Data Analysis and Representation, Selection and Iteration

 

Overview

Focus: The course typically introduces foundational concepts of data analysis in Python, including how to represent, select, and iterate over data structures.

Key Topics:

Data Representation:

Introduction to basic Python data types like integers, strings, lists, dictionaries, and arrays.

Selection:

Conditional logic (if, elif, else) for filtering and selecting data.

Iteration:

Loops (for and while) to process datasets effectively.

Iteration through lists, dictionaries, and other data structures.

Features

• Hands-on coding exercises using tools like Jupyter Notebook.
• Focus on foundational programming and data manipulation skills.
• Introduction to libraries like NumPy and pandas (in some courses).

Build your subject-matter expertise

This course is part of the Computational Thinking with Beginning C Programming Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts

Gain a foundational understanding of a subject or tool

Develop job-relevant skills with hands-on projects

Earn a shareable career certificate

Ideal for

• Beginners in Python looking to build a strong foundation in data analysis.
• Students or professionals wanting to develop essential programming skills for working with data.

Join Free : Data Analysis and Representation, Selection and Iteration

There are 4 modules in this course

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