Accreditation:
EQF7
MaltaSwitzerlandWisconsinCaliforniaWashington
Workload:
1500 hours | 60 ECTS
Tuition cost:
20,000 THB

Postgraduate Diploma in Computer Science

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Kind
Diploma
Area
Computer & Mathematical Science
Mode
Fully Online
Language
Thai
Student education requirement
Undergraduate (Bachelor’s)
Standard length
12 months
Standard delivery length
12 months
Certificates
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\ Overview

The course teaches students comprehensive and specialised subjects in computer science; it teaches students cutting edge engineering skills to solve real-world problems using computational thinking and tools, as well as soft skills in communication, collaboration, and project management that enable students to succeed in real-world business environments. Most of this program is case (or) project-based where students learn by solving real-world problems end to end. This program has core courses that focus on computational thinking and problems solving from first principles. The core courses are followed by specialization courses that teach various aspects of building real-world systems. This is followed by more advanced courses that focus on research level topics, which cover state of the art methods. The program also has a capstone project at the end, wherein students can either work on building end to end solutions to real world problems (or) work on a research topic. The program also focuses on teaching the students the “ability to learn” so that they can be lifelong learners constantly upgrading their skills. Students can choose from a spectrum of courses to specialize in a specific sub-area of Computer Science like Artificial Intelligence and Machine Learning, Cloud Computing, Software Engineering, or Data Science, etc.

  • Target Audience

    • Ages 19-30, 31-65, 65+

  • Target Group This course is designed for individuals who wish to enhance their knowledge of computer science and its various applications used in different fields of employment. It is designed for those that will have responsibility for planning, organizing, and directing technological operations. In all cases, the target group should be prepared to pursue substantial academic studies. Students must qualify for the course of study by entrance application. A prior computer science degree is not required; however the course does assume technical aptitude; and it targets students with finance, engineering, or STEM training or professional experience.

  • Mode of attendance

    • Online

  • Structure of the programme

    • Please note that this structure may be subject to change based on faculty expertise and evolving academic best practices. This flexibility ensures we can provide the most up-to-date and effective learning experience for our students. The Post Graduate Diploma in Computer Science combines asynchronous components (lecture videos, readings, and assignments) and synchronous meetings attended by students and a teacher during a video call. Asynchronous components support the schedule of students from diverse work-life situations, and synchronous meetings provide accountability and motivation for students. Students have direct access to their teacher and their peers at all times through the use of direct message and group chat; teachers are also able to initiate voice and video calls with students outside the regularly scheduled synchronous sessions. Modules are offered continuously on a publicly advertised schedule consisting of cohort sequences designed to accommodate adult students at different paces. Although there are few formal prerequisites identified throughout the programme, enrolment in courses depends on advisement from Woolf faculty and staff.

  • Grading System

    • Scale: 0-100 points

    • Components: 60% of the mark derives from the average of the assignments, and 40% of the mark derives from the cumulative examination

    • Passing requirement: minimum of 60% overall

  • Dates of Next Intake

    • Rolling admission

    • Pass rates Cohort pass rates will be publicised in the next cycle, contingent upon ensuring sufficient student data for anonymization.

  • Identity Malta’s VISA requirement for third country nationals: https://www.identitymalta.com/unit/central-visa-unit/

1500 hours | 60 ECTS

Tier 1: Students must complete 60 ECTS from the following modules:

125 hours | 5 ECTS

User Interface Design: Part 2

125 hours | 5 ECTS

User Interface Design: Part 1

125 hours | 5 ECTS

UX Psychology

125 hours | 5 ECTS

Additional Studies in Software Testing

125 hours | 5 ECTS

System Design

125 hours | 5 ECTS

Introduction to Computer Programming: Part 2

125 hours | 5 ECTS

Applied Statistics

125 hours | 5 ECTS

Foundations of Cloud Computing

125 hours | 5 ECTS

Introduction to Deep Learning

125 hours | 5 ECTS

Introduction to Machine Learning

125 hours | 5 ECTS

Numerical Programming in Python

125 hours | 5 ECTS

Front End UI/UX Development

125 hours | 5 ECTS

Data Visualisation Tools

125 hours | 5 ECTS

Spreadsheets for Data Understanding

125 hours | 5 ECTS

Back End Development

125 hours | 5 ECTS

Front End Development

125 hours | 5 ECTS

DevOps

125 hours | 5 ECTS

JavaScript

125 hours | 5 ECTS

Practical Software Engineering

125 hours | 5 ECTS

Introduction to Problem-Solving Techniques: Part 1

125 hours | 5 ECTS

Relational Databases

125 hours | 5 ECTS

Introduction to Computer Programming: Part 1

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\ Intended learning outcomes

Knowledge
Knowledge acquired by the learner at the end of the course:
Knowledge acquired by the learner at the end of the course: - Students will have a cutting-edge knowledge and understanding of computer science allowing them to solve real-world engineering and specific computational problems using advanced techniques at the forefront of computer science. - Students will be able to analyse the societal, regulatory, and technological contexts for key computer science applications. - Students will be able to apply their technological abilities to produce innovative solutions to real-world problems and that implement techniques learned in the course. - Students will display original thinking on the basis of the knowledge they gain in the course.
Skills
Skills acquired by the learner at the end of the course:
Skills acquired by the learner at the end of the course; - Develop advanced, innovative, and multi-disciplinary problem-solving skills. Communicate computer science methods and tools clearly and unambiguously to specialised and non-specialised audiences. - Develop advanced abilities related to computer science operational procedures and implement them in response to changing environments - Critically evaluate alternative approaches to solving real world engineering and technological problems using cutting edge techniques in computer science on the basis of academic scholarship and case studies, demonstrating reflection on social and ethical responsibilities. - Formulate technological judgments and plans despite incomplete information by integrating knowledge and approaches from various computer science domains including machine learning, distributed computing, and cloud computing. - Enquire critically into the theoretical strategies for solving real-world problems using computational thinking and tools. - Develop new skills in response to emerging knowledge and techniques and demonstrate leadership skills and innovation in complex and unpredictable contexts.
Competencies
Competencies acquired by the learner at the end of the course:
Competencies acquired by the learner at the end of the course: - Formulate research-based solutions to practical problems in environments of incomplete information. - Manage decisions with autonomy in complex and unpredictable environments. - Organise projects and people in a way that is responsive to changes in the wider technological environment. - Demonstrate learning skills needed to maintain continued, self-directed study.

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