Artificial Intelligence Applications

ΕΠ34 - Applications of Artificial Intelligence

General Information

School: Digital Technology

Department: Informatics and Telematics

Level: Undergraduate

Course Title: Applications of Artificial Intelligence

Course id: ΕΠ34

Type: Core Course 

Semester: 7

Teaching and Examination Language: Greek

Is the course offered in Erasmus: Yes

Course web-page: https://eclass.hua.gr/courses/DIT232/

Activities

Lectures (Theory): 3,0

Lab lectures: 0,0

ECTS credits: 5,0

Learning Outcomes

This course introduces students to the use of modern machine learning methods in Artificial Intelligence Applications. More specifically, the course focuses on on deep learning and its application in Computer Vision, Natural Language Processing and Reinforcement Learning problems.

General Skills

- Adaptation in new conditions
- Independent work
- Team work
- Decision making
- Promoting free, creative and deductive reasoning

Course Content

- Artificial Neural Network Training
- The Keras/Tensorflow deep learning framework
- Regularization
- Convolutional Neural Networks
- Image classification
- Visual object recognition
- Word embeddings
- Text classification
- Introduction to deep reinforcement learning and its applications

Learning and Teaching Methods - Evaluation

Teaching methods: face-to-face

Use of ICT: 

eclass course web page
use of AI frameworks and libraries

Course Organization

 

Activity

Semester work load

Lectures

39,0

Lab exercises

 

Individual of group projects

40,0

Lab report preparation

 

Thesis 

 

Independent Study

46,0

Total

125

Assessment

- Final examination (60%)
- Assignments (individual or in teams) (40%)

Literature

- Ian Goodfellow, Yoshua Bengio and Aaron Courville, “Deep Learning”, MIT Press, 2016 https://www.deeplearningbook.org/
- Charu C. Aggarwal, Neural Networks and Deep Learning: A Textbook, Springer, 2018
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, 2nd Edition, O' Reilly, 2019




 

Journals (indicative list):

IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Neural Networks and Learning Systems
Engineering Applications of Artificial Intelligence
Expert Systems with Applications
Journal of Machine Learning Research
Journal of Artificial Intelligence Research
Neural Computing and Applications
International Journal of Computer Vision

Conferences (indicative list):

Neural Information Processing Systems
International Conference on Learning Representations
AAAI Conference on Artificial Intelligence
Computer Vision and Pattern Recognition
International Conference on Computer Vision
International Joint Conference on Artificial Intelligence