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Di Wu
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.
Read more
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.
Read more
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.
Throughout the course, students will work on their data wrangling project, applying the knowledge and skills gained in each module to achieve a refined and well-prepared dataset. By the end of the course, participants will be proficient in the data wrangling process and ready to tackle real-world data challenges in diverse domains.
Register for this course and see more details by visiting:
OpenCourser.com/course/1fq3se/data
What's inside
Syllabus
Data Wrangling Pipeline
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.
Read more
Syllabus
Data Wrangling Pipeline
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.
Read more
Identify Your Data
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.
Data Collection and Integration
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.
Data Understanding and Visualization
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).
Data Processing and Manipulation
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.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops hands-on experience in data wrangling, a skill useful in diverse domains
Provides a comprehensive study of the data wrangling pipeline, a standard in the industry
Builds a strong foundation for beginners to master data wrangling
Save this course
Save Data Wrangling with Python Project to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Data Wrangling with Python Project with these
activities:
Review Linear Regression
Show steps
Review the basics of linear regression to strengthen your foundation for data wrangling.
Browse courses on
Linear Regression
Show steps
-
Go over your notes on linear regression from previous courses.
-
Solve practice problems involving linear regression.
-
Watch online tutorials on linear regression.
Explore Data Visualization Techniques
Show steps
Follow tutorials on data visualization techniques to enhance your ability to present data effectively.
Show steps
-
Identify different types of data visualizations.
-
Learn how to choose the appropriate visualization for different types of data.
-
Practice creating visualizations using online tools.
Develop a Data Wrangling Pipeline
Show steps
Create a step-by-step guide on the data wrangling pipeline to solidify your understanding of the process.
Show steps
-
Identify the different stages of the data wrangling pipeline.
-
Describe the tools and techniques used in each stage.
-
Provide examples of real-world scenarios where the pipeline is applied.
-
Share your guide with classmates for feedback.
Three other activities
Expand to see all activities and additional details
Show all six activities
Data Cleaning Exercises
Show steps
Practice data cleaning skills to improve your ability to handle messy datasets.
Show steps
-
Find datasets with common data quality issues.
-
Clean the datasets using appropriate techniques.
-
Validate the cleaned datasets for accuracy.
Attend Data Science Meetups
Show steps
Connect with industry professionals and learn about real-world data wrangling challenges.
Show steps
-
Find local data science meetups.
-
Attend meetups and participate in discussions.
-
Network with other data scientists.
Participate in Data Wrangling Workshops
Show steps
Gain hands-on experience in data wrangling techniques through workshops.
Show steps
-
Look for data wrangling workshops offered by universities or online platforms.
-
Register for a workshop that aligns with your interests.
-
Attend the workshop and actively participate in exercises.
Review Linear Regression
Show steps
Review the basics of linear regression to strengthen your foundation for data wrangling.
Browse courses on
Linear Regression
Show steps
Show steps
Show steps
- Go over your notes on linear regression from previous courses.
- Solve practice problems involving linear regression.
- Watch online tutorials on linear regression.
Explore Data Visualization Techniques
Show steps
Follow tutorials on data visualization techniques to enhance your ability to present data effectively.
Show steps
Show steps
Show steps
- Identify different types of data visualizations.
- Learn how to choose the appropriate visualization for different types of data.
- Practice creating visualizations using online tools.
Develop a Data Wrangling Pipeline
Show steps
Create a step-by-step guide on the data wrangling pipeline to solidify your understanding of the process.
Show steps
Show steps
Show steps
- Identify the different stages of the data wrangling pipeline.
- Describe the tools and techniques used in each stage.
- Provide examples of real-world scenarios where the pipeline is applied.
- Share your guide with classmates for feedback.
Three other activities
Expand to see all activities and additional details
Show all six activities
Data Cleaning Exercises
Show steps
Practice data cleaning skills to improve your ability to handle messy datasets.
Show steps
Show steps
Show steps
- Find datasets with common data quality issues.
- Clean the datasets using appropriate techniques.
- Validate the cleaned datasets for accuracy.
Attend Data Science Meetups
Show steps
Connect with industry professionals and learn about real-world data wrangling challenges.
Show steps
Show steps
Show steps
- Find local data science meetups.
- Attend meetups and participate in discussions.
- Network with other data scientists.
Participate in Data Wrangling Workshops
Show steps
Gain hands-on experience in data wrangling techniques through workshops.
Show steps
Show steps
Show steps
- Look for data wrangling workshops offered by universities or online platforms.
- Register for a workshop that aligns with your interests.
- Attend the workshop and actively participate in exercises.
Career center
Learners who complete Data Wrangling with Python Project will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts use their skills in data collection, processing, and visualization to help organizations make informed decisions. This course provides a strong foundation in these areas, making it an excellent choice for those looking to enter or advance in this field. The course's focus on real-world projects also gives you the practical experience you need to succeed in this role.
Data Engineer
Data Engineer
Data Engineers design and build the systems that store and process data. This course provides a strong foundation in data wrangling, which is a critical skill for Data Engineers. The course's focus on real-world projects also gives you the practical experience you need to succeed in this role.
Data Scientist
Data Scientist
Data Scientists use their expertise in data wrangling, machine learning, and statistics to solve complex business problems. This course provides a solid foundation in data wrangling, which is a critical skill for Data Scientists. The course's focus on real-world projects also gives you the practical experience you need to succeed in this role.
Business Analyst
Business Analyst
Business Analysts use their skills in data analysis and visualization to help businesses understand their data and make better decisions. This course provides a strong foundation in data wrangling, which is a critical skill for Business Analysts. The course's focus on real-world projects also gives you the practical experience you need to succeed in this role.
Project Manager
Project Manager
Project Managers plan and execute projects, ensuring that they are completed on time, within budget, and to the required quality. This course provides a strong foundation in data wrangling, which is a critical skill for Project Managers. The course's focus on real-world projects also gives you the practical experience you need to succeed in this role.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists create visual representations of data to help businesses understand their data and make better decisions. This course provides a strong foundation in data wrangling, which is a critical skill for Data Visualization Specialists. The course's focus on real-world projects also gives you the practical experience you need to succeed in this role.
Data Journalist
Data Journalist
Data Journalists use their skills in data analysis and visualization to tell stories with data. This course provides a strong foundation in data wrangling, which is a critical skill for Data Journalists. The course's focus on real-world projects also gives you the practical experience you need to succeed in this role.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use their skills in data analysis and optimization to improve the efficiency of organizations. This course provides a strong foundation in data wrangling, which is a critical skill for Operations Research Analysts. The course's focus on real-world projects also gives you the practical experience you need to succeed in this role.
Data Architect
Data Architect
Data Architects design and manage the architecture of data systems. This course provides a strong foundation in data wrangling, which is a critical skill for Data Architects. The course's focus on real-world projects also gives you the practical experience you need to succeed in this role.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course provides a strong foundation in data wrangling, which is a valuable skill for Software Engineers. The course's focus on real-world projects also gives you the practical experience you need to succeed in this role.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases. This course provides a strong foundation in data wrangling, which is a critical skill for Database Administrators. The course's focus on real-world projects also gives you the practical experience you need to succeed in this role.
Quantitative Researcher
Quantitative Researcher
Quantitative Researchers use their skills in data analysis and modeling to solve complex problems. This course provides a strong foundation in data wrangling, which is a critical skill for Quantitative Researchers. The course's focus on real-world projects also gives you the practical experience you need to succeed in this role.
Market Researcher
Market Researcher
Market Researchers use their skills in data collection and analysis to understand consumer behavior. This course provides a strong foundation in data wrangling, which is a valuable skill for Market Researchers. The course's focus on real-world projects also gives you the practical experience you need to succeed in this role.
Financial Analyst
Financial Analyst
Financial Analysts use their skills in data analysis and modeling to make investment recommendations. This course provides a strong foundation in data wrangling, which is a valuable skill for Financial Analysts. The course's focus on real-world projects also gives you the practical experience you need to succeed in this role.
Actuary
Actuary
Actuaries use their skills in mathematics and statistics to assess risk and uncertainty. This course provides a strong foundation in data wrangling, which is a valuable skill for Actuaries. The course's focus on real-world projects also gives you the practical experience you need to succeed in this role.
For more career information including salaries, visit:
OpenCourser.com/course/1fq3se/data
Reading list
We've selected nine books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Data Wrangling with Python Project.
Delves into the Pandas library, a popular tool for data manipulation and analysis in Python. It offers insights into advanced data wrangling techniques, making it a valuable reference for those seeking a deeper understanding of the concepts discussed in the course.
This comprehensive guide covers data analysis techniques using Python, providing a solid foundation for understanding the principles and practices of data wrangling. It complements the course by offering additional insights and examples.
This handbook provides a comprehensive overview of data science tools and practices in Python. It offers a broad perspective on data wrangling, analysis, and visualization, enhancing the knowledge gained in the course.
Offers a foundational approach to data science using Python. It covers essential concepts and techniques, providing a solid basis for understanding the principles of data wrangling discussed in the course.
Save
While this book primarily focuses on data science in R, it offers insights into data wrangling techniques that can be valuable for those working with Python. It provides a complementary perspective, expanding the scope of the course's coverage.
Covers machine learning and deep learning in Python. While it does not directly focus on data wrangling, it provides valuable insights into the end goal of the data wrangling process: preparing data for analysis and modeling.
Provides a mathematical foundation for data analysis. It covers linear algebra concepts that are essential for understanding the theory behind data wrangling techniques.
Introduces Bayesian statistics using Python. While it does not directly focus on data wrangling, it offers valuable insights into the statistical principles that underlie data analysis.
This textbook provides a comprehensive overview of statistical inference. It offers a theoretical foundation for the statistical methods used in data wrangling and analysis.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/1fq3se/data
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Data Wrangling with Python 3
Effort
5-7 hours/week
Level
Intermediate
Via
Coursera
Institution
University of Colorado Boulder
Instructor
Di Wu
Language
English
This course belongs to a
collection
called
Data Wrangling with Python. It's comprised of five courses:
- Data Collection and Integration
- Data Processing and Manipulation
- Fundamental Tools of Data Wrangling
- Data Understanding and Visualization
- Data Wrangling with Python Project (viewing)
Good to know
Develops hands-on experience in data wrangling, a skill useful in diverse domains
Provides a comprehensive study of the data wrangling pipeline, a standard in the industry
Builds a strong foundation for beginners to master data wrangling
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