Syllabus

Title
6069 Elective - Artificial Intelligence
Instructors
Dr.Dr. Wolfgang Frühwirt
Contact details
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
02/12/20 to 02/19/20
Registration via LPIS
Notes to the course
Dates
Day Date Time Room
Wednesday 03/04/20 09:00 AM - 01:00 PM D5.1.004
Monday 03/09/20 09:00 AM - 01:00 PM D5.1.004
Wednesday 03/11/20 09:00 AM - 01:00 PM D5.1.004
Wednesday 03/25/20 09:00 AM - 06:00 PM D5.1.004
Friday 04/17/20 09:00 AM - 06:00 PM D5.1.004
Contents

Artificial intelligence (AI) has left the labs of computer scientists and entered into mainstream business. Many of tomorrow’s business leaders expect AI to have disruptive impact on a variety of industries and individual businesses, but have little understanding what AI actually is, or how it can be practically applied.

In the present lecture, future leaders will learn what they should know about AI in general, and in the domain of Financial Management & Management Control in particular.

Among other important topics, the following fundamental questions will be addressed:


Fundamentals
● What is AI and how can it be practically applied?
● What is the difference between AI, deep learning, machine learning, cognitive computing, and robotics?
● What is an algorithm?
● How does a deep learning algorithm work?
● What are the main drivers of AI progress?
● How ‘intelligent’ are AI systems today?
● How will Quantum Computing change the field of AI?
● What are the main risks and ethical considerations?
● How can we understand how AI systems come up with their decisions?


Applications in Financial Management & Management Control
● What are the main business domains where AI can be used today?
● How can AI be applied in financial management and management control (financial forecasting, risk assessment, portfolio management, fraud detection, churn prediction, budget allocation, etc.)?
● How to harness the power of AI without specialist data science skills?
● What are the first steps in using AI in financial management and management control?
● How can organizations best prepare for the use of AI?
● How do world-leading corporations use AI?
● How can medium-sized enterprises (SMEs) profit from AI?
● What are the main challenges in applied AI projects?
● What can and can’t be done with AI technology existing today?


Strategy & Leadership
● How can AI drive customer and organizational value?
● How can key AI opportunities be identified in organizations?
● How to get started with AI?
● Organizational transformation: How to accompany change, understand and address fears, and empower stakeholders in a participatory fashion.
● What are AI’s essential consequences for the strategic leadership of organizations?

Learning outcomes

Not assuming any mathematical or technical background of participants, a practical understanding of AI is established. The demonstration and explanation of examples in numerous domains enables participants to identify opportunities and to leverage the benefits of this fascinating and game-changing technology for their future organizations.
AI’s impact on our society and the future of organizations becomes evident. By considering the essentials that tomorrow’s executives need to know, participants will be equipped with the comprehensive understanding and the confidence necessary to make informed strategic decisions regarding AI.

After completing this class, students will have the ability to:
● identify key AI opportunities in organizations in the domain of Financial Management & Management Control
● develop coherent narratives to convey their ideas regarding AI in the domain of Financial Management & Management Control
● develop presentation for applied AI projects to pitch their proposals
● make informed strategic decisions regarding AI in the domain of Financial Management & Management Control

Attendance requirements

In order to successfully complete this course, you have to attend at least 80% of its class time.

Teaching/learning method(s)

● Immersive interactive lecture (including theory input, open class discussions, interactive teamwork)
● Guest talks by world-leading AI researchers (University of Oxford) and experienced industry experts (TBA)
● Group projects: Development and delivery of a presentation to pitch a proposal for an applied AI project

Assessment

Workshop presentation (10%)
Final presentation (50%)
Final report (30%)
Class participation (10%)
Bonus (10%): Can be earned via a mini AI research assignment

The following grading scale applies:

Excellent (1)      

87.5%-100.0%

Good (2)          

75.0% -<87.5%

Satisfactory (3)  

62.5% -<75.0%

Sufficient (4)   

50.0% -<62.5%

Fail (5)            

<50.0%

 

Last edited: 2020-01-22



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