Looking to upskill for musedata as a leader, analyst or scientist? These open online courses, mostly free, provide an excellent starting point for education and training.
Big data and analytics introduction for data leadership
Knowledge and Big Data in Business
6 – 8 hours per week for 6 weeks with HKPolyUX (starts September 2016)
From knowledge to big data, analytics to Linked Open Data, cloud computing and machine reasoning. This course provides a leader’s guide to the core principles behind leading a data driven organization.
Fundamentals of Six Sigma (green belt)
3 – 4 hours per week for 10 weeks with TUMx
Learn the fundamentals for quality engineering and management, with an introduction to the statistical concepts of six sigma at a green belt level. Apply the DMAIC process improvement cycle to your work and research and become metrics driven.
Data Science Ethics
3 – 4 hours per week for 4 weeks with MichiganX
Don’t just learn the tools of the trade, appreciate the consequences of the work. This course explores the delicate balance of privacy versus benefit in personal and society wide applications, presenting a framework for analyzing concerns.
Data analytics for beginners
Marketing and Data Analytics
3 – 4 hours per week for 6 weeks with Wharton ($)
Understand the tools and strategies for making data driven decisions with analytical methods across marketing, digital and social media analytics using new techniques in market research.
Explore 5 key courses: digital analytics introduction, Google Analytics principles, eCommerce analytics, app analytics and Google Tag Manager fundamentals.
Statistics for Business
5 – 7 hours per week for 7 weeks with IIMBx
Learn the discipline of statistical analysis for business using datasets, posing questions, describing a probabilistic terms and drawing samples. Statistical modelling, including random variables and simulation for prescribed distributions, is also covered.
Data science foundations
Data Science and Analytics in Context
7 – 10 hours per week for 5 weeks with ColumbiaX
Learn about data science tools and their applications, including concepts like statistical thinking, machine learning and data visualisation alongside emerging trends such as the Internet of Things (IoT), natural language processing and multimedia instrumentation.
The Analytics Edge
10 – 15 hours a week for 12 weeks with MITx
A deep dive into analytical methods including linear regression, logistic regression, CART, clustering and data visualisation, with implementation of models in R and applied mathematics optimisation using spreadsheet software.
Statistics and R
2 – 4 hours per week for 4 weeks with HarvardX
Learn the basics of statistical inference to understand p-values and confidence intervals, while analysing data with R, using statistical and visualisation techniques. This course forms part of a 7 course series to advance statistical concepts, software engineering skills and research concepts.
*Note some classes have closed for verified enrolments and some charge a fee for access or additional services.