Data Science | Technology

Master of Science (MSC) in Computer Science (Data Science and Artificial Intelligence)

Graduates of the Master of Science (MSc) in Computer Science (Data Science and Artificial Intelligence) program will develop a deep understanding of the fundamental concepts and principles of AI, including machine learning, deep learning, natural language processing, computer vision, and reinforcement learning. Upon completion of the program, students will be able to design and implement AI systems, using a range of programming languages, software development methodologies, and tools. Students will develop the ability to evaluate the performance of AI systems and to use a variety of techniques to improve their performance, such as data pre-processing, feature extraction, model selection, and hyperparameter tuning. Students will become familiar with ethical, social and professional issues in AI, such as bias, privacy, transparency and explainability, and be able to navigate them and make informed decisions in their professional practice. Finally, students will have the ability to conduct original research in AI and to contribute to the advancement of the field through publications, presentations, and other forms of scholarly communication.

April/July/Oct 2024

Start Date

18 Months FT/ 36 Months PT

Duration

MQF L7

Certification

Ascencia Malta

Course Provider

€12,000 (FT)

Prerequisites

See Below

Basis

Full-Time | Part-Time

Location

In-Person

Course Fees

€12,000 (FT)

What you'll learn

  • Advanced understanding of AI theories and techniques: Graduates of the program should have a deep understanding of the fundamental concepts and principles of AI, including machine learning, deep learning, natural language processing, computer vision, and reinforcement learning
  • Ability to design and implement AI systems: Graduates should be able to design and implement AI systems, using a range of programming languages, software development methodologies, and tools
  • Ability to evaluate and improve the performance of AI systems: Graduates should have the ability to evaluate the performance of AI systems and use a variety of techniques to improve their performance, such as data pre-processing, feature extraction, model selection, and hyper-parameter tuning
  • Familiarity with ethical, social, and professional issues in AI: Graduates should be familiar with ethical, social and professional issues in AI, such as bias, privacy, transparency and explainability, and be able to navigate them and make informed decisions in their professional practice
  • Ability to conduct research and contribute to the advancement of AI: Graduates should have the ability to conduct original research in AI, and to contribute to the advancement of the field through publications, presentations, and other forms of scholarly communication

Prerequisites

  • Students who have no training in the field must have completed a bachelor’s in Computer Science, Information technology or a STEM subject. This applies to students applying for the MSc program, the Post-graduate certificate, the Post-graduate diploma and the awards
  • Students without the required background may be allowed to join the course depending on the student’s circumstances and background (2 to 5 years of industry experience may also be considered). Please find our RPL policy as authorised by the MFHEA at the end of the document
  • A good grasp of scientific English is also required in order to follow the course. Students will be asked to provide an IELTS certificate higher than grade 7 (or equivalent) or proof of an equivalent level of English before commencing the course if the student has not followed their BSc in a primarily English-speaking country

Candidates will be asked to present their previously obtained qualifications along with their respective transcripts.

Relationship to Occupation

      • Data scientist
      • Data engineer
      • Data analyst
      • Research analyst
      • Software engineer
      • Machine Learning engineer
      • Senior data scientist
      • Data science team lead
      • Senior research analyst

Fees

Full-time: €12,000
Part-time: €20,000

Course Provider

A participative and innovative pedagogy

Our training courses are based on a participative and innovative pedagogy based on the value of the example and the constant exchange between learners and experienced professionals. The realities of corporate life are at the heart of the personalised learning methods we use. They are intended to identify potentials and to hatch vocations of managers and business developers. Our campus is also open to all international candidates who wish to study management in Malta.

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