The course is a compendium of the must-have expertise in data science for executive and middle-management to foster data-driven innovation. It consists of introductory lectures spanning big data, machine learning, data valorization and communication. Topics cover the essential concepts and intuitions on data needs, data analysis, machine learning methods, respective pros and cons, and practical applicability issues.
Informações sobre o curso
O que você vai aprender
What is data science
How data science, machine learning, and data-driven innovation can benefit business outcomes
Foundational concepts and intuitions about machine learning techniques
Habilidades que você terá
oferecido por

EIT Digital
EIT Digital is a European education and innovation organisation with a mission to foster digital technology innovation and entrepreneurial talent for economic growth and quality of life. By linking education, research and business, EIT Digital empowers digital top talents for the future.

Politecnico di Milano
Politecnico di Milano is a scientific-technological University, which trains engineers, architects and industrial designers.
Programa - O que você aprenderá com este curso
Introduction to Data-driven Business
This module introduces the course and offers some basic overview of the topics. It presents the crucial concepts related to data science and big data and provides an outlook on how to use them in real world settings for increasing business value.
Terminology and Foundational Concepts
In this module, you will learn the foundational concepts of machine learning and data science. You will understand how these techniques can be useful in terms of increased business value for organizations, thanks to the discussion of a very well known success story, namely Netflix, which can be deemed as a completely data-driven business. You will also understand how machine learning is different from programming.
Data Science Methods for Business
In this module, you will learn the concepts and intuitions about the basic approaches for data analysis, including linear regression, naive Bayes, decision trees, clustering, and logistic regression. All the methods are presented starting from typical business uses and are covered in an intuitive way through a guided explanation of how the approach works on simple examples.
Challenges and Conclusions
This module summarizes the concepts learned so far and introduces a set of challenges and risks that data-savvy managers must take into account when deciding for a data-driven strategy.
Avaliações
Principais avaliações do DATA SCIENCE FOR BUSINESS INNOVATION
A very well done course that showcases the main technologies applied in different scenarios. It was a good introduction to the world of applied data science.
The knowledge was practical based and interesting; however better application of knowledge in real life would've been a great add-on.
There are sometimes language interpretations that make it really hard to pass the quizes.
Interesting and useful to have an overall overview on this important discipline
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