554 Part-time Short courses in Data Science & Big Data

Get to grips with the General Data Protection Regulation and take the first steps to ensuring that your organisation is compliant with this Understanding the GDPR course from University of Groningen by FutureLearn.

This Data Science - Foundations using R Specialization offered by Coursera in partnership with Johns Hopkins University covers foundational data science tools and techniques, including getting, cleaning, and exploring data, programming in R, and conducting reproducible research. 

This Data Science in Real Life course offered by Coursera in partnership with Johns Hopkins University is a focused course designed to rapidly get you up to speed on doing data science in real life. 

In this Essential Design Principles for Tableau course offered by Coursera in partnership with UC Davis, you will analyze and apply essential design principles to your Tableau visualizations. 

Relational Database Support for Data Warehouses course offered by Coursera in partnership with University of Colorado System  is part of the Data Warehousing for Business Intelligence Specialization.

This Python for Data Science, AI and Development course offered by Coursera in partnership with IBM will develop a foundational understanding of Python programming by learning basic syntax, data types, expressions, variables, and string operations.

The Data Warehouse Concepts, Design, and Data Integration course offered by Coursera in partnership with University of Colorado System is part of the Data Warehousing for Business Intelligence Specialization.

This Functional Program Design in Scala offered by Coursera in partnership with École Polytechnique Fédérale de Lausanne is part of the Functional Programming in Scala Specialization.

Data science and machine learning skills continue to be in highest demand across industries, and the need for data practitioners is booming. Upon completing this edX - online learning platform Data Science Foundations program, you will be armed with the basics to jump start your career in data science and machine learning.

In this Web Scraping in R course offered by Data Camp you will learn how to efficiently collect and download data from any website using R.

The Linear Algebra for Data Science in R course at Data Camp is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.

In this Tidyverse Fundamentals in R course offered by Data Camp you will learn how import and tidy data, wrangle and visualize data, and model and communicate with data in R with the tidyverse.

In this Interactive Data Visualization in R course offered by Data Camp you will build beautiful interactive maps, explore your data by zooming into and hovering over plots, and design engaging, dynamic charts in R.

In this Modeling with Data in the Tidyverse course offered by Data Camp you will learn discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.

Gain the real-world data prepping skills you need to reveal the insights that matter! Discover how to import, clean, and work with APIs and web data with this Importing and Cleaning Data in Python course offered by Data Camp 

In this NoSQL Concepts course offered by Data Camp you will learn about the four major NoSQL databases and popular engines.

In this Understanding Data Engineering course offered by Data Camp you will discover how data engineers lay the groundwork that makes data science possible. No coding involved!

In this User-Oriented Design in Power BI course offered by Data Camp you will learn how to design Power BI visualizations and reports with users in mind.

In this Big Data with PySpark course offered by Data Camp you will master how to process big data and leverage it efficiently with Apache Spark using the PySpark API.

In this Dealing With Missing Data in R course offered by Data Camp you will make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.