4007CEM Computer Science Activity Led Learning Project 2
Course Learning Outcomes Assessed:
B1: COMPUTATION THINKING:
Develop and understand algorithms to solve problems; measure and optimize algorithm complexity; appreciate the limits of what may be done algorithmically in reasonable time or at all.
B2: PROGRAMMING:
Create working solutions to a variety of computational and real world problems using multiple programing languages chosen as appropriate for the task.
B3: ARCHITECTURE:
Understand the underlying architecture that supports the modern computer, including traditional compilers and operating systems, but also the modern infrastructure of the internet and mobile applications.
B4: DATA SCIENCE:
Work with (potentially large) datasets; using appropriate storage technology; applying statistical analysis to draw meaningful conclusions; and using modern machine learning tools to discover hidden patterns.
B5: SOFTWARE DEVELOPMENT:
Take a product from the initial stage of requirement / analysis all the way through development to its final stages of testing /evaluation.
B6: PROFESSIONAL PRACTICE:
Understand professional practices of the modern IT industry which include those technical (e.g. version control / automated testing) but also social, ethical & legal responsibilities.
B7: TRANSFERABLE SKILLS:
Apply a wide variety of degree level transferable skills including time management, team working, written and verbal
presentation to both experts and non–experts, and critical reflection on own and others work.
B8: ADVANCED WORK:
Apply the above to advanced topics selected according to the interests of individual students.
