Master by Coursework

Overview:

The Master of Information Security is a 40 credits postgraduate programme by course work at the Faculty of Computer Science and Information Technology, Universiti Putra Malaysia (UPM). It offers an opportunity for advanced studies and career development in the field of information security.

Credits Requirement for Graduation

In order to graduate, students must have achieved at least 40 credits. The minimum cumulative average is 3.000. The minimum credits distribution for this programme is as follows:                               

Click here for information on list of courses.

Programme Educational Objectives (PEO)

Programme Educational Objectives (PEO) of the Master of Information Security are to:

1. produce highly knowledgeable professionals in the field of information security who are capable of applying the best methodologies and techniques to solve information security issues innovatively.
2. produce professionals with leadership skills who can communicate and interact effectively with various stakeholders.
3. produce professionals with a positive attitude, engaged in lifelong learning activities, and equipped with an entrepreneurial mindset to succeed in their careers.
4. produce professionals who uphold and defend ethical and professional practices in maintaining personal and professional integrity.

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Learning Outcomes (LO)

At the end of the programme, graduates should be able to:

1. Integrate advanced knowledge related to current research issues in information security;
2. Evaluate computing solutions and equipment in terms of usability, efficiency, and effectiveness;
3. Propose innovative solutions that are at the forefront of development in the field of information security;
4. Communicate and interact effectively within teams and with diverse audiences through the publication and presentation of technical materials in security;
5. Demonstrate leadership, teamwork, autonomy, and responsibility in delivering services related to information security;
6. Uphold professional and ethical practices in conducting research and delivering services related to information security;
7. Exhibit the ability to expand knowledge through lifelong learning with an entrepreneurial mindset related to information security;
8. Utilize digital and numerical skills to acquire, interpret, and expand knowledge in the field of information security.

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Overview:

The Master of Software Engineering programme is a 40 credits postgraduate programme by coursework. It offers an opportunity for advanced studies and career development in the field of software engineering. The objectives of this programme are to provide competent software engineers to fulfill the needs of the software industry; to offer the opportunity to further studies as well as career advancement in software engineering; and to produce professional software engineers who have the communication and ethical skills.

Credits Requirement for Graduation

In order to graduate, students must have achieved at least 40 credits. The minimum cumulative average is 3.000. The minimum credits distribution for this programme is as follows:                               

Click here for information on list of courses.

Programme Educational Objectives (PEO)

Programme Educational Objectives (PEO) of the Master of Software Engineering are to produce specialized software engineering experts who:

1. Possess advanced knowledge in the field of Software Engineering and the ability to apply the best methodologies and techniques to provide innovative solutions to current problems in Software Engineering;
2. Possess leadership skills and the ability to communicate and interact effectively with various stakeholders;
3. Demonstrate a positive attitude, engage in lifelong learning activities, and apply an entrepreneurial mindset for a successful career; and
4. Uphold and defend ethical and professional practices in maintaining personal and professional integrity.

Learning Outcomes (LO)

At the end of the programme, graduates should be able to:

1. Integrate advanced knowledge related to current research issues in the field of Software Engineering.

2. Propose innovative solutions that are at the forefront of development in Software Engineering.

3. Evaluate Software Engineering solutions and tools in terms of usability, efficiency, and effectiveness.

4. Communicate and interact effectively within teams and with diverse audiences through the publication and presentation of technical materials in the field of Software Engineering.

5. Utilize digital and numerical skills to acquire, interpret, and expand knowledge in the field of Software Engineering.

6. Demonstrate leadership, teamwork, autonomy, and responsibility in delivering services related to Software Engineering.

7. Exhibit the ability to expand knowledge through lifelong learning with an entrepreneurial mindset related to Software Engineering.

8. Uphold professional and ethical practices in conducting research and delivering services related to Software Engineering.

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Overview:

Credits Requirement for Graduation

In order to graduate, students must have achieved at least 40 credits. The minimum cumulative average is 3.000. The minimum credits distribution for this programme is as follows:                               

Click here for information on list of courses.

Programme Objectives (PO)

The objectives of the programme are to:

1. produce competent and highly knowledgeable professionals in the field of computer networking to meet the needs of the ICT industry and to act as catalysts for research in communication and networking technologies.

2. produce professionals who are creative and innovative in optimizing the use of network resources and skilled in solving problems ethically.
3. produce competitive professionals who meet the expectations of communication, leadership, and teamwork skills in the field of computer networking to support community development.
4. produce professionals with a positive attitude, engaged in lifelong learning activities, and possessing an entrepreneurial mindset to succeed in their careers.

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Learning Outcomes (LO)

At the end of the programme, graduates should be able to:

1. Integrate advanced knowledge related to current research issues in communication and networking technologies
2. Evaluate computer network solutions and equipment in terms of usability, efficiency, and effectiveness
3. Propose innovative solutions that are at the forefront of development in the field of computer networking
4. Communicate and interact effectively within groups and with diverse audiences through publications and presentations of computer networking technical materials
5. Demonstrate leadership, teamwork, autonomy, and responsibility in delivering services related to the field of computer networking
6. Uphold professional and ethical practices in conducting research and delivering services related to computer networking
7. Exhibit the ability to expand knowledge through lifelong learning by applying an entrepreneurial mindset related to computer networking
8. Utilize digital and numerical skills to acquire, interpret, and expand knowledge in communication and networking technologies

Overview:

The Master in Data Science is a 42-credit postgraduate programme by coursework offered by the Faculty of Computer Science and Information Technology, Universiti Putra Malaysia. It is designed to provide advanced knowledge and skills in the rapidly evolving field of data science. The programme aims to produce data science specialists with strong technical competencies in data analytics, machine learning, and big data technologies. The objectives of the programme are to supply skilled data science professionals to meet market demand, to support further academic pursuit and career progression and to produce ethical and effective communicators who are capable of lifelong learning and innovation in data-driven environments. 

Credits Requirement for Graduation

In order to graduate, students must have achieved at least 42 credits. The minimum cumulative average is 3.000. The minimum credits distribution for this programme is as follows:  

Click here for information on list of courses.

Programme Objectives (PO) 

The objectives of the programme are to:

1. To produce highly skilled and professional graduates with advanced knowledge and competencies in data science, analytics, and data-driven technologies. 
2. To support the national and global demand for data science experts capable of addressing complex data-related challenges across various sectors.
3. To enhance the career prospects and marketability of graduates by equipping them with relevant skills in big data analytics, machine learning, and data engineering.
4. To drive innovation and contribute to the development of data science as a catalyst for digital transformation and informed decision-making.
5. To provide lifelong learning opportunities and promote continuous professional development in line with emerging trends and technologies in data science.  
   
   

Learning Outcomes (LO)

At the end of the programme, graduates should be able to:

1. Integrate advanced knowledge related to current research issues in the field of Data Science.
2. Develop Data Science solutions and tools in terms of their usability, efficiency, and effectiveness.
3. Recommend innovative and forward-looking solutions for the advancement of the Data Science field.
4. Demonstrate effective communication within teams and with diverse audiences through the publication and presentation of technical materials in the field of Data Science.
5. Demonstrate effective interaction within teams and with diverse audiences through project discussions and participation in discourse related to the field of Data Science.
6. Demonstrate leadership, teamwork, autonomy, and responsibility in delivering services related to the field of Data Science.
7. Uphold professional and ethical practices in conducting research and delivering services related to the field of Data Science.
8. Demonstrate the ability to expand knowledge in Data Science through lifelong learning.
9. Demonstrate entrepreneurial thinking and capabilities within the field of Data Science.
10. Apply digital skills to acquire, interpret, and expand knowledge in Data Science.
11. Apply numeracy skills to acquire, interpret, and expand knowledge in Data Science.
12. Apply the principles of sustainable development in the design, development, and application of Data Science to support societal well-being and environmental sustainability. 

Overview:

The Master in Intelligent Systems programme aims to produce graduates with advanced knowledge and skills in Artificial Intelligence and Intelligent Systems. The programme equips students to develop intelligent and innovative solutions that address complex challenges and support digital transforma on across various industries. 

Credits Requirement for Graduation

In order to graduate, students must have achieved at least 40 credits with a minimum cumulative average is 3.000. The minimum credits distribution for this programme is as follows:

Click here for information on list of courses.

Programme Objectives (PO) 

The objectives of the programme are to:

1. To produce intelligent systems specialists who possess advanced knowledge, enhanced technical and numeracy skills, and expertise in a specialised domain of intelligent systems to provide innovative computing solutions.
2. To produce intelligent systems specialists who demonstrate leadership, interpersonal, and effective communication skills to engage and interact effectively with stakeholders.
3. To produce intelligent systems specialists who actively engage in and support lifelong learning activities and possess an entrepreneurial mindset.
4. To produce intelligent systems specialists who uphold and maintain ethical conduct, professional practices, and integrity in their professional endeavours. 

Learning Outcomes (LO)

At the end of the programme, graduates should be able to:

1. Integrate advanced knowledge related to current research issues in the field of intelligent systems.
2. Propose innovative solutions that are at the forefront of developments in the field of intelligent systems.
3. Develop intelligent systems solutions and tools in terms of their usability, efficiency, and effectiveness.
4. Interact effectively within teams and with diverse audiences through project discussions and participation in discourse related to the field of intelligent systems.
5. Communicate effectively within teams and with diverse audiences through the publication and presentation of technical materials related to the field of intelligent systems.
6. Utilise digital skills to acquire, interpret, and expand knowledge in the field of intelligent systems.
7. Apply numeracy skills to acquire, interpret, and expand knowledge in the field of intelligent systems.
8. Demonstrate leadership, teamwork, autonomy, and responsibility in delivering services related to intelligent systems.
9. Demonstrate the ability to expand relevant knowledge through lifelong learning.
10. Demonstrate an entrepreneurial mindset related to intelligent systems.