Data Science for Business Innovation

Enroll in the Data Science for Business Innovation Program to learn about techniques of Data Science for Business Innovation

EIT Digital

Course Overview

The course on business innovation is a must for the professionals of data science managers and executives so that they can foster innovation based on data. With a more technical perspective, the article includes supervised, unsupervised, semi semi-supervised methods and explains what can be gained with classification, clustering, and regression methods. Furthermore, it also discusses the role of NoSQL data models and technologies including the impact of scalable cloud-based computing platforms,s. All this will be covered using cases, lectures, and realistic examples.

By the end of this course, students will be able to value data science, the main problem that data science can solve, and the major difference between various forms of analytics and the roles of machine learning.

What you'll learn

  • Decision Making
  • Data Science
  • Big Data
  • Data Analysis
  • Business Analytics

Requirements

  • Basic knowledge of Data Science.
  • A computer or laptop with internet connectivity.
  • Learn about techniques of Data Science for Business Innovation in approximately 7 hours.
  • Flexible work schedule.

AccessTo Career Resources with Data Science for Business Innovation Course

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Enhanced Employability:

An outstanding Data Science for Business Innovation program that increases your chances of landing the best jobs.

Course

Competitive Advantage:

An opportunity to stand out from the competition and make a more significant impression on potential employers.

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Skill Validation:

Robust validation of Data Science for Business Innovation skills confirms that you can complete all related tasks.

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Networking Opportunities:

Managing Data Science for Business Innovation Specialization courses provide ample networking opportunities for participants. Learners can connect with classmates and industry professionals through cooperative exercises, group discussions, and interactive seminars.

Course

4.3 Course (260 reviews)

Beginner level

Beginner

Duration

1-4 Weeks

Earn certificate credit

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