News

Final exam information

Written on 07.02.24 by Yue Fan

Time: 21. February 2023 10:00 a.m.
Location: Günter-Hotz-Hörsaal

  • Please bring your student card or any valid ID to the exam.
  • The exam is 120 minutes long and the maximum point is 100.
  • You cannot use any books, printouts of slides, electronic devices, and cell phones or smartwatches must be… Read more

Time: 21. February 2023 10:00 a.m.
Location: Günter-Hotz-Hörsaal

  • Please bring your student card or any valid ID to the exam.
  • The exam is 120 minutes long and the maximum point is 100.
  • You cannot use any books, printouts of slides, electronic devices, and cell phones or smartwatches must be turned off.
  • You can bring two A4 pages of notes hand-written on both sides (no printouts, no assignment sheets, no carbon copies).
  • The questions will be in English and German and you can answer either in German or English.
  • You should bring a non-programmable calculator.
  • You have to use a non-erasable pen with black or blue ink.

The exam will consist of 20 points from each of the four series of lectures, plus 20 points of multiple-choice questions on all four main topics. The multiple-choice questions are in the same format as those you have seen in Assignments 8 and 9.

Q&A session tomorrow

Written on 07.02.24 by Yue Fan

Dear all,

 

Thank you to everyone who submitted questions for tomorrow's Q&A session. Based on the received requests, we will discuss the following topics tomorrow:

- Demonstrate Backpropagation on a Fully-Connected Network

- Explain the Convolution Operation

- Explain K-Nearest… Read more

Dear all,

 

Thank you to everyone who submitted questions for tomorrow's Q&A session. Based on the received requests, we will discuss the following topics tomorrow:

- Demonstrate Backpropagation on a Fully-Connected Network

- Explain the Convolution Operation

- Explain K-Nearest Neighbors

 

Best,

Fan

Self Driving Cars Lecture 3

Written on 02.02.24 by Bernt Schiele

Dear students

I just uploaded the slides as well as a recording from a previous iteration of the last self driving lecture that is scheduled for Monday, Feb 5th

The reason that I uploaded the recording is that - unfortunately - I won't be able to give the lecture on Monday. Very sorry for… Read more

Dear students

I just uploaded the slides as well as a recording from a previous iteration of the last self driving lecture that is scheduled for Monday, Feb 5th

The reason that I uploaded the recording is that - unfortunately - I won't be able to give the lecture on Monday. Very sorry for that. 

Please note, that the material of this particular lecture will be not relevant for the exam this year. In case you have questions when watching the recording - please do not hesitiate to reach out to me

cheers

Bernt Schiele

 

Reminder: Q&A session on Feb. 8

Written on 02.02.24 by Yue Fan

Dear all,

Please don't forget to submit your questions for the Q&A session on Feb. 8 via this link. If we don't receive any questions, the session will be canceled. The question submission deadline is at 12pm on Feb. 7.

 

Exam Registration

Written on 29.01.24 by Yue Fan

Dear all,

 

In order to take the first written exam, please register in both the LSF and CMS systems by Feb. 14, 2024. The only exception is if you are from a program that cannot register in LSF (e.g. Erasmus students), in which case you only need to register in the CMS system by Feb. 14,… Read more

Dear all,

 

In order to take the first written exam, please register in both the LSF and CMS systems by Feb. 14, 2024. The only exception is if you are from a program that cannot register in LSF (e.g. Erasmus students), in which case you only need to register in the CMS system by Feb. 14, 2024.

 

  • LSF registration:
    • You need to register with your Saarland University credentials through the LSF system for the exam. You are responsible for respecting the deadlines of LSF exam registration yourself.
    • Please go to https://www.lsf.uni-saarland.de/qisserver/rds?state=user&type=0 and apply for the exam of Elements of Data Science and Artificial Intelligence. Depending on your study program, EDSAI may appear under different categories.
  • CMS registration:
    • Please go to your personal page and click on register for the End-of-Term Exam. You need to collect at least 100 points from the assignments and have at most two assignment sheets with 0 points, to be admitted to the exam.

 

Q&A session on Feb. 8

Written on 28.01.24 by Yue Fan

Dear all,

The last lecture on Feb. 8 will be a Q&A session for you to ask questions related to the topics covered in our course. Please submit your questions via this link. Please be specific and provide context to help understand your questions better. You can submit multiple questions in one… Read more

Dear all,

The last lecture on Feb. 8 will be a Q&A session for you to ask questions related to the topics covered in our course. Please submit your questions via this link. Please be specific and provide context to help understand your questions better. You can submit multiple questions in one section. The question submission deadline is at 12pm on Feb. 7.

Qualis Evaluation

Written on 12.01.24 by Yue Fan

Dear all,

Please take some time to fill in the Qualis survey for us.

Here is the link: 

https://qualis.uni-saarland.de/eva/?l=146369&p=su8b0s (for the lecture)

https://qualis.uni-saarland.de/eva/?l=1463691&p=mpyewz (for the tutorial)

The deadline to submit the survey is… Read more

Dear all,

Please take some time to fill in the Qualis survey for us.

Here is the link: 

https://qualis.uni-saarland.de/eva/?l=146369&p=su8b0s (for the lecture)

https://qualis.uni-saarland.de/eva/?l=1463691&p=mpyewz (for the tutorial)

The deadline to submit the survey is 31.01.2024.

Deadline extension of Assignment 06

Written on 18.12.23 by Yue Fan

Dear all,

Due to the upcoming Christmas holiday, the deadline for submitting Assignment 06 is extended to Jan. 07 (you have 3 weeks to solve this). Have a nice Christmas!

Exam Info

Written on 07.12.23 by Yue Fan

Dear all,

The exam for this course will take place on 21st February 2024 at 10:00 at Günter-Hotz-Hörsaal. Please write an email to Fan Yue if you have another exam on the same day. 

Tutorial, office hour, and the first assignment

Written on 30.10.23 by Yue Fan

Dear all,

The assignment sheets will be handed in groups of two or three students. Please register your team grouping on the CMS, and the deadline is 10th November.

The first tutorial starts from next week. The tutorials of the first two weeks will be about installing the VMs, you can choose to… Read more

Dear all,

The assignment sheets will be handed in groups of two or three students. Please register your team grouping on the CMS, and the deadline is 10th November.

The first tutorial starts from next week. The tutorials of the first two weeks will be about installing the VMs, you can choose to come at either one.

Our office hour sessions will start next week as well (E1.3 SR016 Thu 10-12 and E1.1 SR206 Tue 12-14).

Written on 23.10.23 by Yue Fan

Dear all,

The tutorial timeslots have been updated. Please set or update your tutorial preference on your personal status page in the CMS. The deadline is 6th November. You will be assigned a tutorial shortly afterward.

Show all

Elements of Data Science and Artificial Intelligence

 

You will find all administrative information here: Organization

 

Artificial intelligence is a long-standing branch of computer science concerned with the design of algorithms and systems exhibiting intelligent behavior. Data science is a comparatively young area concerned with the extraction of knowledge and insights from structured and unstructured data. Increasingly, the real power of computer science applications lies in combining the two, exploiting insights from data to take intelligent decisions.

Both artificial intelligence (AI) and data science (DS) are complex multi-disciplinary scientific fields. This course provides an overview of central concepts and ideas, structured and motivated by prominent applications requiring elements from both DS and AI. We start with a brief introduction to machine learning (ML), which lies at the heart of the intersection between DS and AI. We then cover game playing, explaining the search and learning techniques essential to recent successes in Go and Chess. We cover autonomous driving as a prominent application of sensing, system design, control, and learning. We cover dialogue systems and the associated learning and reasoning techniques for natural language processing. We finally cover the data processing techniques required to enable big data.

The aim is for students to understand the scope of DSAI and to obtain intuitions about its central algorithmic elements. Detailed technical expositions and analyses of these elements are not covered; these are the subject of later more specialized courses.

The course is accompanied by exercises, covering technical concepts through examples, as well as posing simple programming exercises (suitable for first-term students) in the Python language. This course also contains a quick introduction to Python.

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