|
Teaching GuideTerm Faculty of Computer Science |
| Grao en Intelixencia Artificial |
 Subjects |
| Software Engineering |
| Learning aims |
|
|
|
| Identifying Data | 2023/24 | |||||||||||||
| Subject | Software Engineering | Code | 614G03009 | |||||||||||
| Study programme |
|
|||||||||||||
| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Graduate | 1st four-month period |
Second | Obligatory | 6 | ||||||||||
|
||||||||||||||
| Learning outcomes | Study programme competences | ||
| Carry out the process that allows, from the abstraction, to implement high quality code | A2 A3 |
B2 B6 B7 B8 B9 |
C2 C3 C6 |
| Acquire skills to solve problems in a methodological and practical way | A2 A3 |
B5 B6 B7 B8 B9 |
C3 C6 |
| Establish clearly and unambiguously the client's needs and constraints when developing requirements for a software project | B4 B7 |
C2 C6 |
|
| Analyze the alternatives to deal with and identify which aspects can be addressed with AI and which cannot | B2 B4 B7 B9 |
C3 C6 |
|
| Understand the principles needed to build complete, scalable, and robust, user-centered solutions where AI components fit together as part of a whole | A2 |
B8 B9 |
C6 |
| Be able to identify and understand models and designs of architectures and components to enable effective communication between software and data engineers | B4 |
C2 |
|
| Handle testing techniques and tools to ensure the quality of the results | A3 |
B8 B9 |
C6 |
|
