Please install the latest version of Python 3 and Anaconda (for notebooks). Other packages may be needed on a lecture-by-lecture basis. Common packages include numpy, scipy, scikit-learn, gpyopt.
Mandatory participation, max. 3 absences (strictly observed). Some lectures will have in-class exercises worth points (assignment point quota).
Grading and minimum requirement for passing
Grading (1-5) is based on (1) points collected in assignments (max 100) and (2) score in the written exam (max 50). The two points are summed up for the final grade. The maximum attainable score is 150. For passing the course, minimum 50 points must be collected in assignments and minimum 25 in the exam.
One assignment sheet is released per lecture. One is released by Tuesday EoD and the other by Friday EoD and should be returned by following Monday and Thursday evenings, respectively. Each sheet will have 1-4 tasks, each worth of 3-10 points but typically 5. You can choose which exercises to return to collect assignment points. Answers can only be submitted via MyCourses.
Bonus points may be earned by carrying out a small research project. The bonus task is declared around the second week of December and must be returned in late December. It will be worth max. 10 points. Bonus points can also be earned for being active in in-class activities.
Readings may be assigned before lecture. They will be announced in Announcements. These are optional but recommend to make more out of the lecture.
Final exam on Dec 16 will consist of 10 tasks, one task per page. The tasks include the following types: definition, essay, identification, analysis, and simple numerical exercises. Simple calculators are allowed to the exam; books, computers, or graphical calculators are not permitted. Materials for the exam will be announced late November in MyCourses. Examples of exam tasks will be given in the last lecture (Rehearsal).
Estimate based on previous year: 32 h lectures and support sessions + 66 h independent work on assignments + 12 h preparation for exam. Workload varies depending on prior experience and selection of assignments. Note that workload is relatively higher in the beginning of the course.
We expect all students to be honest and commit to the principles of academic and intellectual integrity in their preparation and submission of course work and examinations. All submitted work of any kind must be the original work of the student who must cite all the sources used in its preparation.
- Please come to the class room and find a seat before the lecture starts.
- Out of courtesy to the teachers and fellow students, please refrain from using computers or smartphones unless asked by the teacher.
- In cases of plagiarism, we will follow the policy of Aalto University. While we recommend talking with other students and learning from the Internet, exercise solutions must be executed individually and by the student. Solutions should not be shared. The student must be ready to explain his/her solution when requested.
- A student who is inactive for two or more weeks may be removed from the course. Students who have already reached the 50 point minimum are exempted.
- Please observe the deadlines for returning the exercises. No extensions will be granted.
- When grading exercises and exams, we may punish for "fishing" points by equivocating in answers. If you do not know the answer, just say so.
This year we organize an excursion to Futurice around mid-December. 10-15 students will be invited to the excursion based on assignment points collected before a cut-off date.
Voluntary sessions on Monday mornings (A136 in the CS building) for those who want support on solving the on-going assignments. Note: We start at 8.15am sharp.
Tayyaba Taimur and Asutosh Hota