Instructional goals
The common framework of this course aims to provide students with a foundational understanding of Artificial Intelligence (AI) and its applications across various domains. By the end, successful students will be able to: Understand the basic concepts, principles, and evolution of AI. Recognize AI in everyday life and professional contexts. Assess the potential benefits and risks of AI technologies. Engage critically and participate in informed discussions about AI and its societal implications.
Prerequisites
N.A.
Intended learning outcomes
Understand the Fundamentals of AI: Demonstrate a solid understanding of the fundamental theoretical concepts, operating principles and evolutionary stages that have characterized the development of Artificial Intelligence. Identify Applications of AI: Recognize and analyze manifestations of AI in everyday scenarios and professional settings, highlighting its pervasiveness and impact. Critically Evaluate AI: Develop the ability to discern and weigh the potential benefits and inherent risks associated with implementing AI technologies.
Course Contents
The program consists of a theoretical part with an introduction to the terminology and basic concepts, the practical part is intended to enhance the use of the technological tools to search, collect, evaluate, produce and present information.
Reference Books
Slilde and materials provided in class
Teaching Methods
The teaching methods used during the course are as follows: - teaching (online / on campus). - exercises (online / on campus).
Assessment Method
The final grade will derive from the evaluation of the following items for the respective percentage share: 50% attendance 10% active participation during classes 40% final test
Thesis assignment criteria
n.a.
Week 1
Introduction to AI Describe AI and its subfields (e.g., machine learning, deep learning, natural language processing, Generative AI, etc.). Explore the history and evolution of AI.
Week 2
AI Techniques and Algorithms Understand key AI techniques and algorithms.
Week 3
AI Applications Examine AI applications in various fields
Week 4
Ethical and Societal Implications Discuss the ethical challenges and explore the societal impact of AI (including regulations and governance). AI and the Future Consider potential future developments in AI and its potential role in the future of society.
Week 5
Prompting techniques – Hands-on session Focuses on the art of crafting effective prompts for AI models Introduction, question answering and text classification AI prompting importance and applications Discusses types of prompts such as zero-shot, few-shot, and fine-tuning. Techniques for designing prompts for question answering Prompting strategies for text classification tasks
Week 6
Information Extraction, Summarization and Critical Reasoning – Hands-on session Explores how prompts can be used to extract information from text, summarize content, and enhance critical reasoning in AI models. Designing prompts for extracting structured information from text Named entity recognition (NER) and relation extraction Approaches to prompt-based text summarization Abstractive vs. extractive summarization Quality assessment techniques Prompts for enhancing critical reasoning in AI models
Week 7
Identity and objectives Defining the AI model's identity and objectives: Establishing clear goals for the AI model. Defining the Identity of the AI Model Role of Identity in Prompt Design Clarifying the Objective of the prompt Evaluation Metrics for Objective Alignment Incorporating Context into Prompts
Week 8
Input Data and Output Style & Format Providing relevant and structured input/output data for optimal performance. Selecting and Formatting Input Data Handling Diverse Data Sources Designing Prompts for Desired Output Style Formatting Outputs for Clarity and Usability
Week 9
Task Decomposition and Advanced Topics – Hands-on session Breaking down complex tasks into smaller, more manageable prompts. Breaking Down Complex Tasks into Manageable Prompts Performance evaluation and optimization Challenges and Solutions Recent Advancements in Prompt Structuring Use cases and applications
Week 10
n.a.
Week 11
n.a.
Week 12
n.a.