Data Structures and Algorithms
Language, Cognition & Computation
*Dates without specified times may still change. I will update them here on this page regularly.
| Course | Type | Weight | Minimum Grade Required | Date | Time |
|---|---|---|---|---|---|
| Calculus | Midterm | 50% | 5.5 | March 25 | 08:30 - 11:00 |
| Data Structures and Algorithms | Midterm (Digital) | 40%–if you get a lower grade on your final; |
0%–if you get a higher grade on your final. | None | March 28 | 13:00 - 16:00 | | | | | | | | | Calculus | Final | 50% | 5.5 | June 2 | 08:30 | | Statistics for CSAI 1 | Final (Digital) | 80% | 5.5 | June 4 | 08:30 | | Data Structures and Algorithms | Final (Digital) | 60%–if you get a lower grade than for your midterm;
100%–if you get a higher grade than for your midterm. | 5.5—if you got a grade lower than 5.5 for your midterm;
None*—if you got a grade higher than 5.5 for your midterm.* | June 6 | 08:30 | | Introduction to AI 2 | Final (Digital) | 75% | 5.5 | June 11 | 17:30 | | Language, Cognition & Computation | Final | 100%–if you did not submit the midterm assignment;
90%–if you submitted the midterm assignment. | 5.5*—but worded weird in the syllabus so not sure.* | June 12 | 08:30 | | | | | | | | | Calculus | Midterm re-sit | 50% | 5.5 | June 23 | - | | Calculus | Final re-sit | 50% | 5.5 | June 30 | - | | Statistics for CSAI 1 | Re-sit (Digital) | 80% | 5.5 | July 2 | - | | Data Structures and Algorithms | Final re-sit (Digital) | 60%–if you get a lower grade than for your midterm;
100%–if you get a higher grade than for your midterm. | 5.5*—if you got a grade lower than 5.5 for your midterm;*
None*—if you got a grade higher than 5.5 for your midterm.* | July 4 | - | | Introduction to AI 2 | Re-sit (Digital) | 75% | 5.5 | July 8 | - | | Language, Cognition & Computation | Re-sit | 100%–if you did not submit all 10 assignments
90%–if you submitted all 10 assignments | 5.5*—but worded weird in the syllabus so not sure.* | July 10 | - |
*Any due dates originally set at unusual or easily overlooked times (e.g. 1pm or 10:45am) have been moved to the previous day here for good measure.
| Course | Type | Weight | Minimum Grade Required | Due Date |
|---|---|---|---|---|
| Statistics for CSAI 1 | 5-6 Practical exercises | 20% | Pass | 1.) February 22 |
| 2.) March 15 | ||||
| 3.) April 12 | ||||
| 4.) April 26 | ||||
| 5.) May 10 | ||||
| 6.) May 24 | ||||
| Introduction to AI 2 | Essay | 25% | 5.5 | Outline: February 19 |
| Draft: February 25 | ||||
| Peer feedback: March 4 | ||||
| Final version: March 12 | ||||
| Introduction to AI 2 | Practical & discussion assignments | 0% | Pass | (P) Machine Learning: March 9* |
| (D) Shannon: March 18 | ||||
| (P) Neural Networks: April 7* | ||||
| *(P) Reinforcement Learning: April 21 | ||||
| (D) Rodney Brooks: May 6 | ||||
| (P) N-gram language models: May 12* |
$**$ (P) assignments can still be submitted later.* |
| Language, Cognition & Computation | 10 Group annotation & selected fragment assignments | 0% | None, but a prerequisite | All together 8, weekly from lecture 2 until lecture 12 (for your midterm assignment to be evaluated)
All together 10, weekly by the end of the course (for your midterm grade to count) | | Language, Cognition & Computation | Midterm Group Assignment | 0%–if you did not submit all 10 assignments
10%–if you submitted all 10 assignments | None | April 3 |