Artificial Intelligence and Data Science - MSc - CITY College, University of York Europe Campus
Κολέγιο CITY College
Main Campus, Thessaloniki, Greece

Artificial Intelligence and Data Science - MSc

Degree title: The title of Master of Science in Artificial Intelligence and Data Science is awarded directly from the University of York
Duration: 1 year (full time) or 2 years (part time)
Mode of delivery: Classes take place during weekends (16 weekends from October to June)
Language of instruction: English

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Industry Collaborations:
(in alphabetical order)

Industry Collaborations

The Computer Science Department of CITY College, University of York Europe Campus has established strong links with the industry, which include collaborations and partnerships with many companies and organisations. Students benefit from the department's links to the industry in multiple ways (i.e. opportunities for job placements, internships, real-life projects and more).


The programme

The past decade has seen an explosion of advancements in Artificial Intelligence and in particular Deep Learning. These advancements have come in a time when (and some would argue are because of) we are now producing and storing online information with an exponential growth. This has led to a great impact in all aspects of businesses, from trading, to production and industry. The fourth industrial revolution is based on the availability and organisation of information, and in a world where information has become too much to handle, Artificial Intelligence has found fertile ground on which to grow. As a result, AI and Data Science are both in great demand.

  • Become a high calibre professional, well-equipped to pursue successful career in the Artificial Intelligence and Data Science industry;
  • Learn the rich theoretical underpinnings in several areas of the Artificial Intelligence and Data Science discipline;
  • Become knowledgeable of the methods which aim to ensure ethics, the reliability and the quality of Artificial Intelligence and Data Science solutions;
  • Become knowledgeable of contemporary Artificial Intelligence and Data Science technologies and their application in the development of modern applications;
  • Gain practical experience, by participating in a group project proposed with collaboration with industries operating in the Artificial Intelligence and Data Science field;
  • Dive deep into contemporary issues on Artificial Intelligence and Data Science by becoming an expert practitioner and researcher of the field.

 

Why choose this course?

  • Degree from one of the world’s top un​iversities, the University of York.
     
  • Graduates will have the knowledge and skills to become high calibre professionals, well-equipped to pursue successful career in the Artificial Intelligence and Data Science industry.
     
  • Flexible delivery mode: classes at weekends.
     
  • World-class, research-led teaching combined with hands-on practice.
     
  • 90% of the Computer Science Department graduates find employment right after graduation.
     
  • Opportunities for placements and internships assisting students to embark their career while studying.
     
  • Practical experience, by participating in a group project proposed with collaboration with industries operating in the Artificial Intelligence and Data Science field  
     
  • Excellent career prospects in Europe and in the world. The value and status of the University of York degree, as well as the valuable skills and knowledge gained during studies reflect the excellent career prospects of our graduates.
     
  • Taught by excellent academic staff with extensive teaching and professional experience.

More reasons why:

 

Recognition of degress Accreditation and recognition The Department

Data Scientist Toolbox
Data Science Elements
Artificial Intelligence: Knowledge and Reasoning
Machine Learning
Deep Learning
Big Data
AI Ethics and Applications
Industrial Project
Research Skills and Dissertation Preparation
Dissertation

 

 

Data Scientist Toolbox
This module aims to help students acquire industrial skills and knowledge for project-based software development in the industry. The module provides fundamental knowledge on agile processes and continuous software quality management practices as well as hands-on experience on industry toolkits for continuous integration, deployment and delivery of software artefacts. Back to top

Data Science Elements
This module introduces students to the fundamental elements, concepts and techniques involved in Data Science applications. Students initially acquire a good understanding of database systems and the Linear algebra, probabilities and statistics concepts required in data science. Students will also gain experience in cleaning, transformation, analysis of data as well as visualisation of data. The module has a practical dimension through the use of an appropriate programming language. Back to top

Artificial Intelligence: Knowledge and Reasoning
Artificial Intelligence (AI) is the area of Computer Science with the ultimate goal to build intelligent machines, i.e. machines that exhibit human-like behaviour when solving complex problems. This module provides an in-depth introduction to explainable classic Artificial Intelligence. The three main pillars under which topics are presented are single intelligent agents, multi-agent systems and biology-inspired agents. The topics include the two main areas of classic AI presented from both theoretical and practical perspective, i.e. Knowledge Representation (logic and its variants, state-space representation, semantic and knowledge graphs, frames and ontologies, rules etc.) and Reasoning (resolution and refutation, search, knowledge retrieval, types of reasoning, rule-extraction in classic machine learning, backward and forward chaining etc.). The module will explicitly refer to agent models for practical reasoning and coordination, communication, collaboration and negotiation between agents. Nature-inspired agents will give an opportunity to touch upon swarm-intelligence, biological agents and will include human to artificial agent interfaces as well as emotional reasoning and simulation of collective intelligence. Back to top

Machine Learning
Machine learning is the part of Artificial Intelligence that studies how computers build experience and autonomously learn from data. The module will follow the standard machine learning taxonomy for organising problems and applying solution techniques, and will provide a thorough grounding in the theory and application of machine learning. Back to top

Deep Learning
Deep learning is a hot topic that has found multiple areas of application in the industry and business. Deep learning is the extension of Neural Networks (NN) that includes some new developments in training algorithms and uses the versatility of the computing power and data storage of the cloud. The module briefly introduces neural networks, explains how they work, how they are trained, and how they are deployed. Furthermore, it discusses the recent developments in training algorithms, NN structures, and cloud deployment, to conclude with the practical application of Artificial Intelligence solutions that we now call Deep Learning. Back to top

Big Data
This module explores a range of the most relevant topics that pertain to contemporary analysis practices, technologies, and tools for Big Data environments. Main aspects and challenges of Big Data will be addressed by introducing relevant algorithms and practices.
Additionally, this course provides a detailed description and hands-on experience to cutting-edge open-source software such as Apache Hadoop, Apache Kafka, Apache Airflow, Apache NiFi etc.
Students will be introduced and gain awareness, in a gradual manner, to the concepts, algorithms and techniques that cover key Big Data topics and will thoroughly use Apache Spark and Python for the coursework. Back to top

AI Ethics and Applications
Artificial Intelligence (AI) is the area of Computer Science with the ultimate goal to build intelligent machines, i.e. machines that exhibit human-like behaviour when solving complex problems. This module investigates the professional, legal and ethical dimensions when developing such capabilities in businesses and society. The module discusses the aforementioned issues from the perspective of raising awareness and developing Responsible Computing (RC) professionals that will see tomorrow’s development of Digital Society. Furthermore, this module will aspire to examine cases in various application areas of AI (such as Data Mining, Information Retrieval, Recommendation systems, Natural Language Processing (NLP), social network analysis and text mining) with a view of how these could developed with RC in mind as well as observing the Ethics Guidelines for Trustworthy AI published by EU. Back to top

Industrial Project
The purpose of this module is to provide students with the opportunity to integrate and apply the skills and the knowledge they have acquired so far in their studies to a realistic problem. Students are exposed to the processes involved in the team-based development of software through real projects that are provided by companies from the software industry. Back to top

Research Skills and Dissertation Preparation
Through this module, students develop their research skills and get prepared for working on their MSc dissertation. With the guidance of their supervisors, students are introduced to the research topics and techniques that are commonly employed in software engineering research. Students are exposed to and exercise the principles and practices of report writing, literature reviewing, and research designs and approaches. Back to top

Dissertation
For the dissertation, the students work individually on a project under the supervision of a lecturer. In the project students will be developing a software solution to a real problem using the skills and knowledge they acquired from all the modules, and from outside sources and materials they will investigate at the duration of the project. At the end students develop and practice research skills that will help them further develop in the future as AI and Data Science experts. Back to top

 

Entry requirements

Candidates should hold an undergraduate degree in Computer Science or a related degree. For candidates from other disciplines their substantial professional experience in software development will be considered.
View the application and admission requirements of the programme.

 

How to apply

If you wish to apply for this programme you may view details of the application process.

 

Any questions?

If you'd like to know more about this programme, contact our Admissions Team at
admissions@york.citycollege.eu

 

The Computer Science Department of CITY College, University of York Europe Campus provides excellent quality education driven by research and industrial needs, by developing and maintaining high standards in the provision of education and by deploying quality assurance procedures, with major aim to produce high calibre graduates, well-equipped to pursue successful careers in a wide range of contexts.

Students do not only acquire a sound theoretical understanding but they also gain practical experience, by applying their knowledge on real life projects. Students benefit from the research-led environment, since they are exposed to not only the well-established fundamentals in their courses, but also to the most advanced theories and techniques currently under consideration and they are encouraged to be involved in academic research activities. Students are taught by academic staff members who are passionate about developing and delivering high quality innovative and inspirational learning and teaching methods. Students benefit from the provision of personal support, which ensures their successful learning development. 
More about the Computer Science Department

 

Research at the Computer Science Department

The academic staff of the Computer Science Department

Contact the Computer Science Department

Recognition and Careers

Accreditation and Recognition
CITY College is strongly committed to quality education and academic excellence. It is officially accredited and recognised by top international accreditation bodies. Read more

Degree and formal qualifications
The degree and formal qualifications our graduates receive.

For Greek graduates only: Recognition of degrees

 

Career opportunities

As a graduate of this programme you will be working in the cutting edge research area, and in the forefront of the industry as an Artificial Intelligence and Data science expert, able to design and develop learning systems that radically change the way businesses work today. Furthermore, as a Data analyst, you will be able to identify patterns, analyse trends and suggest solutions to any business that deals with vast amounts of information.

 

Career, Employability and Enterprise Centre

The Career, Employability and Enterprise Centre, focuses on helping students to set attainable career goals. It offers advice on CVs and cover letters, and on how to effectively handle job interviews. Through career fairs, and different internship programmes, the department aims at constantly bringing students in contact with prospective employers. 

Every spring we organize the Annual Career Fair presenting with an opportunity to get a first feel of job seeking. During the event students and alumni have interview opportunities with corporate recruiters and present their skills and abilities to potential employers. Large companies, organisations and multinationals from different industries across S.E. Europe participate every year in our Career Fair and offer employment and internship opportunities to our students and graduates.
More about our Career Services.

Contact the Career, Employability and Enterprise Centre at careers@york.citycollege.eu

 

The programme is taught by academic staff members who have extensive teaching and professional experience. The administration staff fully supports all processes of the department and provides a wide range of services to our students.

Dr. Dimitris Dranidis

“The programme is taught by academic staff members who are highly skilled educators and are characterised by high quality and inspirational teaching. Important values of our teaching approach are student engagement and participation, constructive feedback, continuous student support, high utilisation of learning technologies, and focus on skills for students' professional development. Three academic staff members of the department are recognised for their excellence in learning and teaching by receiving the Senate Award for Excellence in Learning & Teaching. Our teaching is further informed by the research performed by academic staff members involved in research projects funded by the European union. The administration staff of the department is dedicated to fully support all processes of the department and provide a wide range of services to our students.”

Dr. Dimitris Dranidis
Head of the Computer Science Department

 

 

The academic staff & administration staff of the Computer Science Department

 

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