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UniWA BSc on Artificial Intelligence and Data Science

University of West Attica’s new BSc Program on Artificial Intelligence & Data Science aspires to be the first undergraduate program in Artificial Intelligence & Data Science in Greece. The UniWA BSc on AI & DS aims at combining the study of Artificial Intelligence and modern computing techniques so as to provide students with the in-depth knowledge and hands-on skills required to leverage large amounts of different modalities of data (image, video, text, language, sensor data, big data) to derive actionable decisions, and intelligent systems that can operate autonomously in the course of improving or complementing human capabilities, solve problems and navigate the uncertainty of our complex modern world. 

The program offers a broad and flexible curriculum that includes coursework in computer science, electronics, communication and engineering, mathematics, statistics, machine learning, symbolic computation, automated reasoning, data science, and will feature a wide range of paradigms in areas like energy, transportation, education, the food sector and engineering.

With the increasing penetration of Artificial Intelligence in various facets of business, economy and society, a wide range of employers, from large multinational corporations to knowledge-intensive SMEs, as well as public organizations at local, national and international levels, seek graduates that combine in-depth artificial intelligence, computing and engineering skills with the ability to apply them to effectively and efficiently address the challenges their organizations are facing, as well as help them acquire better insights and drive innovation in their activities. Substantial opportunities exist nowadays, and even more will arise in the near future, in almost all sectors of economic and social life, such as healthcare and wellbeing, biology and pharmaceuticals, food and nutrition, agriculture, finance, energy, games and creative industries, retail and public services. Furthermore, it is within the objectives of the new program to provide students with the necessary entrepreneurial competences that will help them build their own company and launch a new product.

Curriculum structure
Consistent with the 4-year engineering programs of UNIWA School of Engineering, the new program on AI & DS will have a duration of 8 semesters and will offer a Bachelor of Science degree upon graduation. The program will be organized by a Scientific Committee comprising faculty from six engineering departments (Informatics & Computer Engineering, Electrical & Electronic Engineering, Mechanical Engineering, Surveying and Geoinformatics Engineering, Industrial Design and Production Engineering, and Civil Engineering) as well as from the department of Food Science and technology. 

Students will take courses from five large course groups:

  • Mathematics and Theoretical Computer Science: calculus, linear algebra, statistics, probability, graph theory, computational thinking, etc.
  • ICT fundamentals: programming, computer networks, databases, computer architecture, signals and systems, high performance computing, etc.
  • Core AI-ML: symbolic AI, machine learning, deep learning, reinforcement learning, fuzzy systems and evolutionary computation, computer vision, etc.
  • Data Science: data mining, data visualization and analytics, big data management and analysis, natural language processing, social network analysis, etc.
  • Applications of AI: biomedical image analysis, remote sensing, AI in energy, IoT, smart cities and intelligent transport, robotics, autonomous systems, the food sector, etc.

Additionally, courses will be provided on disciplines where examples and paradigms of AI applications can impact and improve social, economic and business aspects, such as: ethical, legal and policy issues in AI, entrepreneurship and economics in AI. The final (8th) semester will be dedicated to the BSc dissertation of the students.

Cooperation with European and North American Universities
UniWA lays special emphasis on the cooperation with European and North American Universities and aims to enforce and extend existing ones, as well as establish new ones in the context of this new program. Indicative examples of the different forms of inter-university cooperation are given hereby:

  • Visiting scholars teaching specific courses (or parts thereof) or giving invited lectures or seminars (physically and/or remotely).
  • Students taking a semester of courses or completing their thesis work in a foreign University (and vice versa) (the Erasmus+ program can be leveraged where applicable).
  • Co-organizing initiatives such as workshops and summer/winter schools in Greece or abroad.

Cooperation with the industry
The UniWA AI program aims to encourage and support all students to gain industrial experience during their studies, mainly via internships. This will allow them to broaden and deepen their skills by combining academic knowledge with practical experience in the workplace, but also connects them with potential employers to assist them in shaping their future career. 

Agreements between the University and companies active in AI & DS will be sought, so that the latter support student internships as well as seminars and workshops in the context of specific program courses.

The BSc Program is organized by the Department of Informatics and Computer Engineering and the following UniWA partners:

  • Dpt. of Electrical and Electronic Engineering
  • Dpt. of Mechanical Engineering
  • Dpt. of Industrial Design and Production
  • Dpt. of Civil Engineering
  • Dpt. of Surveying and Geoinformatics Engineering
  • Dpt. of Food Science and Technology

Student Handbook

The Undergraduate Study Programme requires the successful completion of 36 courses, with 6 ECTS credits for each course, of which:

  • 29 are compulsory courses, with 174 ECTS credits, taught during the first seven semesters.
  • 6 are elective courses 36 ECTS credits. 2 courses are taught in the sixth semester and 4 in the seventh semester, respectively. The student can choose these courses from a pool of courses offered.

In the eighth semester the student is required to complete a final year project thesis (Final Year Project Thesis), which corresponds to 30 ECTS credits.

1st semester

  • Object-Oriented Programming
  • Matrices and Linear Algebra
  • Calculus
  • Discrete Mathematics
  • Fundamentals of Computer Engineering

2nd semester

  • Python Programming
  • Probability Theory – Statistics
  • Algorithms and Data Structures for Data Science
  • Introduction to Databases
  • Computer Architecture

3rd semester

  • Scientific Programming – MATLAB & R Programming
  • Computational Thinking
  • Introduction to Artificial Intelligence
  • Signal Processing
  • Computer Networks

4th semester

  • Human-Computer Interaction
  • Data Mining
  • Parallel Computing
  • Fuzzy Systems and Evolutionary Computation
  • Fundamentals of Machine Learning

5th semester

  • Big Data Management and Analysis
  • Deep Learning
  • Hardware for AI and Big Data
  • Privacy and Security in Data Science and AI
  • High Performance Computing

6th semester

  • Intelligent Learning Environments
  • Computer Vision
  • Natural Language Processing, Semantic Web & Social Networks Analysis
  • Elective 1
  • Elective 2

7th semester

  • Ethical, Policy and Legal Issues in Artificial Intelligence
  • Elective 3
  • Elective 4
  • Elective 5
  • Elective 6

8th semester

  • Final Year Project B.Sc. Thesis

List of Elective Courses

6th semester

  • Geographic Information Science
  • Advanced Statistics and Probability
  • Advanced databases
  • Internet of Things
  • Intelligent Control
  • Artificial Intelligence in Engineering Applications I

7th semester

  • Game Theory
  • Advanced Topics in Deep Learning
  • Data Streaming
  • Artificial Intelligence and Data science in the Food Sector
  • Machine Learning in Remote Sensing
  • Cryptography
  • Entrepreneurship in Artificial Intelligence & Data Science
  • Artificial Intelligence for Robotics & Autonomous Systems
  • Computer Graphics
  • Emerging Computing Paradigms
  • Artificial Intelligence in Engineering Applications II
  • Artificial Intelligence for Smart Grids and Power Systems
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