Course Plan

Date	AM/PM	Mode	Content
2023-09-17	AM	online	Introduction to the course and innovation
2023-02-01	AM	in classroom	starting with R
2023-02-02	AM	in classroom	Business plans and MCDA
2023-02-03	PM	in classroom	building models (regressions)
2023-03-24	PM	online	building models (machine learning)
2023-04-20	PM	online	Selected Topics (AI applications, Quantum Computing, Applications of Quantum Computing, Blockchain)
2023-04-21	PM	online	Exam (your presentations)

Course Modules Content

Introduction

introduction to innovation
the role of innovation in the history of capitalism
setting expectations and agreements
installing R and RStudio

Business Plans and Multi Criteria Decision Analytics (MCDA)

Elements of a Business plan
MCDA (Multi Criteria Decision Analytics)
case studies MCDA

Building Models: regressions and Machine Learning

linear regressions
generalised linear models
non-linear regressions
decision trees
random forests
SVN
neural networks

Case studies and models

recap of theory (and continuation)
case studies and practice

From Accounting to Creating Value

A selection from:

financial accounting
management accounting
valuation of cash, bonds, equities
other financial instruments

Selected innovation axis

A selection from:

automated reporting
preparation for the end-project
crypto ledgers
quantum computing
Big Data

Exam: presentations of projects by students

presentations of the projects (counts as exam)

Background Material

The Big R-Book: From Data Science to Learning Machines and Big Data
examples and other material from my book
50 minutes summary of models
my channel on YouTube
the data science channel

Further Case Studies

quantum computers: https://hbr.org/podcast/2021/12/how-quantum-computing-will-change-everything-with-chad-rigetti
big data: https://hbr.org/2012/10/big-data-the-management-revolution
block-chain: https://hbr.org/2017/01/the-truth-about-blockchain

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