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[ 536AIBAIAIV19 ] VL Introduction to AI
Versionsauswahl
Workload Education level Study areas Responsible person Hours per week Coordinating university
3 ECTS B1 - Bachelor's programme 1. year (*)Artificial Intelligence Johannes Fürnkranz 2 hpw Johannes Kepler University Linz
Detailed information
Original study plan Bachelor's programme Artificial Intelligence 2025W
Learning Outcomes
Competences
Students understand and are able to explain the fundamental theoretical principles, models, and techniques of Artificial Intelligence, including its historical development and core subfields.
Skills Knowledge
  • Understanding the historical development of AI (k2)

Students are able to describe the theoretical foundations and historical evolution of AI, including key milestones, scientific breakthroughs, and shifts in paradigms.

  • Analyzing Theoretical Foundations of Reasoning and Knowledge Representation (k4)

Students can explain formal models of knowledge representation and logical reasoning.

  • Exploring theoretical aspects of Machine Learning (k3)

Students are able to differentiate between fundamental machine learning approaches (supervised, unsupervised, and reinforcement learning) and understand their mathematical underpinnings and theoretical limitations.

Students have theoretical knowledge of AI’s core subfields, including reasoning and knowledge representation, machine learning, natural language processing, and reinforcement learning, with an emphasis on formal models and foundational principles. They understand AI’s historical background and its theoretical challenges.
Criteria for evaluation Three written online exams.
Language English
Study material To be found on moodle.
Changing subject? No
On-site course
Maximum number of participants -
Assignment procedure Direct assignment