Artificial intelligence

The course presents a range of central AI techniques and provides the students with an extensive toolbox for solving problems in practice.
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Schedule:

Teaching time:

Daytime

Location:

Online
Espoo

Topic:

Information and communications technology

Form of learning:

On-campus
Online

Provider:

Aalto University, FITech

Level:

Advanced

Credits:

5 By Aalto University (ECTS)

Fee:

Free of charge

Application period:

7.11.2022 – 4.1.2023

Target group and prerequisites

Programming skills, data structures and algorithms, basics of probability theory and linear algebra.

Course description

The course presents a range of central AI techniques and provides the students with an extensive toolbox for solving problems in practice.

For applications that require high degree of adaptation, specific techniques such as (deep) machine learning, reinforcement learning, and graphical models are included. These methods are instrumental for decision under uncertainty. For the purposes of knowledge representation and reasoning, different logical representations such as formulas and rules are covered. These representations establish the foundations for declarative problem solving and enable the use of state-of-the-art solver technology to search for solutions. The course also encourages students to combine the logical and machine learning perspectives when solving future problems.

Artificial intelligence (AI) tackles complex real-world problems, such as question answering, speech recognition, social network analysis, and task scheduling, with rigorous mathematical methods and tools. The goal of this course is to give an in-depth introduction to AI methodology while approaching the topic from the perspective of concrete application problems.

Learning outcomes

Having completed the course, you have

  • gained a comprehensive overview of AI and understand its fundamental principles related to machine learning and logical reasoning.
  • excellent premises for solving real-world problems with modern AI techniques and building intelligent systems by implementing such techniques.

Course material

The course material will be available on the course page.

Completion methods

  • Mandatory weekly homework, including programming tasks
  • The course can be completed online excluding the exam on campus (material and homework online).
  • Exam on Thu 20.4.2023 at 17.00–20.00.
  • Updated:
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