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A Scientific Approach to Innovation Management Coursera

Highlights
Tuition fee
Free
Free
Unknown
Tuition fee
Free
Free
Unknown
Duration
7 days
Duration
7 days
Apply date
Anytime
Unknown
Apply date
Anytime
Unknown
Start date
Anytime
Unknown
Start date
Anytime
Unknown
Taught in
English
Taught in
English

About

The A Scientific Approach to Innovation Management course offered by Coursera in partnership with Bocconi is highly interactive and includes exercises and real-world applications. 

Overview

How can innovators understand if their idea is worth developing and pursuing? In this course, we lay out a systematic process to make strategic decisions about innovative product or services that will help entrepreneurs, managers and innovators to avoid common pitfalls. 

A Scientific Approach to Innovation Management course offered by Coursera in partnership with Bocconi teaches students to assess the feasibility of an innovative idea through problem-framing techniques and rigorous data analysis labelled ‘a scientific approach’. 

Students will also be shown the implications of a scientific approach to innovation management through a wide range of examples and case studies.

About this course:

The course covers the basics of data analysis, beginning with the distinction between correlation and causality. It teaches how to make predictions using regression analysis and links these methods to the scientific approach, explaining their role in scientific decision-making and how they support managerial decisions. Real examples of companies using data to guide innovation decisions are included. The course concludes this section by discussing how to interpret analyses and results critically, emphasizing what can truly be learned from the analyses and when results should be interpreted cautiously and critically.

Programme Structure

Courses include:

  • Operation Efficiency Vs Strategic Efficiency
  • Conditional Probabilities And The Bayes Theorem
  • Randomized Control Trials
  • Correlation Vs Causality
  • Reflection Critical Evaluation
  • Machine Learning For Innovation Management Decisions

Key information

Duration

  • Part-time
    • 7 days
    • 10 hrs/week

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online
  • Self-paced

Campus Location

  • Mountain View, United States

What students do after studying

Join for free or log in to access our complete career info list.

Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

  • This course is aimed at students and managers interested in applying a scientific approach to innovation and managerial decision‑making, with a focus on problem formulation, data analysis, experimentation, and evidence‑based innovation decisions.

Tuition Fees

Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
  • International

    Non-residents
    Free
  • Out-of-State
    Free

Additional Details

Course is free for the first 7 days. After 7 days, the course can be accessed with the Coursera Plus Subscription

Funding

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