Data Science for Business Innovation. A new MOOC on Coursera

Breaking news!

We just published our new MOOC “Data Science for Business Innovation” on Coursera!

Our course is available for free on Coursera and is jointly offered by Politecnico di Milano and EIT Digital, as a compendium of the must-have expertise in data science for non-technical people, including executives, middle-managers to foster data-driven innovation.

The course is an introductory, non-technical overview of the concepts of data science.

You can enrol in the first edition of the course starting today.

The course is completely free and you can enjoy content at any time, with professional English speakers and animated, engaging materials.

Here is a short intro to the course:

[youtube https://www.youtube.com/watch?v=LXiUj1Ad1SQ&w=560&h=315]

The course consists of introductory lectures spanning big data, machine learning, data valorization and communication.
All the remaining details can be found on Coursera:

eit

Topics cover the essential concepts and intuitions on data needs, data analysis, machine learning methods, respective pros and cons, and practical applicability issues. The course covers terminology and concepts, tools and methods, use cases and success stories of data science applications.

The course explains what is Data Science and why it is so hyped. It discusses the value that Data Science can create, the main classes of problems that Data Science can solve, the difference is between descriptive, predictive and prescriptive analytics, and the roles of machine learning and artificial intelligence.

From a more technical perspective, the course covers supervised, unsupervised and semi-supervised methods, and explains what can be obtained with classification, clustering, and regression techniques. It discusses the role of NoSQL data models and technologies, and the role and impact of scalable cloud-based computation platforms.

All topics are covered with example-based lectures, discussing use cases, success stories and realistic examples.

If you are interested in these topics, feel free to look at it on Coursera.

We look forward to seeing you there!

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