DV1712 - Applied generative AI - Blekinge Institute of Technology

1. Descision

This course is established by Dean 2024-04-30. The course syllabus is approved by Head of Department of Technology and Aesthetics 2024-08-15 and applies from 2024-08-15.

2. Entry requirements

Admission to the course requires 30 completed credits in the main field of study Computer Science or Media Technology.

3. Objective and content

3.1 Objective

The aim of the course is for students to explore the basics of generative AI and large language models (LLMs) with a practical focus. The course covers the creation of text, images and other outputs of these models. The student examines features, architecture, training processes and practical implementation methods.

3.2 Content

Introduction to AI with a focus on neural networks and generative AI
Overview of applications (text generation, media synthesis, code generation, data synthesis)
History and trends, competing research trends
Core mechanisms and concepts of generative AI and LLMs
Tokenization, embeddings, attention mechanism, transformers architecture, zero-shot and few-shot learning, foundational models, self-supervised learning, multi-modal interaction
Fine-tuning and deployment
Using open-source tools and libraries for text and media generation
Techniques for fine-tuning models for specific tasks
Deployment process for generative AI models
Practical applications and case studies
Case studies on successful deployments of generative AI
Enhancing digital experiences with AI-generated content
Ethical considerations and responsible AI
Biases and other limitations of generative AI
Ethical implications of generative AI
Legal challenges and societal impacts

4. Learning outcomes

The following learning outcomes are examined in the course:

4.1. Knowledge and understanding

**On completion of the course, the student will be able to:

grasp the basics of generative AI and LLMs

comprehend the architectures and training processes of LLMs

account for understanding trends and potential future changes in generative AI

4.2. Competence and skills

On completion of the course, the student will be able to:

gain hands-on experience in setting up environments to use open-source models

learn techniques for fine-tuning and deploying generative AI models

apply theoretical knowledge in practical projects and labs

4.3. Judgement and approach

On completion of the course, the student will be able to:

Critically assess the impact and limitations of generative AI and LLMs

Understand trends and potential future changes in generative AI

Evaluate ethical implications and develop responsible AI practices

independently and critically evaluate their creative and aesthetic applications of generative AI

5. Learning activities

The course includes lectures, exercises, laboratories, and projects. Lectures provide the theoretical foundations essential for course understanding. Exercises, laboratories, and projects offer practical application of theoretical concepts, with group-based projects and laboratory work. The course also necessitates students to utilize their problem-solving skills to address challenges encountered during learning activities

6. Assessment and grading

Modes of examinations of the course

Code	Module	Credit	Grade
2505	Written assignment	1.5 credits	GU
2515	Project	3 credits	AF
2525	On-campus Examination	1.5 credits	AF

The course will be graded A Excellent, B Very good, C Good, D Satisfactory, E Sufficient, FX Failed result, a little more work required, F Fail.

The information before a course occasion states the assessment criteria and make explicit in which modes of examination that the learning outcomes are assessed.

An examiner can, after consulting the Disability Advisor at BTH, decide on a customized examination form for a student with a long-term disability to be provided with an examination equivalent to one given to a student who is not disabled.

7. Course evaluation

The course evaluation should be carried out in line with BTH:s course evaluation template and process.

8. Restrictions regarding degree

The course can form part of a degree but not together with another course the content of which completely or partly corresponds with the contents of this course.

9. Course literature and other materials of instruction

Course material from the department selected journal papers

This is not a legal document. If you would like a copy of the legal decision regarding this course plan, contact the registrar at Blekinge Institute of Technology.

Course syllabus