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Dr. Tim "Dr. T" Chamillard
This course is the second course in the specialization exploring both computational thinking and beginning C programming. Rather than trying to define computational thinking, we’ll just say it’s a problem-solving process that includes lots of different components. Most people have a better understanding of what beginning C programming means!
Read more
This course is the second course in the specialization exploring both computational thinking and beginning C programming. Rather than trying to define computational thinking, we’ll just say it’s a problem-solving process that includes lots of different components. Most people have a better understanding of what beginning C programming means!
Read more
This course is the second course in the specialization exploring both computational thinking and beginning C programming. Rather than trying to define computational thinking, we’ll just say it’s a problem-solving process that includes lots of different components. Most people have a better understanding of what beginning C programming means!
This course assumes you have the prerequisite knowledge from the previous course in the specialization. You should make sure you have that knowledge, either by taking that previous course or from personal experience, before tackling this course. The required prerequisite knowledge is listed below.
Prerequisite computational thinking knowledge: Algorithms and procedures, data collection
Prerequisite C knowledge: Data types, variables, constants, and STEM computations
Throughout this course you'll learn about data analysis and data representation, which are computational thinking techniques that help us understand what sets of data have to tell us. For the programming topics, you'll continue building on your C knowledge by implementing selection, which lets us decide which code to execute, and iteration (or looping), which lets us repeat chunks of code multiple times.
Module 1: Learn about some common statistics we can calculate as we analyze sets of data
Module 2: Discover how we make decisions in our code
Module 3: Explore the various ways we can represent sets of data
Module 4: Use iteration (looping) to repeat actions in your code
Register for this course and see more details by visiting:
OpenCourser.com/course/a5s4qm/data
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What's inside
Syllabus
DATA ANALYSIS
Selection
Data Representation
Read more
Syllabus
DATA ANALYSIS
Selection
Data Representation
Read more
Iteration
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Builds a strong foundation in computational thinking techniques such as data analysis and data representation
Focuses on developing computational skills, including algorithms, data visualization, and data analysis techniques
Targets students with a foundational knowledge of computational thinking and C programming
Prerequisites may be a barrier to entry for some learners without prior experience
Requires proficiency in data analysis and data representation techniques
Save this course
Save Data Analysis and Representation, Selection and Iteration to your list so you can find it easily later:
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Reviews summary
Useful data representation course
Learners say this course is a useful course for understanding data representation and programming using C. Students remark that the lectures are informative and well explained. However, learners caution that the auto-grader needs fixing and the last assignment is too difficult compared to the rest of the course materials.
Learners find this course useful.
"Good for beginners."
"Very Interesting and Informative"
"Great course."
"Great course for learning C programming"
The course teaches C programming.
"50% Excel spreadsheets (+graphs) 50% C coding."
"Great course. Dr. Tim is excellent professor, explanations are very clear and useful"
"Great course for learning C programming"
Learners find the lectures informative and helpful.
"had nice experience of taking this course."
"Thank you Sir for this informative course."
"Dr. Tim is excellent professor, explanations are very clear and useful"
The last assignment is too challenging.
"the last assignment was super hard, and was kind of not covered through the course!"
Learners report issues with the auto-grader.
"The auto-grader needs to be fixed."
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 Analysis and Representation, Selection and Iteration with these
activities:
Review previous course material
Show steps
Revisiting previous course material will help strengthen your foundation for this course.
Browse courses on
Computational Thinking
Show steps
-
Review your notes, assignments, and quizzes from the previous course.
-
Complete practice problems or exercises related to the prerequisite topics.
Review basic programming concepts
Show steps
To ensure success in this course, it is beneficial to brush up on the basics of programming.
Browse courses on
C Programming
Show steps
-
Review online tutorials or textbooks on basic programming concepts.
-
Complete practice exercises to test your understanding.
Host a study session
Show steps
Hosting a study session allows you to reinforce your understanding and assist your peers.
Show steps
-
Gather a group of classmates who are also taking the course.
-
Choose a topic from the course material to focus on.
-
Lead the session, reviewing the concepts and facilitating discussions.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Re-implement past exercises
Show steps
Practice is crucial to enhancing problem-solving abilities and solidifying fundamental concepts.
Browse courses on
Problem Solving
Show steps
-
Select a series of exercises from previous lessons.
-
Re-implement the solutions independently.
-
Review your solutions against the original solutions.
-
Identify and address any discrepancies or areas for improvement.
Explore data visualization techniques
Show steps
Data visualization helps make data more comprehensible and enables us to identify patterns and insights.
Browse courses on
Data Representation
Show steps
-
Find online tutorials or courses on data visualization.
-
Follow the tutorials and experiment with different visualization techniques.
-
Apply these techniques to analyze and present data from the course.
Attempt online coding challenges
Show steps
Coding challenges provide a platform to refine your coding skills and solve real-world problems.
Browse courses on
C Programming
Show steps
-
Find online coding platforms such as LeetCode or HackerRank.
-
Select challenges that align with the topics covered in the course.
-
Attempt to solve the challenges independently.
-
Review your solutions and identify areas for improvement.
Develop a data analysis project
Show steps
A project provides an opportunity to apply your understanding of data analysis and visualization in a practical setting.
Browse courses on
Data Analysis
Show steps
-
Identify a dataset related to the course topics.
-
Analyze the data using techniques covered in the course.
-
Visualize the data using appropriate techniques.
-
Present your findings in a clear and concise manner.
Review previous course material
Show steps
Revisiting previous course material will help strengthen your foundation for this course.
Browse courses on
Computational Thinking
Show steps
Show steps
Show steps
- Review your notes, assignments, and quizzes from the previous course.
- Complete practice problems or exercises related to the prerequisite topics.
Review basic programming concepts
Show steps
To ensure success in this course, it is beneficial to brush up on the basics of programming.
Browse courses on
C Programming
Show steps
Show steps
Show steps
- Review online tutorials or textbooks on basic programming concepts.
- Complete practice exercises to test your understanding.
Host a study session
Show steps
Hosting a study session allows you to reinforce your understanding and assist your peers.
Show steps
Show steps
Show steps
- Gather a group of classmates who are also taking the course.
- Choose a topic from the course material to focus on.
- Lead the session, reviewing the concepts and facilitating discussions.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Re-implement past exercises
Show steps
Practice is crucial to enhancing problem-solving abilities and solidifying fundamental concepts.
Browse courses on
Problem Solving
Show steps
Show steps
Show steps
- Select a series of exercises from previous lessons.
- Re-implement the solutions independently.
- Review your solutions against the original solutions.
- Identify and address any discrepancies or areas for improvement.
Explore data visualization techniques
Show steps
Data visualization helps make data more comprehensible and enables us to identify patterns and insights.
Browse courses on
Data Representation
Show steps
Show steps
Show steps
- Find online tutorials or courses on data visualization.
- Follow the tutorials and experiment with different visualization techniques.
- Apply these techniques to analyze and present data from the course.
Attempt online coding challenges
Show steps
Coding challenges provide a platform to refine your coding skills and solve real-world problems.
Browse courses on
C Programming
Show steps
Show steps
Show steps
- Find online coding platforms such as LeetCode or HackerRank.
- Select challenges that align with the topics covered in the course.
- Attempt to solve the challenges independently.
- Review your solutions and identify areas for improvement.
Develop a data analysis project
Show steps
A project provides an opportunity to apply your understanding of data analysis and visualization in a practical setting.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Identify a dataset related to the course topics.
- Analyze the data using techniques covered in the course.
- Visualize the data using appropriate techniques.
- Present your findings in a clear and concise manner.
Career center
Learners who complete Data Analysis and Representation, Selection and Iteration will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to help businesses make better decisions. This course will provide you with the skills and knowledge you need to succeed in this role, including data analysis techniques, data representation methods, and programming skills in C. By taking this course, you will be well-positioned to enter or advance your career as a Data Analyst.
Statistician
Statistician
Statisticians collect, analyze, and interpret data to provide insights and make predictions. This course will provide you with the skills and knowledge you need to succeed in this role, including data analysis techniques, data representation methods, and programming skills in C. By taking this course, you will be well-positioned to enter or advance your career as a Statistician.
Data Scientist
Data Scientist
Data Scientists use data to solve business problems and make predictions. This course will provide you with the skills and knowledge you need to succeed in this role, including data analysis techniques, data representation methods, and programming skills in C. By taking this course, you will be well-positioned to enter or advance your career as a Data Scientist.
Data Engineer
Data Engineer
Data Engineers design and build data systems to manage and process large amounts of data. This course will provide you with the skills and knowledge you need to succeed in this role, including data analysis techniques, data representation methods, and programming skills in C. By taking this course, you will be well-positioned to enter or advance your career as a Data Engineer.
Business Analyst
Business Analyst
Business Analysts use data to analyze business processes and identify opportunities for improvement. This course will provide you with the skills and knowledge you need to succeed in this role, including data analysis techniques, data representation methods, and programming skills in C. By taking this course, you will be well-positioned to enter or advance your career as a Business Analyst.
Market Researcher
Market Researcher
Market Researchers collect and analyze data to understand consumer behavior and trends. This course will provide you with the skills and knowledge you need to succeed in this role, including data analysis techniques, data representation methods, and programming skills in C. By taking this course, you will be well-positioned to enter or advance your career as a Market Researcher.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make predictions. This course will provide you with the skills and knowledge you need to succeed in this role, including data analysis techniques, data representation methods, and programming skills in C. By taking this course, you will be well-positioned to enter or advance your career as a Quantitative Analyst.
Actuary
Actuary
Actuaries use mathematics and statistics to assess risk and make financial decisions. This course will provide you with the skills and knowledge you need to succeed in this role, including data analysis techniques, data representation methods, and programming skills in C. By taking this course, you will be well-positioned to enter or advance your career as an Actuary.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use data to improve business performance. This course will provide you with the skills and knowledge you need to succeed in this role, including data analysis techniques, data representation methods, and programming skills in C. By taking this course, you will be well-positioned to enter or advance your career as a Business Intelligence Analyst.
Computer Systems Analyst
Computer Systems Analyst
Computer Systems Analysts design, implement, and maintain computer systems. This course will provide you with the skills and knowledge you need to succeed in this role, including data analysis techniques, data representation methods, and programming skills in C. By taking this course, you will be well-positioned to enter or advance your career as a Computer Systems Analyst.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course will provide you with the skills and knowledge you need to succeed in this role, including data analysis techniques, data representation methods, and programming skills in C. By taking this course, you will be well-positioned to enter or advance your career as a Software Engineer.
Database Administrator
Database Administrator
Database Administrators design, implement, and maintain databases. This course will provide you with the skills and knowledge you need to succeed in this role, including data analysis techniques, data representation methods, and programming skills in C. By taking this course, you will be well-positioned to enter or advance your career as a Database Administrator.
Information Security Analyst
Information Security Analyst
Information Security Analysts protect computer systems and networks from unauthorized access and attacks. This course will provide you with the skills and knowledge you need to succeed in this role, including data analysis techniques, data representation methods, and programming skills in C. By taking this course, you will be well-positioned to enter or advance your career as an Information Security Analyst.
Financial Analyst
Financial Analyst
Financial Analysts analyze financial data to make investment decisions. This course will provide you with the skills and knowledge you need to succeed in this role, including data analysis techniques, data representation methods, and programming skills in C. By taking this course, you will be well-positioned to enter or advance your career as a Financial Analyst.
Risk Analyst
Risk Analyst
Risk Analysts analyze data to identify and assess risks. This course will provide you with the skills and knowledge you need to succeed in this role, including data analysis techniques, data representation methods, and programming skills in C. By taking this course, you will be well-positioned to enter or advance your career as a Risk Analyst.
For more career information including salaries, visit:
OpenCourser.com/course/a5s4qm/data
Reading list
We've selected 12 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 Analysis and Representation, Selection and Iteration.
Provides a clear and entertaining introduction to C programming. It is particularly useful for students with no prior programming experience, and can serve as a valuable reference for the C programming topics covered in this course.
A textbook that explores the fundamental principles of computational thinking. It provides a conceptual framework for understanding the problem-solving techniques covered in this course and can be used as a reference for further study of computational thinking.
A free and open textbook that introduces statistical concepts using Python. While it focuses on Python rather than C, it provides a clear and accessible explanation of statistical methods and can be used as a supplement to this course.
A comprehensive guide to C programming, covering both fundamental concepts and advanced techniques. It can serve as a valuable reference for students looking to expand their knowledge of C beyond the scope of this course.
A textbook that focuses on algorithm design and analysis using C. While it is more advanced than this course, it can serve as a valuable reference for students interested in exploring algorithms and data structures in more depth.
A textbook that introduces big data concepts and techniques. While it is more advanced than this course, it can serve as a valuable reference for students interested in exploring big data and data mining.
A concise and practical guide to modern C programming. It covers the latest features and best practices of C and can serve as a valuable reference for students looking to stay up-to-date with the latest developments in C.
A textbook that introduces discrete mathematics concepts used in computer science. While it does not cover programming, it provides a foundation for understanding computational thinking and can be used as a reference for further study of discrete mathematics.
A free and open textbook providing a foundation for data analysis and computational thinking concepts. While more broadly focused than this course, it complements the prerequisite knowledge assumed in this course.
An introductory textbook on data structures and algorithms, with a focus on C implementation. It provides a deeper understanding of the concepts covered in this course and can be used as a reference for further exploration of these topics.
A textbook that provides an accessible introduction to artificial intelligence. While it does not cover programming, it provides a conceptual framework for understanding the principles of AI and can be used as a reference for further study of the field.
An introductory textbook on data science, covering data analysis, prediction, and machine learning. It provides a broad overview of the field and can serve as a valuable reference for students interested in exploring data science beyond this course.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/a5s4qm/data
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Computational Thinking and Big Data
Level
Introductory
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Coursera
Institution
University of Colorado System
Instructor
Dr. Tim "Dr. T" Chamillard
Language
English
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This course belongs to a
collection
called
Computational Thinking with Beginning C Programming. It's comprised of four courses:
- Abstraction, Problem Decomposition, and Functions
- Simulation, Algorithm Analysis, and Pointers
- Data Analysis and Representation, Selection and Iteration (viewing)
- Algorithms, Data Collection, and Starting to Code
Good to know
Builds a strong foundation in computational thinking techniques such as data analysis and data representation
Focuses on developing computational skills, including algorithms, data visualization, and data analysis techniques
Targets students with a foundational knowledge of computational thinking and C programming
Prerequisites may be a barrier to entry for some learners without prior experience
Requires proficiency in data analysis and data representation techniques
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