ACIT4040 Applied Artificial Intelligence Project Course description

A real artificial intelligence project will be carried by a large team of students. A practical application will be targeted using state-of-the-art methods and tools. The students will construct a working system from scratch, implementing machine learning components as well as using existing tools. The students are involved in the entire process, starting from earlier design choices to the AI system completion. Examples of tasks may include speech processing and image recognition, robots or drones navigation, self-driving vehicles, and chatbots.

Through this course, the students will gain an in-depth understanding of "AI in practice", as opposed to "AI in theory" or "AI on toy problems".

It is highly recommended that the student has taken the courses Advanced Machine Learning and Deep Learning and/or Evolutionary AI and robotics. It is also recommended to have good programming skills, such as 20 ECTS of previous programming-focused subjects.

No formal requirements over and above the admission requirements.

Upon successful completion of the course:

Knowledge

The student:

• understands why, when and how to use AI methods in realistic problems that they may encounter in their technical careers
• knows how to produce the necessary technical documentation
• understands how to manage a project in its expertise domain

Skills

The student:

• can work in a large group with a vaguely defined problem statement
• can assess different frameworks and tools for artificial intelligence in given contexts
• can build systems that realise aspects of intelligent behaviour
• can take part in the design and implemention of a relatively large AI project
• can debug AI applications and correct bugs at a system level (integration)

General competence

The students

• can work in a project within their specific expertise area
• is able to make decisions based on limited information
• is able to tolerate previous decisions when they turn out to be suboptimal and can evaluate them when better information becomes available

Introduction to modern methods, techniques and tools used in projects related to the course assignment. Lectures and tutorials will be given on the tools, laboratories and facilities available at OsloMet, and their use in relation to the given assignment text, specifications, design, verification, prototyping and development. A realistic project will then be carried out where participants work together as an "applied artificial intelligence development team".

The project involves the full process from specifications, programming, testing, verification and documentation.

The project work will be carried out in groups of a size suited for the assignment and focused around the relevant laboratories at OsloMet. The groups are relatively large, with 5-20 students.

The following required coursework must be approved before the student can take the exam:

• Minimum 80% attendance in workshops
• A final group (5-20 students) presentation.

Project report in groups (between 10000 and 25000 words) (100%)

The exam grade can be appealed.

New/postponed exam

In case of failed exam or legal absence, the student may apply for a new or postponed exam. New or postponed exams are offered within a reasonable time span following the regular exam. The student is responsible for applying for a new/postponed exam within the time limits set by OsloMet. The Regulations for new or postponed examinations are available in Regulations relating to studies and examinations at OsloMet.

All aids are permitted.

Grade scale A-F.

Two internal examiners. External examiner is used periodically. 

Ola Huse Ramstad