Data Analysis and Representation, Selection and Iteration (Coursera)

Data Analysis and Representation, Selection and Iteration (Coursera)

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!

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

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
Course 2 of 4 in the Computational Thinking with Beginning C Programming Specialization.

Syllabus

WEEK 1: Data Analysis
WEEK 2: Selection
WEEK 3: Data Representation
WEEK 4: Iteration

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Effective Problem-Solving and Decision-Making (Coursera) Coursera
University of California, Irvine

Effective Problem-Solving and Decision-Making (Coursera)

Critical thinking – the application of scientific methods and logical reasoning to problems and decisions – is the foundation of effective problem solving and decision making. Critical thinking enables us to avoid common obstacles, test our beliefs and assumptions, and correct distortions in our thought processes. Gain confidence in assessing problems accurately, evaluating alternative solutions, and anticipating likely risks. Learn how to use analysis, synthesis, and positive inquiry to address individual and organizational problems and develop the critical thinking skills needed in today’s turbulent times. Using case studies and situations encountered by class members, explore successful models and proven methods that are readily transferable on-the-job.

Jun 8th 2026
4 Weeks
Six Sigma Advanced Define and Measure Phases (Coursera) Coursera
University System of Georgia

Six Sigma Advanced Define and Measure Phases (Coursera)

This course is for you if you are looking to dive deeper into Six Sigma or strengthen and expand your knowledge of the basic components of green belt level of Six Sigma and Lean. Six Sigma skills are widely sought by employers both nationally and internationally. These skills have been proven to help improve business processes and performance. This course will take you deeper into the principles and tools associated with the "Design" and "Measure" phases of the DMAIC structure of Six Sigma.

Jun 8th 2026
5-12 Weeks
Inferential Statistics (Coursera) Coursera
University of Amsterdam

Inferential Statistics (Coursera)

Inferential statistics are concerned with making inferences based on relations found in the sample, to relations in the population. Inferential statistics help us decide, for example, whether the differences between groups that we see in our data are strong enough to provide support for our hypothesis that group differences exist in general, in the entire population. We will start by considering the basic principles of significance testing: the sampling and test statistic distribution, p-value, significance level, power and type I and type II errors. Then we will consider a large number of statistical tests and techniques that help us make inferences for different types of data and different types of research designs.

Jun 8th 2026
5-12 Weeks
Introducción a Data Science: Programación Estadística con R (Coursera) Coursera
Universidad Nacional Autónoma de México

Introducción a Data Science: Programación Estadística con R (Coursera)

Este curso te proporcionará las bases del lenguaje de programación estadística R, la lengua franca de la estadística, el cual te permitirá escribir programas que lean, manipulen y analicen datos cuantitativos. Te explicaremos la instalación del lenguaje; también verás una introducción a los sistemas base de gráficos y al paquete para graficar ggplot2, para visualizar estos datos. Además también abordarás la utilización de uno de los IDEs más populares entre la comunidad de usuarios de R, llamado RStudio.

Jun 8th 2026
4 Weeks
Fundamentals of GIS (Coursera) Coursera
University of California, Davis

Fundamentals of GIS (Coursera)

Explore the world of spatial analysis and cartography with geographic information systems (GIS). What you will learn: define core geospatial concepts; practice with subset data using selections and feature attributes; create map books using advanced mapping techniques; create layer and map packages.

Jun 8th 2026
4 Weeks
Introduction to Probability and Data with R (Coursera) Coursera
Duke University

Introduction to Probability and Data with R (Coursera)

This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization.

Jun 8th 2026
5-12 Weeks
Data Visualization with Advanced Excel (Coursera) Coursera
PwC

Data Visualization with Advanced Excel (Coursera)

In this course, you will get hands-on instruction of advanced Excel 2013 functions. You’ll learn to use PowerPivot to build databases and data models. We’ll show you how to perform different types of scenario and simulation analysis and you’ll have an opportunity to practice these skills by leveraging some of Excel's built in tools including, solver, data tables, scenario manager and goal seek.

Jun 8th 2026
4 Weeks
Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud (Coursera) Coursera
University of Illinois at Urbana-Champaign

Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud (Coursera)

Welcome to the Cloud Computing Applications course, the second part of a two-course series designed to give you a comprehensive view on the world of Cloud Computing and Big Data! In this second course we continue Cloud Computing Applications by exploring how the Cloud opens up data analytics of huge volumes of data that are static or streamed at high velocity and represent an enormous variety of information. Cloud applications and data analytics represent a disruptive change in the ways that society is informed by, and uses information.

Jun 8th 2026
4 Weeks
Marketing Analytics (Coursera) Coursera
University of Virginia

Marketing Analytics (Coursera)

Organizations large and small are inundated with data about consumer choices. But that wealth of information does not always translate into better decisions. Knowing how to interpret data is the challenge -- and marketers in particular are increasingly expected to use analytics to inform and justify their decisions. Marketing analytics enables marketers to measure, manage and analyze marketing performance to maximize its effectiveness and optimize return on investment (ROI). Beyond the obvious sales and lead generation applications, marketing analytics can offer profound insights into customer preferences and trends, which can be further utilized for future marketing and business decisions.

Jun 8th 2026
5-12 Weeks
Infonomics II: Business Information Management and Measurement (Coursera) Coursera
University of Illinois at Urbana-Champaign

Infonomics II: Business Information Management and Measurement (Coursera)

Even decades into the Information Age, accounting practices yet fail to recognize the financial value of information. Moreover, traditional asset management practices fail to recognize information as an asset to be managed with earnest discipline. This has led to a business culture of complacence, and the inability for most organizations to fully leverage available information assets. This second course in the two-part Infonomics series explores how and why to adapt well-honed asset management principles and practices to information, and how to apply accepted and new valuation models to gauge information’s potential and realized economic benefits.

Jun 10th 2026
4 Weeks
More C# Programming and Unity (Coursera) Coursera
University of Colorado System

More C# Programming and Unity (Coursera)

This course is the second course in the specialization about learning how to develop video games using the C# programming language and the Unity game engine on Windows or Mac. Why use C# and Unity instead of some other language and game engine? Well, C# is a really good language for learning how to program and then programming professionally. Also, the Unity game engine is very popular with indie game developers; Unity games were downloaded 16,000,000,000 times in 2016! Finally, C# is one of the programming languages you can use in the Unity environment.

Jun 8th 2026
4 Weeks