Show/hide contentOpenClose All
Curricular information is subject to change
At the end of this module, the student will be able to:
1. Organise scientific events for scholarly exchange.
2. Design a scientific programme.
3. Coordinator all stakeholders to ensure the program is executed within the required timeframe and resources.
4. Prepare training materials for the event.
5. Prepare scientific posters and branded materials.
6. Participate in scientific panel discussions.
7. Organise datathons.
8. Engage in discussions of cutting edge machine learning techniques.
9. Engage in discussions of the impacts of machine learning on society.
The key topics that will be involved in the Summer School module include:
-- Presentations on cutting-edge machine learning
-- Workshops on the social implications of machine learning
-- Presentations by PhD candidates within the centre
-- Workshops of critical skills for PhD resaerch
-- Group development activities such as hackathons and ideation sessions.
Student Effort Type | Hours |
---|---|
Specified Learning Activities | 25 |
Autonomous Student Learning | 100 |
Total | 125 |
Not applicable to this module.
Resit In | Terminal Exam |
---|---|
Autumn | No |
• Group/class feedback, post-assessment
Delivered after key stages within the module.