BIP Proforma 20222023

BIT34303 Machine Learning
Prerequisite Course(s): None

Synopsis
An introduction to machine learning theories and algorithms. Topics include supervised Learning
(artificial neural networks, support vector machines) and unsupervised learning (clustering,
dimensionality reduction).

References

1. Lee Meng Wei. (2019). Python Machine Learning. Wiley.
2. Mohri Mehryar, Afshin Rostamizadeh, and Ameet Talwalkar. (2018). Foundations of Machine

Learning. The MIT Press
3. Andreas C. Müller & Sarah Guido. (2016) Introduction to Machine Learning with Python: A Guide

for Data Scientists. O'Reilly Media
4. Shalev-Shwartz S., Ben-David S. (2014). Understanding Machine Learning: From Theory to

Algorithms. Cambridge University Press.
5. Christopher M. Bishop. (2011). Pattern Recognition and Machine Learning. Springer

BIT30303 Decision Support System
Prerequisite Course(s): None

Synopsis
This course introduces topics such as Data and Model Management, Decision Making, Decision Making
Process, Decision Making Modelling, Decision Support System Design and Development, User
Interface Component, Decision Support System Integration and Implementation, Group Decision
Support System

References

1. Ramesh Sharda, Dursun Delen & Efraim Turban (2019) Analytics, Data Science, & Artificial
Intelligence: Systems for Decision Support (11th Edition). Pearson

2. S. Christian Albright (2015) VBA for Modelers: Developing Decision Support Systems with
Microsoft Office Excel 5th Edition. Cengage Learning

3. Efraim, T., Aronson, J. E. Liang T. & McCarthy R.V. (2011). Decision support and
businessintelligence systems. 9th ed. New York: Prentice Hall. Call Number: HD30.2 .D42 2007

4. Chiang S.J., (2011). Efficient Decision Support System : Practice and Challenges in
Multidisciplinary Domains. Rijeka:INTECH OPEN ACCESS

5. Efraim.T., et.al. (2014). A Business Intelligence and Analytics: Systems for Decision Support.
New York : Pearson.

6. Chiu, C. M., Liang, T. P., & Turban, E. (2014). What can crowdsourcing do for decision support?.
Decision Support Systems, 65, 40-49.

BIT33603 Data Mining
Prerequisite Course(s): None

Synopsis
This course provides detail explanation on data mining and machine learning, which include:
classification, clustering, association rules and so on. Emphasis will be laid on performance and
implementation issues, as well as on application such as web mining.

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References

1. Galit Shmueli, Peter C. Bruce, Peter Gedeck & Nitin R. Patel (2019). Data Mining for Business
Analytics: Concepts, Techniques and Applications in Python. Wiley

2. Witten, I. H., Frank, E., Hall, M. A., & Pal, C. J. (2016). Data Mining: Practical machine learning
tools and techniques. Morgan Kaufmann.

3. Larose, D.T. & Larose, C.D. (2015). Data mining and predictive analytics. Hoboken, NJ: John
Wiley. Call Number: QA76.9.D343 .L375 2015.

4. Han, J., Kamber, M., & Pei, J. (2012). Data mining: concepts and techniques. Burlington, MA:
Elsevier. Call Number: QA76.9.D343 .H36 2012.

5. Gupta, G.K. (2011). Introduction to data mining with case studies. New Delhi: Prentice-Hall. Call
Number: QA76.9.D343 .G86 2011.

6. Kudyba, S. (2014). Big data, mining, and analytics: components of strategic decision making.
CRC Press.

BIT20903 Artificial Intelligent
Prerequisite Course(s): None

Synopsis

This course introduces topics such as searching and problem solving, knowledge representation, logic,
knowledge engineering, machine learning, and artificial intelligence future.

References

1. Russel, S., and Norvig, P., (2020). Artificial Intelligence: A Modern Approach. 4th Edition. Pearson
Education. [ISBN-13: 978-0134610993, ISBN-10: 0134610997].

2. Mitchell, M. (2019). Artificial Intelligence: A Guide for Thinking Humans. Farrar, Straus and Giroux
Publications. [ISBN-10:0374257833, ISBN-13: 978-0374257835]

3. Stone, J. V., (2019). Artificial Intelligence Engines. Sebtel Press. [ISBN-13: 978-0956372819,
ISBN-10: 0956372813].

4. Mehrotra, D., (2019). Basics of Artificial Intelligence & Machine Learning. Notion Press. [ISBN-
10: 1645872823, ISBN-13: 978-1645872825].

5. Wilkins, N., (2019). Artificial Intelligence. Bravex Publications. [ISBN-10: 1950922510, ISBN-13:
978-1950922512].

6. Rothman, D., (2018). Artificial Intelligence by Example. Packt Publishing. [ISBN-10: 1788990544,
ISBN-13: 978-1788990547].

7. Li, D., & Du, Y. (2017). Artificial intelligence with uncertainty. CRC press.

UQU40103 Professional at Works
Prerequisite Course(s): None

Synopsis

The Professional at Work course is designed to improve the ability of students to develop their technical
skills in professionalism, social responsibility, and environmental sustainability. Nurturing and
empowering the student with these skills could enhance the student's professionalism prior to entering
the workspace. The philosophy of the course is ongoing, systematic, and aimed toward a fulfilling work
life, which is part of their overall plan for personal development. This course includes an introduction to
professional practice, ethics, legal, innovation and infrastructure, social responsibility, and professional
environment. Also, this course was developed by referring to Sustainable Development Goals (SDG)
and Politic, Economy, Social, Technology, Environment, and Legal (PESTEL) guidelines. Particularly,
students will propose a suitable community service project that deals with local/community issues that
lead to professional practices.

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References

1. Lydia E. Anderson & Sandra B. Bolt (2016). Professionalism : skills for workplace success.
Pearson, c2013 ISBN 9780132624664

2. Department of Economic and Social Affairs, United Nation (2019). Handbook for th preparation of
valuntary national reviews

3. Purohit, S. S. (2008). Green technology : an approach for sustainable environment. ISBN:
9788177543438, [S494.5.S86 .P87 2008]

4. Russ, Tom (2010). Sustainability and design ethics. ISBN: 9781439808542 [TA157 .R87 2010]
5. Yoe, Charles (2012). Principles of risk analysis : decision making under uncertainty. ISBN:

9781439857496 [T57.95 .Y63 2012]

Synopsis of Free Modules

BIC 21102 Professional Ethics and Occupational Safety
Prerequisite Course(s): None

Synopsis
This course discusses topics related to professional ethics in computing. Topics include introduction to
professional ethics in computing, professional ethics and responsibilities, personality in computing
ethics, security and control, copyright and intellectual property, freedom of speech, politeness, filtering
and pornography, and cyber laws in Malaysia.

References
1. Reynolds, G., (2013). Ethics in information technology 5th ed. Boston, MA: Course Technology. Call

Number: HC79.I55.R49 2015
2. Quinn, M. J., (2010). Ethics for the information age. 4th ed. Boston: Addison Wesley. Call Number:

QA76.9.M65 .Q74 2011
3. Baase, S., (2008). A gift of fire: social, legal and ethical issues for computer and the Internet. 3rd

ed. Upper Saddle River, NJ: Prentice Hall.
4. MacKinnon, B., (2015). Ethics: theory and contemporary issues 8th ed. California: Wadsworth

Publishing. Call Number: BJ1012.M324 2015.
5. Furaker, B., (2012). Commitment to work and job satisfaction: studies of work orientations. Call

Number: HD4905.C65 2012.
6. Occupational Safety and Health Act and Regulations. MDC Publishers Printer Sdn. Bhd. (2001).

Call number: KPG1390.M34 2001 rw N2.
7. Factories and Machinery Act & Regulations. MDC Publishers Printer Sdn. Bhd. (2001). Call

number: KPG1390.A31967 .A4 2001 rw N1.

BIE 30503 Software Project Management
Prerequisite Course (s):Taken BIE10103 Software Engineering Principles

Synopsis
This course exposes students’ within overview on the concept of software project management. Topics
to be discussed include introduction to project management, project planning, project time management
and cost, management of project human resources, communication, risk and purchasing.

References
1. Fairley, R. E. (2011) Managing and leading software projects. NJ: John Wiley
2. Schwalbe, K.. (2014) Information technology project management. 7th. Ed. Boston; Thomson. Call

Number: HD30.2 .S38 2014
3. Soriano, J. L. 2012. Maximizing benefits from IT project management: from requirements to value

delivery.Boca Raton, FL; CRC Press. Shelf Number: HD30.2 .S67 2012

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4. Kerzner, H. 2009. Project management: a system approach to planning, scheduling and controlling.
10th Ed. New Jersey: John Wiley & Sons, Inc. Shelf Number: HD69.P75 .K47 2009

5. Ahmed, A. (2016) Software project management : A Process-Driven Approach. CRC Press, Tylor
& Francis Group

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Career and Further Education Prospect

Graduate from this programme may pursue a wide range of careers such as Software Engineer,
Information System Engineer, Information System Officer, System Designer, System Developer, IT
Project Manager, Programmer, Software Tester, Academician, Software Architect, System Analyst and
Test Engineer.
In general, graduate from this programme will be involved in the following activities:
• Investigating current applications.
• Liaising with users and providing guidance and training.
• Producing specifications.
• Costing new or modified systems.
• Agreeing proposals.
• Writing new software and operating manuals.
• Solving software-writing problems and maintenance issues.
• Testing the product to ensure that it operates satisfactorily.
• Handling support and feedback.

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Source: Malaysian Qualification Framework

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Centre for Academic Development and Training
Universiti Tun Hussein Onn Malaysia
86400 Batu Pahat, Johor Darul Ta’zim
www.uthm.edu.my

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