The opening session for the Elements of AI series of webinars, accompanying the Elements of AI MOOC. More information on our reddit page, including a recording of the presentation: eofai.lu/reddit

1. Elements of AI
Luxembourg
Opening session
February 25, 2021

2. Session overview
1. The hosts
2. The Elements of AI course
3. Webinars schedule & speakers
4. Contact and discussions
5. Course certificate
6. Questions

3. 1. Your hosts
Dr. Jérémie Dauphin
• Postdoctoral researcher at the
University of Luxembourg
Prof. Martin Theobald
• Professor of Computer Science
at the University of Luxembourg,
head of the Big Data research
group

4. 2. The Elements of AI MOOC
• Created by Reaktor and the University of Helsinki (2018)
• Designed in order to demystify AI, helping non-experts
undertsand what AI is and what it can (or can’t) do
• No complex formulas, high-level concepts with practical
exercises and examples
• Aim to educate 1% of European citizens about the basics
of AI (600 000 registered users, 75 000 completed)
• Available in 9 different languages and counting
• Ranked world’s #1 AI course on Class Central and Forbes,
along with courses from Stanford and Google

5. Elements of AI in Luxembourg
• Brought to you by the Luxembourgish Government, in
collaboration with the SMC, the INAP, the SCRIPT, the
University of Luxembourg and the Competence Centre.
• 6 chapters in a paced format, in English
• 6 week program: February 22 to April 4
• Weekly 1h webinars with guest researchers from the
University of Luxembourg
• Webinars will also include a Q&A session at the end
• Concluded by a final exam
• Course material available online: eofai.lu

6. Additional resources
• Extra material and webinar slides will be posted on
the reddit page eofai.lu/reddit
• Webinar recordings will be posted there, in case you
miss the live sessions
• Feel free to ask questions and discuss the course
material there!

7. 2. The course content: overview

8. Chapter 1: What is AI?
• Finding a good definition
• Related fields:
• Machine learning
• Data science
• Robotics
• Philosophy
• What is intelligence?
• Thought experiements

9. Chapter 2: AI problem solving
• Search and problem solving
• Finding the ‘best’ soluDon
• Planning
• Solving problems with AI
• History
• Game theory
• Tic tac toe
• Chess
• Go

10. Chapter 3: Real world AI
• Classical probabilistic reasoning
• Uncertainty
• The Bayes rule
• Partial knowledge
• Naïve Bayes classification
• Spam filters
• Weather prediction

11. Chapter 4: Machine learning
• The 3 types of machine learning
• Supervised
• Unsupervised
• Reinforcement
• Nearest neighbour
• Assigning labels
• Recommendations
• Regression
• Numbers
• Predicting cost

12. Chapter 5: Neural networks
• Neural networks basics
• Simulating a brain
• Neural networks components
• Advanced techniques
• Deep learning
• CNNs
• GANs (fake faces)

13. Chapter 6: Implications
• PredicTng the future
• ExpectaDons vs reality
• Societal implicaTons
• Ethics
• Privacy
• Summary
• Beyond the course

14. 3. Webinars

15. Dr. Sana Nouzri
• Postdoctoral researcher at the University of
Luxembourg, in the AI Robolab
• PhD in Computer Science from the Cady Ayyad
University (2014)
• Formerly assistant professor in Computer Science
at Cady Ayyad University
• Research focus on multi-agent systems
• Interests in AI&Art and knowledge dissemination
• Talk (March 4): An introduction to AI, AI&Art and
problem solving

16. Dr. Alexander Steen
• Postdoctoral researcher at the University of
Luxembourg, in the Individual and Collective
Reasoning (ICR) research group
• PhD in Computer Science from the Free University
of Berlin (2018)
• Research focus on theory and practice of higher-
order reasoning
• Talk (March 11): Logic in AI, Automated Theorem
Provers and their applications

17. Prof. Luis Leiva
• Professor of Computer Science at the University of
Luxembourg
• PhD in Computer Science from the Polytechnic
University of Valencia (2012)
• Formerly at Aalto University and the Polytechnic
University of Valencia
• Research focus at the intersection of Machine
Learning and Human-Computer Interaction
• Talk (March 18): It's not what you do, but how you
do it: Information retrieval with implicit interaction

18. Prof. MarQn Theobald
• Professor of Computer Science at the
University of Luxembourg, head of the Big
Data research group
• Talk (March 25): Current trends and topics
in Big Data Analytics

19. Prof. Dov Gabbay
• PhD in Logic from Hebrew University (1969)
• Augustus De Morgan Professor of Logic (Emeritus) at King’s
College London
• Visiting Professor at the University of Luxembourg since
2008
• One of the world’s most active and influential researchers
in Logic and reasoning
• Over 550 research papers in AI
• Editor of over 50 Handbooks of Logic and Reasoning
• Charmain and founder of many international conferences
• Talk (April 1): Formal logic, human intelligence, artificial
intelligence, fake intelligence

20. 4. Contact and discussion
• Mainly: eofai.lu/reddit
• Anyone can read
• Make a free to account to participate
• Webinar full schedule
• Webinar recordings
• Questions to be answered during webinar
• Elements of AI FAQ:
elementsofai.lu/faq

21. 5. Course certificate
a) Continuous assessment
b) Final exam

22. a) ConQnuous assessment
• Course includes regular practical exercises
• Automatically graded
• A few questions are subjective (no wrong answer)
• Some essay-based questions, peer-review feedback
(also moderated)
• Certificate at the end of the online material
(23/25 completed with 50% correct)

23. b) Final exam
• Conducted via Moodle (link coming soon)
• Available from April 5 to April 18
• Around 30 questions, multiple choice
• Based on written material of the online course, no
question about webinar talks
• Example: What is the formula for Bayes rule:
i. 𝑐ℎ𝑎𝑛𝑐𝑒 𝑜𝑓 𝑠𝑢𝑐𝑐𝑒𝑠𝑠 = 1 – 𝑐ℎ𝑎𝑛𝑐𝑒 𝑜𝑓 𝑓𝑎𝑖𝑙𝑢𝑟𝑒
ii. 𝑝𝑜𝑠𝑡𝑒𝑟𝑖𝑜𝑟 𝑜𝑑𝑑𝑠 = 𝑙𝑖𝑘𝑒𝑙𝑖ℎ𝑜𝑜𝑑 𝑟𝑎𝑡𝑖𝑜 ∗ 𝑝𝑟𝑖𝑜𝑟 𝑜𝑑𝑑𝑠
iii. 𝑒𝑥𝑝𝑒𝑐𝑡𝑎𝑡𝑖𝑜𝑛 = 𝑣𝑎𝑙𝑢𝑒 ∗ 𝑝𝑟𝑜𝑏𝑎𝑏𝑖𝑙𝑖𝑡𝑦
iv. 𝑟𝑖𝑠𝑘 = 𝑡ℎ𝑟𝑒𝑎𝑡 ∗ 𝑣𝑢𝑙𝑛𝑒𝑟𝑎𝑏𝑖𝑙𝑖𝑡𝑦 ∗ 𝑐𝑜𝑛𝑠𝑒𝑞𝑢𝑒𝑛𝑐𝑒

24. Getting your final certificate
• Submit online course certificate via Moodle
• Pass final exam on Moodle
• => Final certificate from the Competence Centre
• 100% online
• Reminder: for INAP, webinar mandatory
• Use same email for all platforms

25. 6. Questions
Useful links recap:
• eofai.lu
• eofai.lu/reddit
• elementsofai.lu/faq