ACS6427 Data Modelling and Machine Intelligence
By the end of the modules students will be able to:
This module satisfies the AHEP3 (Accreditation of Higher Education Programmes, Third Edition) Learning Outcomes that are listed in brackets after each learning outcome above. For further details on AHEP3 Learning Outcomes, see the downloads section of our accreditation webpage.
Learning and Teaching Methods
NOTE: This summary of teaching methods is representative of a normal Semester. Owing to the ongoing disruption from Covid-19, the exact method of delivery will be different in 2020/21.
Lectures: 18 hours
Learning and Teaching Materials
Al lecture slides will be provided as handouts with space to take notes. Matlab “helper” software will be provided for the labs. All resources will be available on Blackboard (MOLE) as will vodcasts of the lectures.
Formal exam (50%) 2 hrs in Autumn exam period.
Blackboard (MOLE) quizzes x4 (6.25% each)
Examples will be presented in class that provide an opportunity for you to gauge your understanding and to request clarification from the lecturer. Questions during lectures are welcomed.
Laboratory sessions provide a good opportunity for feedback and guidance on progress – this will be face-to-face & oral. Four Blackboard (MOLE) “quizzes” will take place & these will contain feedback available immediately the submission date is passed. The final assignment & examination will receive only summary feedback that you can access after they have been marked.
Students are encouraged to provide feedback during the module direct to the lecturer. Students will also have the opportunity to provide formal feedback via the Faculty of Engineering Student Evaluation Survey at the end of the module.
You can view the latest Department response to the survey feedback here.