Python Programming Fundamentals (Coursera)

Offered by Duke University,
Python Programming Fundamentals (Coursera)

This introductory course is designed for beginners and individuals with limited programming experience who want to embark on their software development or data science journey using Python. Throughout the course, learners will gain a solid understanding of algorithmic thinking, Python syntax, code testing, debugging techniques, and modular code development--essential skills for a successful career in software engineering, development, or data science.

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

By the end of this course, you will learn to:

  • Gain a stepwise approach to problem-solving using algorithms and programming logic.
  • Apply common functions, conditional statements, and loops to build Python scripts and programs.
  • Work with the VS Code programming environment to enhance coding proficiency.
  • Use testing and debugging strategies to ensure code reliability.
  • Perform logical and mathematical operations on datasets.

In the final week of the course you will apply your new algorithm design and programming skills to a data analysis problem: analyzing heart rate data.

What You Will Learn

  • Utilize a Logical Seven Step framework to create algorithms and programs
  • Create useful test cases and efficiently debug Python code.
  • Master Python basics (conditionals, loops, mathematical operators, data types)
  • Develop a Python Program from scratch to solve a given data science problem.

Syllabus

WEEK 1
Algorithm Design
This week, you will learn best practices for developing code in any language by beginning with an algorithm: a stepwise approach to solving a problem. You’ll then apply the concepts by developing your own algorithms and properly identifying when to use specific data types in Python.

WEEK 2
Translating Ideas into Code
This week, you will learn how to take the logical process of algorithm design and translate an algorithm into functional Python code. You will apply this by correctly identifying proper Python syntax for a given algorithm, and then subsequently by creating your own Python program for a given algorithm.

WEEK 3
Validating Your Code
This week, you will learn different approaches to testing Python code, and methods for debugging code. You will apply this by conducting a code review, identifying opportunities to use asserts to debug code, and generating your own test cases.

WEEK 4
Diving Deeper with Lists
This week, you will learn how to filter and perform operations (logical and mathematical) across a given dataset, and how to create modular code that can be used in discrete pieces. You will apply this by writing your own functions to identify a list item with a given property, and writing a program to calculate a set of conclusions from a given dataset.

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

Related Courses

Fundamental Skills in Bioinformatics (Coursera) Coursera
King Abdullah University of Science and Technology (KAUST)

Fundamental Skills in Bioinformatics (Coursera)

The course provides a broad and mainly practical overview of fundamental skills for bioinformatics (and, in general, data analysis). The aim is to support the simultaneous development of quantitative and programming skills for biological and biomedical students with little or no background in programming or quantitative analysis.

Sep 21st 2026
4 Weeks
Machine Learning: Concepts and Applications (Coursera) Coursera
University of Chicago

Machine Learning: Concepts and Applications (Coursera)

This course gives you a comprehensive introduction to both the theory and practice of machine learning. You will learn to use Python along with industry-standard libraries and tools, including Pandas, Scikit-learn, and Tensorflow, to ingest, explore, and prepare data for modeling and then train and evaluate models using a wide variety of techniques. Those techniques include linear regression with ordinary least squares, logistic regression, support vector machines, decision trees and ensembles, clustering, principal component analysis, hidden Markov models, and deep learning.

Sep 21st 2026
5-12 Weeks
Analíticas de Datos con Pandas (Coursera) Coursera
Tecnológico de Monterrey

Analíticas de Datos con Pandas (Coursera)

La analítica de datos ha avanzado considerablemente en los últimos años y ahora existen diversas herramientas que nos permiten realizar tareas o procesos que antes eran complicados de realizar. Gracias a su versatilidad, el lenguaje de programación Python posee una serie de librerías que permiten realizar proyectos de analítica de datos de una forma muy sencilla y una de las librerías más populares es Pandas.

Sep 21st 2026
4 Weeks
Approximation Algorithms (Coursera) Coursera
EIT Digital

Approximation Algorithms (Coursera)

Many real-world algorithmic problems cannot be solved efficiently using traditional algorithmic tools, for example because the problems are NP-hard. The goal of this course is to become familiar with important algorithmic concepts and techniques needed to effectively deal with such problems. These techniques apply when we don't require the optimal solution to certain problems, but an approximation that is close to the optimal solution. We will see how to efficiently find such approximations.

Sep 18th 2026
4 Weeks
Programação para todos (Conceitos básicos de Python) (Coursera) Coursera
University of Michigan

Programação para todos (Conceitos básicos de Python) (Coursera)

Este curso tem como objetivo ensinar a todos os conceitos básicos de programação de computadores usando Python. Abordamos o básico de como criar um programa a partir de uma série de instruções simples em Python. O curso não tem pré-requisitos e evita tudo, exceto a matemática mais simples. Qualquer pessoa com experiência moderada em computadores deve ser capaz de dominar os materiais deste curso. Este curso abordará os capítulos 1 ao 5 do livro “Python para Todos”.

Sep 21st 2026
5-12 Weeks
¡A Programar! Una introducción a la programación (Coursera) Coursera
University of Edinburgh,Universidad ORT Uruguay

¡A Programar! Una introducción a la programación (Coursera)

¿Alguna vez pensaste en crear tus propios juegos de computadora, pero no tenías idea cómo hacerlo o por dónde comenzar? Este curso te enseñará a programar utilizando Scratch, un lenguaje de programación visual muy fácil de usar, y más importante aún, aprenderás los principios fundamentales de la computación para que comiences a pensar como ingeniero/a de software.

Sep 21st 2026
5-12 Weeks
VLSI CAD Part I: Logic (Coursera) Coursera
University of Illinois at Urbana-Champaign

VLSI CAD Part I: Logic (Coursera)

A modern VLSI chip has a zillion parts -- logic, control, memory, interconnect, etc. How do we design these complex chips? Answer: CAD software tools. Learn how to build thesA modern VLSI chip is a remarkably complex beast: billions of transistors, millions of logic gates deployed for computation and control, big blocks of memory, embedded blocks of pre-designed functions designed by third parties (called “intellectual property” or IP blocks). How do people manage to design these complicated chips? Answer: a sequence of computer aided design (CAD) tools takes an abstract description of the chip, and refines it step-wise to a final design.

Sep 21st 2026
5-12 Weeks
Algorithms, Part I (Coursera) Coursera
Princeton University

Algorithms, Part I (Coursera)

This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers elementary data structures, sorting, and searching algorithms. Part II focuses on graph- and string-processing algorithms.

Sep 21st 2026
5-12 Weeks
Architecting Smart IoT Devices (Coursera) Coursera
EIT Digital

Architecting Smart IoT Devices (Coursera)

This course will teach you how to develop an embedded systems device. In order to reduce the time to market, many pre-made hardware and software components are available today. You'll discover all the available hardware and software components, such as processor families, operating systems, boards and networks. You'll also learn how to actually use and integrate these components.

Sep 21st 2026
5-12 Weeks
Laboratório de Programação Orientada a Objetos - Parte 1 (Coursera) Coursera
Universidade de São Paulo, Brasil

Laboratório de Programação Orientada a Objetos - Parte 1 (Coursera)

Este curso apresenta os conceitos mais importantes em torno do paradigma de desenvolvimento mais comum da indústria de software hoje: a Programação Orientação a Objetos (POO). Oferecido pelo Departamento de Ciência da Computação do Instituto de Matemática e Estatística da USP, o curso é voltado para quem já conhece os conceitos básicos de POO e quer se aprofundar no assunto, tornando-se um excelente programador. Ele funciona bem como uma sequência natural aos 2 cursos anteriores do Prof. Fabio Kon do IME-USP no coursera: Introdução à Ciência da Computação com Python.

Sep 21st 2026
5-12 Weeks