Exam
Format and grading
The course ends with an exam. The exam will be on campus and will contain both pen and paper questions as well as programming questions. The exam will be done on a computer using Inspera Assessment system. See further information here Links to an external site. regarding how it works to do a digital exam on campus.
The exam will consist of a combination of automatically corrected multiple choice questions and free text questions and problem solving assignments. Both pen and paper questions as well as programming quesations will be included. The solutions to the exam questions will in most cases be entered digitally directly in Inspera. For questions where the expected solution contains mathematical expressions, these solution will be handed in on paper as in a normal written exam.Since some of the solutions you are supposed to hand in on hand-written paper: don't forget to bring a pen! Also, remember to write your exam code and page numbers on the papers that you hand in.
Format
1RT003: 5 problems, total 50 points
1RT705: 4 problems, total 40 points
Preliminary grade limits
1RT003
Grade 3: 23hp
Grade 4: 33hp
Grade 5: 43hp
1RT705
Grade 3: 19hp
Grade 4: 27hp
Grade 5: 35hp
Exam time
1RT003: 5 hours
1RT705: 4 hours
Aiding material: One (1) hand-written sheet of paper with notes and formulas (A4, front and back), a calculator
Provided material: (provided, listed as digital resources in the e-exam):
- Numpy documentation Links to an external site.
- Scipy documentation Links to an external site.
- Matplotlib documentation Links to an external site.
- Lecture slides Download Lecture slides
- Lecture notes (VI and GPs) Download Lecture notes (VI and GPs)
- Formula sheet for the Gaussian distribution Download Formula sheet for the Gaussian distribution
- Christopher M. Bishop, Pattern Recognition and Machine Learning
, Springer, 2006.
- Lindholm et al, A First Course for Engineers and Scientists Links to an external site. , 2021 Machine Learning -
- Programming tool Links to an external site.
Course grade
To pass the course, you need to pass the mini-project, the peer-review assignment, the lab (only for 1RT003) and the exam. The course grade will then be the grade you got on the exam.
Old exams
- 2024-01-28 Exam Links to an external site., Solution Download Solution (only problem 1-4 for 1RT705)
- 2023-10-27 Exam Links to an external site., Solutions Download Solutions (only problem 1-4 for 1RT705)
- 2023-08-17 Exam, Links to an external site. Solutions Download Solutions (only problem 1-4 for 1RT705)
- 2022-10-21: Exam 1RT003 Links to an external site., Exam 1RT705 Links to an external site., Solutions Download Solutions
- 2022-08-24 Exam 1RT003 Links to an external site., Exam 1RT705 Links to an external site., Solutions Download Solutions
- 2021-12-20 Exam 1RT003 Links to an external site. (pdf Download pdf), Exam 1RT705 Links to an external site. (pdf Download pdf), Solutions Download Solutions
- 2021-10-22: Exam 1RT003 Links to an external site. (pdf Download pdf) , Exam 1RT705 Links to an external site. (pdf Download pdf), Solutions Download Solutions
- Demo exam:* Exam 1RT003 Links to an external site., Exam 1RT705 Links to an external site., Solutions Download Solutions
*Note: The demo exam Question 2(d) is about Markov Random Fields: which is not covered anymore in the course.
Re-exam
Re-exams will be offered during the re-exam periods in January and August.
Registration
You register to the exam via ladok no later than 12 days before the exam.
PhD-students
PhD students enrolled in FNT0092 and FNT0204 will take the same exam as 1RT705 and 1RT003, respectively. FNT0092 and FNT0204 are only graded with U/G. To get grade G on the course, grade 3 on the exam is required for PhD students.
PhD students register to the exam by sending an email to it-kansli@it.uu.se including personal number and the course code of the exam (1RT705 if you are resisted on the 5hp version or 1RT003 if you are resisted on the 7.5hp version). This should also be done no later than 12 days before the exam.