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CM52044: Reading module in artificial Intelligence and machine learning

[Page last updated: 22 April 2025]

Academic Year: 2025/26
Owning Department/School: Department of Computer Science
Credits: 10 [equivalent to 20 CATS credits]
Notional Study Hours: 200
Level: Masters UG & PG (FHEQ level 7)
Period:
Academic Year
Assessment Summary: CWES 70%, CWOI 30%
Assessment Detail:
  • Research seminar presentation (CWOI 30%)
  • Literature review (CWES 70%)
Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Requisites:
Learning Outcomes: 1. Summarise, critique, contrast, and compare AI & ML research papers. 2. Distinguish various research themes in AI & ML and highlight broad research aims. 3. Disseminate a perspective on a research paper or topic in AI & ML to an academic audience.


Synopsis: "You will explore a specific topic in artificial intelligence and machine learning at research level. You will summarise, critique, and compare research papers, consider the broader motivations and aims around the research topic, and disseminate your perspective to an academic audience. "

Content: Typically, this unit will include: Guest lectures by researchers in the department (lecturers, postdocs, PhD students) Attendance at research group seminars given by internal or external speakers Reading and discussing a selection of research papers Giving a seminar Writing a report

Course availability:

CM52044 is Optional on the following courses:

Department of Computer Science
  • USCM-AFM01 : MComp(Hons) Computer Science (Year 4)
  • USCM-AAM02 : MComp(Hons) Computer Science with Study year abroad (Year 5)
  • USCM-AKM02 : MComp(Hons) Computer Science with Year long work placement (Year 5)
  • USCM-AFM27 : MComp(Hons) Computer Science and Artificial Intelligence (Year 4)
  • USCM-AAM27 : MComp(Hons) Computer Science and Artificial Intelligence with Study year abroad (Year 5)
  • USCM-AKM27 : MComp(Hons) Computer Science and Artificial Intelligence with Year long work placement (Year 5)

Notes:

  • This unit catalogue is applicable for the 2025/26 academic year only. Students continuing their studies into 2026/27 and beyond should not assume that this unit will be available in future years in the format displayed here for 2025/26.
  • 好色tv and units are subject to change in accordance with normal University procedures.
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