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.
Data Wrangling with Python Project
Data Wrangling with Python Project
This course is part of Data Wrangling with Python Specialization
Instructor: Di Wu
Included with 
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
Shareable certificate
Add to your LinkedIn profile
Assessments
5 assignments
Taught in English
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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.
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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
Offered by
Recommended if you're interested in Data Analysis
Duke University
University of Michigan
University of Michigan
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