University of Colorado Boulder
Data Wrangling with Python Project
University of Colorado Boulder

Data Wrangling with Python Project

Di Wu

Instructor: Di Wu

Included with Coursera Plus

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

25 hours to complete
3 weeks at 8 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

25 hours to complete
3 weeks at 8 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Initiate and conduct a data wrangling project from raw data to a refined dataset for analysis.

  • Apply data wrangling techniques learned in the specialization to handle real-life data scenarios.

  • Utilize Python libraries and tools effectively for data wrangling tasks. Communicate and present data wrangling results effectively to stakeholders.

Details to know

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Assessments

5 assignments

Taught in English

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Build your subject-matter expertise

This course is part of the Data Wrangling with Python 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

In this introductory week, you will gain an understanding of the data wrangling pipeline, which serves as a structured approach to transform raw data into a cleaned and organized dataset for analysis. You will learn the key stages involved in the pipeline, setting the foundation for the rest of the course.

What's included

3 readings1 assignment

In this week, you will learn how to identify and define the scope and objectives of your data wrangling project. You will explore various data sources, understand their structure, and assess the suitability of each source for the project.

What's included

3 readings1 assignment

This week covers the data collection and integration stage of the data wrangling process. You will learn techniques for data collection, validate the collected data, and integrate data from multiple sources.

What's included

3 readings1 assignment

This week focuses on gaining a comprehensive understanding of the dataset through statistical analysis and data visualization. You will learn how to perform descriptive statistics, create informative visualizations, and conduct exploratory data analysis (EDA).

What's included

3 readings1 assignment

In this week, you will delve into essential data processing and manipulation techniques. You will learn how to handle missing values, detect and handle outliers, perform data sampling and dimensionality reduction, apply data scaling and discretization, and explore data cubes and pivot tables.

What's included

9 readings1 assignment1 discussion prompt

Instructor

Di Wu
University of Colorado Boulder
15 Courses40,290 learners

Offered by

Recommended if you're interested in Data Analysis

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