EdX

Python for Data Science Project (edX)

Offered by IBM,
Python for Data Science Project (edX)

This mini-course is intended for you to demonstrate foundational Python skills for working with data. This mini-course is intended for you to demonstrate foundational Python skills for working with data. The completion of this course involves working on a hands-on project where you will develop a simple dashboard using Python.

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

This course is part of the following programs:

What you'll learn
In this course you will learn about:

  • Demonstrate your skills for working with Python and Data
  • Create a dashboard that shows key performance indicators from a specific data set

Syllabus

Module 1 - Intro to Web Scraping (optional)
Module 2 - Final Project: Analyzing Stock Performance and Building a Dashboard
Peer assignment

Prerequisites:
Python Basics for Data Science course from IBM is a pre-requisite for this project course. Please ensure that before taking this course you have either completed the Python Basics for Data Science course from IBM or have equivalent proficiency in working with Python and data.

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

Related Courses

Computing in Python IV: Objects & Algorithms (edX) EdX
Georgia Institute of Technology,GTx

Computing in Python IV: Objects & Algorithms (edX)

CS: Programming

Learn about recursion, search and sort algorithms, and object-oriented programming in Python. Complete your introductory knowledge of computer science with this final course on objects and algorithms. Now that you've learned about complex control structures and data structures, learn to develop programs that more intuitively leverage your natural understanding of problems through object-oriented programming. Then, learn to analyze the complexity and efficiency of these programs through algorithms. In addition, certify your broader knowledge of Introduction to Computing with a comprehensive exam.

Self Paced
Self-Paced
Programming Python Computing
Details
SQL for Data Science (edX) EdX
IBM

SQL for Data Science (edX)

Statistics & Data Analysis Data Science

Learn how to use and apply the powerful language of SQL to better communicate and extract data from databases - a must for anyone working in the data science field. Much of the world's data lives in databases. SQL (or Structured Query Language) is a powerful programming language that is used for communicating with and extracting various data types from databases.

Self Paced
Self-Paced
Python Databases SQL
Details
Programming for Data Science (edX) EdX
University of Adelaide,AdelaideX

Programming for Data Science (edX)

CS: Programming Data Science

Learn how to apply fundamental programming concepts, computational thinking and data analysis techniques to solve real-world data science problems. There is a rising demand for people with the skills to work with Big Data sets and this course can start you on your journey through our Big Data MicroMasters program towards a recognised credential in this highly competitive area. Using practical activities you will learn how digital technologies work and will develop your coding skills through engaging and collaborative assignments.

Self Paced
Self-Paced
Programming Big Data Data Analysis
Details
Data Science and Machine Learning Capstone Project (edX) EdX
IBM

Data Science and Machine Learning Capstone Project (edX)

Statistics & Data Analysis Data Science

Create a project that you can use to showcase your Data Science skills to prospective employers. Apply various data science and machine learning techniques to analyze and visualize a data set involving a real life business scenario and build a predictive model. Now that you've taken several courses on data science and machine learning, it’s time to put your learning to work on a data problem involving a real life scenario. Employers really care about how well you can apply your knowledge and skills to solve real world problems, and the work you do in this capstone project will make you stand out in the job market.

Self Paced
Self-Paced
Python Machine Learning Data Science
Details
Data Science: Probability (edX) EdX
HarvardX,Harvard University

Data Science: Probability (edX)

Statistics & Data Analysis Data Science

Learn probability theory — essential for a data scientist — using a case study on the financial crisis of 2007–2008. In this course, you will learn valuable concepts in probability theory. The motivation for this course is the circumstances surrounding the financial crisis of 2007–2008. Part of what caused this financial crisis was that the risk of some securities sold by financial institutions was underestimated. To begin to understand this very complicated event, we need to understand the basics of probability.

Self Paced
Self-Paced
Probability Monte Carlo Method Data Science
Details
Visualización de Datos y Storytelling (edX) EdX
Tecnológico de Monterrey,TecdeMonterreyX

Visualización de Datos y Storytelling (edX)

Engineering Statistics & Data Analysis

Aprende en este curso en línea que es la visualización de datos, sus usos; los elementos que la conforman y la forma de poder utilizarla para el apoyo en la toma de las mejores decisiones para las empresas basadas en el análisis de datos. Digamos que necesitas comprender big data; miles o incluso millones de filas de datos, y tienes poco tiempo para hacerlo. los datos pueden provenir de tu equipo, en cuyo caso tal vez ya estés familiarizado con lo que estás midiendo y de los resultados que se esperan. O puede provenir de otro equipo, o tal vez de varios equipos a la vez, y estar completamente familiarizado.

Self Paced
Self-Paced
Big Data Storytelling Data Science
Details
Statistics Using Python (edX) EdX
University of Wisconsin–Madison,WisconsinX

Statistics Using Python (edX)

Statistics & Data Analysis CS: Programming

Learn the fundamentals of statistics using Python. This course is a compact primer in statistics as a foundation for data-driven business analysis. A selection of concepts include descriptive statistics, probability, inference, correlation, and regression. The course also exposes students to basic Python programming for use in statistics.

Sep 2nd 2026
5-12 Weeks
Python Statistics Probability
Details