 | Study programme 2020-2021 | Français | |
 | Big Data Analytics | ||
Programme component of Master's in Mathematics à la Faculty of Science |
| Students are asked to consult the ECTS course descriptions for each learning activity (AA) to know what special Covid-19 assessment methods are possibly planned for the end of Q3 |
|---|
| Code | Type | Head of UE | Department’s contact details | Teacher(s) |
|---|---|---|---|---|
| US-M1-SCMATH-055-M | Optional UE | BEN TAIEB Souhaib | S861 - Big Data and Machine Learning |
|
| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Credits | Weighting | Term |
|---|---|---|---|---|---|---|---|---|---|
| Anglais, Français | 30 | 30 | 0 | 0 | 0 | 6 | 6.00 | 2nd term |
| AA Code | Teaching Activity (AA) | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term | Weighting |
|---|---|---|---|---|---|---|---|---|
| S-INFO-075 | Big Data Analytics | 30 | 30 | 0 | 0 | 0 | Q2 | 100.00% |
| Programme component |
|---|
Objectives of Programme's Learning Outcomes
- Carry out major projects.
- Work in teams and, in particular, communicate effectively and with respect for others.
- Present the objectives and results of a project orally and in writing.
- Communicate clearly.
- Communicate the results of mathematical or related fields, both orally and in writing, by adapting to the public.
- Adapt to different contexts.
- Have developed a high degree of independence to acquire additional knowledge and new skills to evolve in different contexts.
- Critically reflect on the impact of mathematics and the implications of projects to which they contribute.
Learning Outcomes of UE
See single learning activity.
Content of UE
This unit is a follow-up to the "Machine Learning" unit. It covers other topics related to big data analysis which will allow to deepen the knowledge about the previously covered topics.
Prior Experience
"Machine learning" is a pre-requisite for this unit.
Type of Assessment for UE in Q2
- Presentation and/or works
- Written examination
- Graded tests
Q2 UE Assessment Comments
Written exam (60% of total score)
Project (20% of total score)
Assignments (20% of total score)
There is a hurdle of 50% for each of the previous evaluations
Type of Assessment for UE in Q3
- Presentation and/or works
- Oral examination
- Graded tests
Q3 UE Assessment Comments
Oral exam (60% of total score)
Project (20% of total score)
Assignments (20% of total score)
There is a hurdle of 50% for each of the previous evaluations
Type of Teaching Activity/Activities
| AA | Type of Teaching Activity/Activities |
|---|---|
| S-INFO-075 |
|
Mode of delivery
| AA | Mode of delivery |
|---|---|
| S-INFO-075 |
|
Required Reading
| AA | |
|---|---|
| S-INFO-075 |
Required Learning Resources/Tools
| AA | Required Learning Resources/Tools |
|---|---|
| S-INFO-075 | Not applicable |
Recommended Reading
| AA | |
|---|---|
| S-INFO-075 |
Recommended Learning Resources/Tools
| AA | Recommended Learning Resources/Tools |
|---|---|
| S-INFO-075 | Not applicable |
Other Recommended Reading
| AA | Other Recommended Reading |
|---|---|
| S-INFO-075 | Not applicable |
Grade Deferrals of AAs from one year to the next
| AA | Grade Deferrals of AAs from one year to the next |
|---|---|
| S-INFO-075 | Unauthorized |