AI Series: Prompt Engineering (5cr)
Code
General information
- Enrollment
- 01.09.2025 - 20.07.2026
- Registration for introductions has not started yet.
- Timing
- 01.09.2025 - 31.07.2026
- The implementation has not yet started.
- Number of ECTS credits allocated
- 5 cr
- Institution
- LAB University of Applied Sciences, Verkkokampus
- Teaching languages
- English
- Seats
- 0 - 2000
- Course
- C-10126-AT00DH89
Unfortunately, no reservations were found for the realization AI Series: Prompt Engineering C-10126-AT00DH89-3001. It's possible that the reservations have not yet been published or that the realization is intended to be completed independently.
Evaluation scale
Approved/Failed
Content scheduling
Unlock the potential of AI by mastering the art of Prompt Engineering. This course provides students a comprehensive understanding of how to effectively communicate with AI models through well-crafted prompts. Learn to guide AI models to perform tasks accurately and efficiently by giving clear and precise instructions.
Objective
- Introduction to Prompt Engineering: Understand the basics of prompt engineering and its importance in AI interactions. - Understanding Language Models (LLMs): Learn how language models work, their architecture, and how they process and generate text. - Basic Prompt Techniques: Explore the core elements of crafting prompts, including role prompting and few-shot prompting. - Advanced Prompt Techniques: Dive into more complex prompting methods like Chain of Thought (CoT), Zero Shot Chain of Thought, self-consistency, and generated knowledge. - Evaluating and Refining Prompts: Learn how to assess the effectiveness of your prompts and refine them for better results. - Prompt Hacking: Discover the risks associated with prompt engineering, including prompt injection, prompt leaking, and jailbreaking.
Location and time
All the needed material is in the course. This also includes videos, ebooks and audio lessons.
Teaching methods
Independent online course
International connections
Moodle
Student workload
The course offers 5 ECTS credits worth of content