Basic notions, definitions, and concepts of artificial intelligence, machine learning
Theory of probability
K-Means clustering, decision Trees support vector machines, bagging and boosting
Introduction to deep learning, neural networks, and multi-layer perceptron
Convolutional neural networks
Object detection networks
Image segmentation networks
Introduction to reinforcement learning
Objective
The students will gain an overview of artificial intelligence methods and their applications in the engineering field.
By finishing programming assignments using educational robots, the students learn to overcome practical obstacles when working with real life sensor data, actuators, and programming interfaces.
Study Material
The lectures will use power point slides and will be split into the different topics.
For each topic the connection to the fundamental origins (such as neural networks in human brains) will be presented as well as its connection to the engineering domain.
The students will learn to apply their knowledge on a practical localization problem using GoPiGo robot kits which will be provided to them.
The robot assignment will be performed in small teams of students.
Recommended Reading
Russell, S., Norvig, P., Canny, J., Malik, J., & Edwards, D. (1995). Artificial Intelligence: A Modern Approach. Prentice hall Englewood Cliffs.
Krishnamoorthy, C. S., & Rajeev, S. (1996). Artificial Intelligence and Expert Systems for Engineers. CRC Press LLC.
