ΔΕΑL0204 ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING (Core Elective)

ΔΕΑL0204 ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING (Core Elective)

Course Information

Course Outline

Course Category
Course Type
Course Code
Semester
Contact Hours
ECTS Units
Division
Instructor

Graduate
Core Elective
ΔΕΑL0204
2nd (Spring)
3 hours/week
7.5
Production Management & Industrial Administration
Kostas Ampountolas

Course Category: Graduate
Course Type: Core Elective
Course Code: ΔΕΑL0204
Semester: 2nd (Spring)
Contact Hours: 3 hours/week
ECTS Units: 7.5
Division: Production Management and Industrial Administration
Instructor: Kostas Ampountolas

Scope
Learn artifical intelligence and machine learning methods and apply them in problems in supply chains, transportation, autonomous vehicles, and smart cities.
Contents
  • Introduction to Data Science and large-scale data analysis.
  • Artificial Intelligence (AI) and Machine Learning (ML) (search algorithms, statistical learning).
  • Supervised Learning (SVM, decision trees, logistic regression).
  • Artificial Neural Networks and Deep Learning (CNN, RNN, LSTM).
  • Reinforcement Learning and Unsupervised Learning (Clustering, k-means).
Bibliography
  • Russell, S. J., & Norvig, P. (2020). Artificial intelligence: A modern approach (4th ed.). Pearson.
  • Murphy, K. P. (2012). Machine learning: A probabilistic perspective. The MIT Press.
  • Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. The MIT Press.
Educational Material

Slides, R and Python languages, libraries (Keras, TensorFlow, PyTorch, Theano).

Language of Instruction

Greek or English.

Teaching Method

Lectures and Assignments.

Assessment
  • Written examination (50%)
  • Assignments (50%).
Workload (in hours)

190.