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Charles Ivan Niswander II
It has been said that obtaining and cleaning data constitutes 80% of a data scientists job. Whether it's correcting or replacing missing data, removing duplicate entries, or dealing with outliers, our datasets always require some level of cleaning and reshaping. Doing so improves the accuracy of our results immensely.
In this 2 hour project-based course, we will examine a variety of methods to clean, and reshape any dataset.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/7vjyx3/cleaning
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Focuses on data cleaning and reshaping techniques, which are essential for data scientists
Taught by Charles Ivan Niswander II, a recognized data scientist
Suitable for learners based in North America, indicating relevance to the regional market
Emphasizes hands-on project-based learning, providing practical experience
Offers a concise and focused curriculum, catering to busy learners
Note that the course may not be accessible to learners outside of North America
Save this course
Save Cleaning, Reshaping, and Expanding Datasets in Python to your list so you can find it easily later:
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Reviews summary
Excellent data cleaning course
This course provides many useful and effective techniques for cleaning and reshaping datasets, leading to improved accuracy in results. Based on the reviews, it appears that this course will be most useful to students based in North America.
Helpful course
"Very good course"
Good lecture
"The lecture is very good"
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 Cleaning, Reshaping, and Expanding Datasets in Python with these
activities:
Brush Up on Basic Programming Skills
Show steps
Ensures students have a strong foundation in programming concepts, which is essential for data manipulation and analysis.
Browse courses on
Programming Fundamentals
Show steps
-
Review online tutorials or books on basic programming concepts
-
Complete coding exercises and practice problems
Read 'Data Science for Business'
Show steps
Provides additional insights into the application of data science in business contexts, complementing course content.
View
Data Science for Business: What You Need to...
on Amazon
Show steps
-
Read the book and take notes on key concepts
-
Summarize the main ideas and discuss them with peers
Practice Data Wrangling Exercises
Show steps
Provides hands-on experience in manipulating and cleaning data, enhancing understanding of data wrangling techniques.
Browse courses on
Data Wrangling
Show steps
-
Work through online data wrangling tutorials
-
Complete coding challenges involving data manipulation
Four other activities
Expand to see all activities and additional details
Show all seven activities
Compile a Resource List on Data Cleaning Best Practices
Show steps
Fosters critical thinking by requiring students to research and organize information on best practices in data cleaning.
Show steps
-
Research and gather resources on data cleaning best practices
-
Organize the resources into a comprehensive list
-
Share the list with peers or colleagues
Develop a Data Cleaning Pipeline
Show steps
Applies data cleaning concepts to a real-world dataset, fostering practical understanding of data preparation techniques.
Browse courses on
Data Manipulation
Show steps
-
Select a dataset and identify data quality issues
-
Implement data cleaning algorithms and write code to automate the process
-
Evaluate the effectiveness of the data cleaning pipeline
Create a Presentation on Data Reshaping Techniques
Show steps
Encourages students to synthesize and present their understanding of data reshaping methods, deepening their knowledge.
Browse courses on
Data Reshaping
Show steps
-
Research and gather information on data reshaping techniques
-
Develop a presentation outline and slides
-
Present the findings to peers or colleagues
Follow Tutorials on Advanced Data Manipulation Techniques
Show steps
Enhances understanding of complex data manipulation techniques, extending the skills taught in the course.
Show steps
-
Identify specific data manipulation techniques to focus on
-
Find online tutorials or courses on those techniques
-
Follow the tutorials and complete the exercises
Brush Up on Basic Programming Skills
Show steps
Ensures students have a strong foundation in programming concepts, which is essential for data manipulation and analysis.
Browse courses on
Programming Fundamentals
Show steps
Show steps
Show steps
- Review online tutorials or books on basic programming concepts
- Complete coding exercises and practice problems
Read 'Data Science for Business'
Show steps
Provides additional insights into the application of data science in business contexts, complementing course content.
View
Data Science for Business: What You Need to...
on Amazon
Show steps
Show steps
Show steps
- Read the book and take notes on key concepts
- Summarize the main ideas and discuss them with peers
Practice Data Wrangling Exercises
Show steps
Provides hands-on experience in manipulating and cleaning data, enhancing understanding of data wrangling techniques.
Browse courses on
Data Wrangling
Show steps
Show steps
Show steps
- Work through online data wrangling tutorials
- Complete coding challenges involving data manipulation
Four other activities
Expand to see all activities and additional details
Show all seven activities
Compile a Resource List on Data Cleaning Best Practices
Show steps
Fosters critical thinking by requiring students to research and organize information on best practices in data cleaning.
Show steps
Show steps
Show steps
- Research and gather resources on data cleaning best practices
- Organize the resources into a comprehensive list
- Share the list with peers or colleagues
Develop a Data Cleaning Pipeline
Show steps
Applies data cleaning concepts to a real-world dataset, fostering practical understanding of data preparation techniques.
Browse courses on
Data Manipulation
Show steps
Show steps
Show steps
- Select a dataset and identify data quality issues
- Implement data cleaning algorithms and write code to automate the process
- Evaluate the effectiveness of the data cleaning pipeline
Create a Presentation on Data Reshaping Techniques
Show steps
Encourages students to synthesize and present their understanding of data reshaping methods, deepening their knowledge.
Browse courses on
Data Reshaping
Show steps
Show steps
Show steps
- Research and gather information on data reshaping techniques
- Develop a presentation outline and slides
- Present the findings to peers or colleagues
Follow Tutorials on Advanced Data Manipulation Techniques
Show steps
Enhances understanding of complex data manipulation techniques, extending the skills taught in the course.
Show steps
Show steps
Show steps
- Identify specific data manipulation techniques to focus on
- Find online tutorials or courses on those techniques
- Follow the tutorials and complete the exercises
Career center
Learners who complete Cleaning, Reshaping, and Expanding Datasets in Python will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists use data to solve business problems and develop new products and services. This course provides a comprehensive overview of data cleaning and reshaping techniques, which are essential skills for Data Scientists. By taking this course, you will be well-prepared for a career in data science.
Data Engineer
Data Engineer
Data Engineers design and build data pipelines to collect, clean, and store data. This course provides a comprehensive overview of data cleaning and reshaping techniques, which are essential skills for Data Engineers. By taking this course, you will be well-prepared for a career in data engineering.
Data Analyst
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. This course provides a solid foundation in data cleaning and reshaping techniques, which are essential skills for Data Analysts. By taking this course, you will be well-prepared for a career in data analysis.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build and deploy machine learning models to solve business problems. This course provides a solid foundation in data cleaning and reshaping techniques, which are essential skills for Machine Learning Engineers. By taking this course, you will be well-prepared for a career in machine learning engineering.
Business Analyst
Business Analyst
Business Analysts use data to help businesses improve their operations and make better decisions. This course provides a solid foundation in data cleaning and reshaping techniques, which are essential skills for Business Analysts. By taking this course, you will be well-prepared for a career in business analysis.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists use data to create visual representations of data. This course provides a solid foundation in data cleaning and reshaping techniques, which are essential skills for Data Visualization Specialists. By taking this course, you will be well-prepared for a career in data visualization.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases. This course provides a comprehensive overview of data cleaning and reshaping techniques, which are essential skills for Database Administrators. By taking this course, you will be well-prepared for a career in database administration.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. This course provides a comprehensive overview of data cleaning and reshaping techniques, which are essential skills for Statisticians. By taking this course, you will be well-prepared for a career in statistics.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use data to improve the efficiency of operations. This course provides a solid foundation in data cleaning and reshaping techniques, which are essential skills for Operations Research Analysts. By taking this course, you will be well-prepared for a career in operations research.
Financial Analyst
Financial Analyst
Financial Analysts use data to make investment decisions. This course provides a solid foundation in data cleaning and reshaping techniques, which are essential skills for Financial Analysts. By taking this course, you will be well-prepared for a career in financial analysis.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course provides a solid foundation in data cleaning and reshaping techniques, which are essential skills for Software Engineers. By taking this course, you will be well-prepared for a career in software engineering.
Biostatistician
Biostatistician
Biostatisticians use data to solve problems in biology and medicine. This course provides a solid foundation in data cleaning and reshaping techniques, which are essential skills for Biostatisticians. By taking this course, you will be well-prepared for a career in biostatistics.
Actuary
Actuary
Actuaries use data to assess risk and uncertainty. This course provides a comprehensive overview of data cleaning and reshaping techniques, which are essential skills for Actuaries. By taking this course, you will be well-prepared for a career in actuarial science.
Market Researcher
Market Researcher
Market Researchers collect and analyze data about consumer behavior. This course provides a comprehensive overview of data cleaning and reshaping techniques, which are essential skills for Market Researchers. By taking this course, you will be well-prepared for a career in market research.
Web Developer
Web Developer
Web Developers design and develop websites. This course provides a comprehensive overview of data cleaning and reshaping techniques, which are essential skills for Web Developers. By taking this course, you will be well-prepared for a career in web development.
For more career information including salaries, visit:
OpenCourser.com/course/7vjyx3/cleaning
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
Cleaning, Reshaping, and Expanding Datasets in Python.
Save
Provides a comprehensive overview of data cleaning techniques and best practices. It valuable resource for anyone who wants to learn how to clean data effectively.
Provides a comprehensive overview of Python programming for data analysis. It valuable resource for anyone who wants to learn how to use Python for data analysis.
Save
Provides a comprehensive overview of deep learning. It valuable resource for anyone who wants to learn about deep learning.
Provides a comprehensive overview of data science. It valuable resource for anyone who wants to learn about data science.
Provides a comprehensive overview of data science for business. It valuable resource for anyone who wants to learn about data science for business.
Provides a comprehensive overview of data science for beginners. It valuable resource for anyone who wants to learn about data science.
Provides a comprehensive overview of data science with Python. It valuable resource for anyone who wants to learn about data science with Python.
Save
Provides a comprehensive overview of data science with R. It valuable resource for anyone who wants to learn about data science with R.
Provides a comprehensive overview of data science with Go. It valuable resource for anyone who wants to learn about data science with Go.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/7vjyx3/cleaning
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Time
2 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Charles Ivan Niswander II
Good to know
Focuses on data cleaning and reshaping techniques, which are essential for data scientists
Taught by Charles Ivan Niswander II, a recognized data scientist
Suitable for learners based in North America, indicating relevance to the regional market
Emphasizes hands-on project-based learning, providing practical experience
Offers a concise and focused curriculum, catering to busy learners
Note that the course may not be accessible to learners outside of North America
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