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Data Analysis and Representation, Selection and Iteration

Approx. 11 hours to complete

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Course Summary

Learn how to represent and analyze data in Python using various techniques including selection and iteration. This course covers the basics of data analysis and is great for beginners who want to gain skills in Python programming.

Key Learning Points

Understand data analysis and its importance
Learn how to represent data using Python
Master techniques like selection and iteration to analyze data

Learning Outcomes

Understand the basics of data analysis
Gain proficiency in Python programming
Learn how to represent and analyze data using Python

Prerequisites or good to have knowledge before taking this course

Basic knowledge of programming concepts
A computer with internet access

Course Difficulty Level

Beginner

Course Format

Online
Self-paced

Similar Courses

Data Science Essentials
Python Data Structures
Applied Data Science with Python

Notable People in This Field

DataCamp
Kaggle
Dataquest

Related Books

Description

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

Outline

DATA ANALYSIS
Course Introduction
Navigating a Coursera Course
Meet the Instructor (optional)
Lesson Introduction
Mean and Standard Deviation, Part 1
Mean and Standard Deviation, Part 2
Fictional Drug Trials
Continuous vs Discrete Data
Spelling Errors
Data Analysis Topic Understanding Check
Data Analysis Practice Quiz
Data Analysis Graded Quiz

Selection
Lesson Introduction
If Statements
The Danger of Equals
Switch Statements
Exercise 1: If Statements
Exercise 2: Switch Statements
Selection Lecture Code
Number Characteristics Solution

Data Representation
Lesson Introduction
Histograms
Bar Charts
Line Graphs
Pie Charts
Scatterplots
Super Cool Representations
Data Representation Topic Understanding Check
Data Representation Practice Quiz
Data Representation Graded Quiz

Iteration
Lesson Introduction
For Loops
Nested For Loops
While Loops
Do-While Loops
Nesting and Boxes
Finishing Up
Exercise 3: For Loops
Exercise 4: While Loops
Iteration Lecture Code
When Will They Stop Solution

Summary of User Reviews

The Data Analysis: Representation, Selection, and Iteration course on Coursera has received positive reviews from learners who found it to be an informative and comprehensive course on data analysis. Many users appreciated the well-structured course content and the hands-on approach to learning.

Key Aspect Users Liked About This Course

The hands-on approach to learning was a key aspect that many users thought was good.

Pros from User Reviews

Well-structured course content
Great hands-on approach to learning
Informative and comprehensive course on data analysis
Engaging and knowledgeable instructors
Practical exercises and assignments that help learners apply what they have learned

Cons from User Reviews

Some users found the course to be too technical
A few learners reported that the course moved too fast
The course may not be suitable for beginners with no prior knowledge of data analysis
The quizzes and exams were challenging for some learners
Some users experienced technical difficulties with the platform

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