Welcome to DD2301

In this course we will have one seminar per period for the first 6 periods of your studies at KTH and discuss topics such as:

• The logistic and experiences of a machine learning student at KTH: courses and thesis project.
• Where do machine learning graduates work? Academia, industry and the public sector
• The ethics of making conclusions from experiments and results and presenting these to the public.
• Privacy, security and ethical issues around "big data".
• What machine learning can and cannot predict
• Code of conduct for a machine learning scientist

The course will also include visits to companies.

Important: To pass the course you need to complete an assignment for each seminar = 6 assignments in total (4 in Year 1 + 2 in Year 2)

Next Seminar: Seminars for  Period 1 are being scheduled. For details please check out Schedule for Seminars

Links to important webpages and assignments

Assignments & Seminars

• Seminar Period 1
• Seminar Period 2
• Seminar Period 3
• Seminar Period 4 - Industry Field Trips

Schedule & Group Information

•  Schedule for Seminars - This page contains the schedule for the seminars  (as we have many seminar groups it is not possible for all of them to happen on the same day and time) and assignment of groups to seminar leaders.

Information about thesis projects (Year 2 students)

•  Master Thesis information meetings for students in IS department 

• Degree Project Fair 2023 -  11 October, 11:30-15:00 (Kistagången 16/Electrum). Sign up before Sept 15.
• Degree Projects at EECS, 2023 - The official page for the thesis project VT23
• KTH degree project portal
  
• Master Thesis information meetings for students in IS department 
  
  • Thursday, September 28,  1:00–2:30 PM, Location: L1, Drottning Kristinas Väg 30. KTH main campus 
  • Friday, October 6, 4:00—5:30 PM. Online: zoom link, https://kth-se.zoom.us/j/63516317715 Links to an external site. 
    The content will be the same for the two meetings.
    

• Projects on offer at Department of Intelligent Systems

  • Project proposals from RPL, Division of Robotics, Perception and Learning.
  • Project Proposals from DCS, Division of Decision and Control Systems.
  • Project proposals from ISE, Division of Information Science and Engineering. 
  • Project proposals from TMH, Division of Speech, Music, and Hearing.

Information for Year 1 Students

•  intro.pdf Download intro.pdf - Slides from my introduction talk (Thursday, Aug 24)
•  Mentimeter Slides with results Links to an external site. - Slides with the results of the questionnaires.

• The course DD1420 is a mandatory course in the program syllabus for the Master's Programme in Machine Learning. If you have already taken the course DD2421/DD1420 or another course equivalent to these before then you will need to replace it with either an extra conditionally elective course or a course from the recommended courses list. Please fill out this form if you are in this situation:
  Replacement course for DD2421/DD1420 Machine Learning

Other information

• Studies abroad - KTH website with information about studying abroad
• Links to accessible Canvas Pages relevant to TMAIM students  - to help with your course choices several teachers of conditionally elective courses have kindly shared the Canvas page of their course with us. It is not exhaustive at the moment but I hope the list will expand over time.