ONLINE COURSE

Forecasting Technology Innovation:

Using Data for Strategic Advantage

Why Enroll in this Course?

Become part of the MIT community, the leading institution in the world for innovation.

The crucial need to effectively measure & forecast technological evolution to draw insights & data.

Equipped with these insights, businesses can influence the rates/directions of technological change.

Assist your organization boost strategy for investing in new technology.

What will you learn?

Insights into dynamics of technological innovation
Compare rates of progress
State of the art technological innovation theories
Data analysis
Decision-making process

All the participants who successfully complete their program will receive an MIT Professional Education Certificate of Completion, as well as Continuing Education Units (CEUs)*.

To obtain CEUs, complete the accreditation confirmation, which is available at the end of the course. CEUs are calculated for each course based on the number of learning hours.

*The Continuing Education Unit (CEU) is defined as 10 contact hours of ongoing learning to indicate the amount of time they have devoted to a non-credit/non-degree professional development program.

To understand whether or not these CEUs may be applied toward professional certification, licensing requirements, or other required training or continuing education hours, please consult your training department or licensing authority directly.

Course Outline

MIT Professional Education's online course Forecasting Technology Innovation explores the data-driven process of measuring, tracking, predicting, and influencing technological innovation. Gain mastery in the skills needed to make better technology investments and design decisions to elaborate public policy, as well as financial and R&D portfolios.

1

Course overview and motivation

2

Definitions and performance metrics

3

Data, trends, and data-driven models

4

Forecasting using data-driven models

5

Mechanistic models part 1: Innovation of interconnected components

6

Mechanistic models part 2: Innovation mechanisms

7

Portfolio Optimization

8

Applications of data-informed insights to technology decisions

Instructor

Prof. Jessika Trancik

Professor, Institute for Data, Systems, and Society, MIT

I absolutely loved this course on technological innovation and forecasting! It has been an incredibly enriching experience, both personally and professionally. The course content was not only comprehensive but also presented in a way that made complex concepts easy to grasp. I've learned so much about measuring and forecasting technological change, from the importance of data-driven models to the simplicity of focusing on results and trends. This newfound knowledge has already proven invaluable in my work, helping me make informed decisions and optimize technology investment portfolios. I'm genuinely excited about the insights I've gained and how they will continue to shape my career in the ever-evolving world of technology. Thank you for this fantastic learning journey!

Aldo Segnini

Founder / Chief Executive & Strategy Officer,

Tailor Strategy

Register now and boost your professional trajectory.

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