AI in Business (5 cr)

Evaluation scale

H-5

Schedule

This course is 100% virtual independent studies.

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

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 AI topics. All the course is taught virtually. Guest lecturers/experts on AI will also provide some lectures and these will be recorded as a webinar and placed onto the course. The contact classes and guest lectures will also include a small number of assessment tasks.

• Learning methods
• Virtual classes
• Tutorials
• Online lectures/webinars
• Independent study

Working life connections

Possible company visits and guest lecturers and workshops from different companies and organisations

Exam dates and re-exam possibilities

All assessment will be done in the virtual course as either assignments or online tests, based on the assignment tasks.

Internationality

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

Completion alternatives

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

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-(with Python code)
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

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.?

• Topic 1: Online multiple choice exam - (worth 20% and graded)
• Topic 2: Machine Learning task with data file using BigML or PowerBI - (Pass/Fail - worth 20%)
• Topic 3 & 4: Online Exam (Written & Multiple choice) & Long Assignment - (worth 40% graded)
• Topic 5: Online multiple choice exam - (worth 20% and graded)