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Course details

Course Includes:

  • Intakes:Jan /Apr /Jul /Oct
  • Duration:12 months
  • ECTS:60 credits
  • Mode:Face-to-face
  • Language:British English
  • MQF Level / EQF Level :Level 7
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Post Graduate Diploma in Computer Science (Data Science and Artificial Intelligence)

The Post Graduate Diploma in Computer Science (Data Science and Artificial Intelligence) is a graduate-level programme that focuses on advanced, research-led learning in the fields of data science and artificial intelligence. The programme aims to equip students with the knowledge and technical skills required to design, develop, and apply intelligent systems across a wide range of domains in research and industry. It integrates theoretical foundations with practical applications, enabling students to develop a deep understanding of how AI technologies can be used to solve complex real-world problems.

The overall programme curriculum covers a broad range of subjects, including machine learning, deep learning, natural language processing, computer vision, reinforcement learning, and data science techniques. Students develop the ability to design and implement AI systems using various programming languages, tools, and software development methodologies. They also learn to evaluate and optimise system performance through techniques such as data preprocessing, feature extraction, model selection, and hyperparameter tuning. The programme further enables students to understand ethical, social, and professional issues in AI, including bias, privacy, transparency, and explainability. Practical components and research-focused activities allow students to gain hands-on experience, enhance analytical and problem-solving skills, and contribute to the field through research, publications, and presentations.

The programme is designed to combine theoretical knowledge with practical and research-oriented applications, preparing students for advanced roles in the rapidly evolving field of artificial intelligence and data science.

  • PROGRAMME OVERVIEW
    Programme Title Post Graduate Diploma in Computer Science (Data Science and Artificial Intelligence)
    Provider Ascencia Malta LTD
    Licence Number 2021-018
    Institution Category Higher Education Institution
    Accrediting Body Malta Further & Higher Education Authority
    MQF/EQF Level Level 7
    Total ECTS 60
    Total Learning Hours 1500
    Contact Hours 300
    Supervised Placement/Practice Hours 75
    Self-Study Hours 800
    Assessment Hours 325
    Mode of Delivery Fully Face-to-Face Learning
    Mode of Attendance Full-Time
    Duration(Full-Time)/(part-time) 12 months / 24 months
    Language of Instruction British English
    Delivery Address Floriana Campus: 23, Vincenzo Dimech Street, Floriana, Malta
    Swieqi Campus: 88, 90 Triq It-Tiben, Swieqi SWQ 3034, Malta
    Assessment Methods Individual and group reports, presentations, written exams, multiple-choice exams, assignments, and thesis
  • TARGET GROUP AND ENTRY REQUIREMENTS

      Target Group :

      The Post Graduate Diploma in Computer Science (Data Science and Artificial Intelligence) is a graduate-level programme designed for both national and international students who wish to develop advanced knowledge and technical expertise in Artificial Intelligence and Data Science. The programme is particularly suitable for graduates from Computer Science, Information Technology, and STEM-related disciplines who aim to specialise in areas such as machine learning, data analysis, and intelligent systems. It also attracts professionals seeking to enhance their technical capabilities, transition into AI-focused roles, or advance their careers in rapidly evolving technology-driven industries.

      Entry Requirements :

      Applicants to the Post Graduate Diploma in Computer Science (Data Science and Artificial Intelligence) programme should have:

    • A Bachelor’s degree in Computer Science, Information Technology, or a STEM-related subject
    • Applicants without the required academic background may be considered based on relevant professional experience (typically 2 to 5 years in the industry), subject to individual assessment
    • A good command of scientific English, demonstrated by an IELTS score higher than 7.0 (or equivalent), unless the previous degree was completed in a primarily English-speaking country
    • Applicants will also have the opportunity to apply for the programme based on Ascencia Malta’s Recognition of Prior Learning (RPL) process. Candidates will be required to present their previously obtained qualifications, along with their academic transcripts

      • The programme forms part of the main Computer Science track and provides specialised training in Data Science and Artificial Intelligence through a research-led approach.

  • RELATIONSHIP TO OCCUPATION

    The Post Graduate Diploma in Computer Science (Data Science and Artificial Intelligence) will prepare students for the following occupations:

    • Data Scientist
    • Data Engineer
    • Data Analyst
    • Research Analyst
    • Software Engineer
    • Machine Learning Engineer
    • Senior Data Scientist
    • Data Science Team Lead
    • Senior Research Analyst
  • PROGRAMME LEARNING OUTCOMES

    5.1 Knowledge and Understanding

    The learner will be able to:

    • Develop an advanced understanding of artificial intelligence theories and techniques, including machine learning, deep learning, natural language processing, computer vision, and reinforcement learning.
    • Understand the principles and methodologies required to design and implement AI systems using appropriate programming languages, tools, and software development approaches.
    • Understand methods for evaluating and improving the performance of AI systems, including data preprocessing, feature extraction, model selection, and hyperparameter tuning.
    • Demonstrate awareness of ethical, social, and professional issues in AI, including bias, privacy, transparency, and explainability, and understand their implications in real-world applications.
    • Understand research methodologies in artificial intelligence and the processes involved in contributing to the advancement of the field through scholarly work.

    5.2 Skills

    The learner will be able to:

    • Design and implement AI systems using appropriate technologies, programming languages, and development methodologies.
    • Evaluate and optimise the performance of AI models using advanced analytical and computational techniques.
    • Apply machine learning and data science techniques to solve complex real-world problems across various domains.
    • Make informed decisions by considering ethical, social, and professional implications in the development and deployment of AI systems.

    Conduct independent research in artificial intelligence, including problem formulation, data analysis, model development, and communication of findings through reports, presentations, and publications.

  • TEACHING, LEARNING, AND ASSESSMENT
    • Face-to-face lectures with practical applications
    • Case study analysis
    • Group discussions
    • Guest lectures from industry practitioners
    • Workshop-based sessions
    • Supervised independent research

    Grading

    Grade Classification
    70–100% Distinction
    60–69% Merit
    50–59% Pass
    40–49% Marginal Fail
    0–39% Fail

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