Data Wrangling with Python Project

Data Wrangling with Python Project

This course is part of Data Wrangling with Python Specialization

Instructor: Di Wu

Access provided by University of California, Irvine

5 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

3 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

5 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

3 weeks to complete

at 10 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.

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

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

There are 5 modules in this course

The "Data Wrangling Project" course provides students with an opportunity to apply the knowledge gained throughout the specialization in a real-life data wrangling project of their interest. Participants will follow the data wrangling pipeline step by step, from identifying data sources to processing and integrating data, to achieve a fine dataset ready for analysis. This course enables students to gain hands-on experience in the data wrangling process and prepares them to handle complex data challenges in real-world scenarios.

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.