictionaries Code Examples•30 minutes
  • Lesson 4 Overview•1 minute
  • Weekly Lesson PowerPoint•10 minutes
  • Building Sets Code Example•30 minutes
5 assignments•Total 150 minutes
  • Lists Quiz•30 minutes
  • Tuples Quiz•30 minutes
  • Dictionaries Quiz•30 minutes
  • Sets Quiz•30 minutes
  • Formative Assessment: Create a List•30 minutes

In this module, you will explore how to read in data from a file, store information to a file, and modify a file.

What's included

3 videos9 readings4 assignments

3 videos•Total 22 minutes
  • Reading Numeric and Textual Data•9 minutes
  • How to Write Data to a File•8 minutes
  • Handling Exceptions During File Input and Output•5 minutes
9 readings•Total 123 minutes
  • Lesson 1 Overview•1 minute
  • Weekly Lesson PowerPoint•10 minutes
  • File Input Code Example•30 minutes
  • Lesson 2 Overview•1 minute
  • Weekly Lesson PowerPoint•10 minutes
  • File Output Code Example•30 minutes
  • Lesson 3 Overview•1 minute
  • Weekly Lesson PowerPoint•10 minutes
  • Handling Exceptions Code Example•30 minutes
4 assignments•Total 120 minutes
  • File Read Quiz•30 minutes
  • Writing Data Quiz•30 minutes
  • Handling Exceptions During File Input and Output•30 minutes
  • Formative Assessment: Creating, Modifying and Saving to a File•30 minutes

In this module, you will explore libraries that allow you to manipulate data.

What's included

5 videos9 readings3 assignments1 peer review

5 videos•Total 42 minutes
  • Using Data Analysis with the NumPy Library in Python•11 minutes
  • Using Data Analysis with the NumPy Library in Python Pt. 2•10 minutes
  • How to Use Data Analysis with the Pandas Library in Python •9 minutes
  • Using Data Visualization with Matplot Library in Python•12 minutes
  • Course Review•1 minute
9 readings•Total 123 minutes
  • Lesson 1 Overview•1 minute
  • Weekly Lesson PowerPoint•10 minutes
  • NumPy Library Code Example•30 minutes
  • Lesson 2 Overview•1 minute
  • Weekly Lesson PowerPoint•10 minutes
  • Pandas Library Code Example•30 minutes
  • Lesson 3 Overview•1 minute
  • Weekly Lesson PowerPoint•10 minutes
  • Matplotlib Code Example•30 minutes
3 assignments•Total 90 minutes
  • Data Analysis with NumPy Quiz•30 minutes
  • Pandas Library•30 minutes
  • Matplotlib Quiz•30 minutes
1 peer review•Total 60 minutes
  • Working with Data•60 minutes

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Instructors

Arizona State University
4 Courses•12,006 learners

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Frequently asked questions

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

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¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.