AI in Business (5 cr)

Evaluation scale

H-5

Schedule

The course will run intensively with live online Zoom support webinars over 3 week period starting 24.05 -11.06. These will be designed to support the topics, introduce the content and provide opportunities to interact with the course instructor (webinars will be recorded for those that cannot join live).

After 11.06 students will be able to work independently on the course assessments in their own time over the summer. All support materials will be active during the summer. The course will start week 21 (24.05) and finish in officially in week 33 (20.08). All assessments will need to be returned by Friday 20th August for final grades to be released and verified by the course instructor.

Implementation methods, demonstration and Work&Study

a) Learning with contact teaching including assignments, project work, independent study and exams
b) Virtual learning including virtual study with assignments, project work via the Internet, project execution as a webinar and exams:

Materials

The main book to use for this course is: Artificial Intelligence: 101 Things You Must Know Today About Our Future, Lasse Rouhiainen, ISBN: 1982048808 (50 page free sample will be provided for all students).

Materials will be provided in the course such as:
• Learning materials
• Books on the?content topics???
• E-books and online articles??
• Online tutorials???
• Companies’ web?portals?
• Relevant media, news agencies, quality press, etc.??
• Exercises, tests??
• Instructors’ own materials, materials produced by students.

Teaching methods and instruction

This course introduces the impact of AI in business and introduces students to a number of current AI topics. The course is taught virtually, but there will be option for students to also join live interactive webinars in addition to some guest lecturers and AI experts. The course will include a small number of assessment tasks based around the following teaching instruction:

• Virtual classes
• Inquiry learning??
• Peer-to-peer learning??
• Tutorials
• Lectures and live webinars
• Independent study and teamwork???

Working life connections

Possible networking opportunities with AI experts and guest lecture workshops from different companies and organisations.???

Exam dates and re-exam possibilities

All assessment will be done in the course through assignments and or via Moodle quiz/exams.
• Virtual course assignments x2 (60%)
• Guest lectures and webinar tasks (40%)

Internationality

Possibility to?operate?with international teams?and international lectures. Possible guest lecturers from international organisations and partner universities.?

Completion alternatives

Virtual learning including virtual study with assignments, independent study, project work, interactive webinars and online exams.

Learning assignments

Contents
There are five key topics covered in the course module:
Topic 1: An Introduction to Artificial Intelligence
Topic 2: Machine Learning in Business and applications
Topic 3: Robotics in Business
Topic 4: Artificial Intelligence in Business and Society
Topic 5: The Future of Artificial Intelligence

Grade 1
The student?has?some?understanding of?AI in business used in the module. He/She?is able to communicate at a minimal level?with AI in business terminology and theory. The student is able to operate?only?when?aided by other students and supervisors.

Grade 3
The student?is able to?understand most concepts in?AI in business within the module. He/She?is able to communicate at an intermediate level?with AI in business terminology and theory. He/She is able to discuss and write assessment tasks with reference to some AI academic materials mostly independently. ?

Grade 5
The student?is able to?understand concepts in?AI in business within the module. He/She?is able to communicate fully independently with AI in business terminology and theory. He/She is able to discuss and write assessment tasks with reference to AI academic materials independently. He/She applies an entrepreneurial problem-solving approach to their project work.

Assessment methods

• Virtual course assignments x2 (60%)
• Guest lectures and webinar tasks (40%)

Detailed assessment can be checked from implementation plans. The self-assessment of one's own learning does not influence the module grade. The self-assessment and students’ feedback to the module will be used for the module development. The feedback is collected?in?an electronic form.?