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Course syllabus - Software Engineering for Artificial Intelligence

Scope

7.5 credits

Course code

DVA269

Valid from

Autumn semester 2023

Education level

First cycle

Progressive Specialisation

G1F (First cycle, has less than 60 credits in first-cycle course/s as entry requirements).

Main area(s)

Computer Science

School

School of Innovation, Design and Engineering

Ratified

2023-01-19

Literature lists

Course literature is preliminary up to 8 weeks before course start. Course literature can be valid over several semesters.

    • Ratified date: 2023-09-07
    • Latest update: 2023-09-07

    Books

    Sommerville, Ian

    Software engineering

    Tenth edition. : Boston : Pearson, 2016. - xiv, 796 pages

    ISBN: 9781292096131 LIBRIS-ID: 18431906

    Note: Main course literature. Previous editions (8 or 9) can also be used.

    Kniberg, Henrik

    Scrum and XP from the trenches : how we do Scrum

    2nd ed. : C4Media, cop. 2015 - 169 s.

    ISBN: 978-1-329-22427-8 LIBRIS-ID: 18635611

    Can be downloaded for free at www.infoq.com/minibooks/scrum-xp-from-the-trenches-2

Objectives

The course provides a general introduction to software engineering describing important concepts such as software processes, activities, languages, and tools used to engineer large complex Artificial Intelligence (AI) systems. 

Learning outcomes

After completing the course, the student shall be able to: 

1. Explain the main software development activities for developing AI systems.  
2. Explain the main software life cycle models and their differences. 
3. Select and use proper notations and tools for different life cycle models and activities. 

 

Course content

Software processes, requirements engineering, software architecture, design and implementation, verification and validation, UML. 

Specific requirements

Programming 7.5 credits, Data Structures, Algorithms and Program Development 7.5 credits,  Artificial Intelligence 7.5 credits (of which 5 credits must be completed at the start of the course), and 7.5 additional credits in computer science. 

Examination

Laboratory work (LAB1), A series of laboratory exercises that are reported according to instructions, 2.5 credits, examines the learning outcome 3, marks Fail (U) or Pass (G). 
Written examination (TEN1), 5 credits, examines the learning outcomes 1-3, marks Fail (U), 3, 4 or 5. 

A student who has a certificate from MDU regarding a disability has the opportunity to submit a request for supportive measures during written examinations or other forms of examination, in accordance with the Rules and Regulations for Examinations at First-cycle and Second-cycle Level at Mälardalen University (2020/1655). It is the examiner who takes decisions on any supportive measures, based on what kind of certificate is issued, and in that case which measures are to be applied.

Suspicions of attempting to deceive in examinations (cheating) are reported to the Vice-Chancellor, in accordance with the Higher Education Ordinance, and are examined by the University’s Disciplinary Board. If the Disciplinary Board considers the student to be guilty of a disciplinary offence, the Board will take a decision on disciplinary action, which will be a warning or suspension.

Grade

Pass with distinction, Pass with credit, Pass, Fail

Interim Regulations and Other Regulations

The course overlaps with 6 credits towards DVA312/DVA332 Software Engineering 1: Basic Course.