COMPUTATIONAL INTELLIGENCE FOR DATA ANALYTICS

CSE3CIX

2019

Credit points: 15

Subject outline

Quantitative analysis plays an important role in business analytics and knowledge engineering, thus it is very useful to develop computing skills for data regression and classification. This subject covers some fundamentals of computational intelligence techniques, including fuzzy inference systems, neural networks and hybrid neuro-fuzzy systems. The subject is designed with a focus on solving time-series forecasting problems using fuzzy inference systems, where fuzzy inference mechanisms and fuzzy rule extraction from numerical data are addressed. Some advanced learning techniques for training neural networks will also be highlighted. In labs and assignments students will work with business datasets for time-series prediction using a fuzzy system, which helps to consolidate the knowledge taught in the lectures and gain a hand-on experience on computational intelligence applications in business.

SchoolSchool Engineering&Mathematical Sciences

Credit points15

Subject Co-ordinatorRabei Alhadad

Available to Study Abroad StudentsNo

Subject year levelYear Level 3 - UG

Exchange StudentsNo

Subject particulars

Subject rules

Prerequisites Must be admitted in SBAIO or SBACTO and have passed CSE2DBX or CSE2DCX

Co-requisitesN/A

Incompatible subjectsN/A

Equivalent subjectsN/A

Special conditionsN/A

Readings

Resource TypeTitleResource RequirementAuthor and YearPublisher
ReadingsArtificial intelligence-a guide to intelligent systems.RecommendedNegnevitsky, M., 2002Addison-Wesley
ReadingsNeural fuzzy systems: a neuro-fuzzy synergism to intelligent systems.RecommendedLin, C.T., Lee, C.S., 1996Prentice-Hall
ReadingsComputational Intelligence for Data AnalyticsRecommendedDidasko, 2018Didasko Digital

Graduate capabilities & intended learning outcomes

01. Critically evaluate the technologies and applications of computational intelligence systems (CIS) relating to business analytics and knowledge engineering.

Activities:
Online chapters from the textbook. Online modules and webinars on the introduction of computational intelligence systems and its applications Self- checking open-ended questions to support the activities.

02. Develop different computational intelligence systems, such as forecasting and classification systems using techniques which replicate human decision-making.

Activities:
Online chapters from the textbook. Online modules and webinars with open discussion forums on fuzzy logic, neural networks and hybrid intelligent systems. Knowledge assessed via online quizzes and self-paced online problems.

03. Compare and contrast computational intelligence techniques and knowledge engineering using different business applications.

Activities:
Online chapters from the textbook. Online modules and webinars with discussion forums on computational intelligence techniques and knowledge engineering. Knowledge assessed via online quizzes and self-paced online problems.

04. Implement a decision support system for time-series forecasting to set business goals and objectives.

Activities:
Online practical activity using relevant tools to implement a fuzzy logic based decision support system for resolving a time-series forecasting problem.

Subject options

Select to view your study options…

Start date between: and    Key dates

Online (Didasko), 2019, Study Block 1, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorJustin Wang

Class requirements

Unscheduled Online Class Week: 02 - 13
One 3.0 hours unscheduled online class per week on any day including weekend during the day from week 02 to week 13 and delivered via online.

Assessments

Assessment elementComments% ILO*
Online test (30 minutes) (equivalent to 500 words)Multiple-choice and/or short answer questions on computational intelligence systems. Test will be conducted in week 5.15 01
Assignment on computational intelligence system (equivalent to 1500 words)A practical scenario-based report on developing a computational intelligence system using fuzzy inference systems or neural networks or hybrid intelligent system30 02
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge25 02, 03
Assignment on time-series forecasting (equivalent to 1500 words)A practical scenario-based report on using a tool to implement a fuzzy expert system for resolving a time-series forecasting problem.30 04

Online (Didasko), 2019, Study Block 2, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorJustin Wang

Class requirements

Unscheduled Online Class Week: 06 - 17
One 3.0 hours unscheduled online class per week on any day including weekend during the day from week 06 to week 17 and delivered via online.

Assessments

Assessment elementComments% ILO*
Online test (30 minutes) (equivalent to 500 words)Multiple-choice and/or short answer questions on computational intelligence systems. Test will be conducted in week 5.15 01
Assignment on computational intelligence system (equivalent to 1500 words)A practical scenario-based report on developing a computational intelligence system using fuzzy inference systems or neural networks or hybrid intelligent system30 02
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge25 02, 03
Assignment on time-series forecasting (equivalent to 1500 words)A practical scenario-based report on using a tool to implement a fuzzy expert system for resolving a time-series forecasting problem.30 04

Online (Didasko), 2019, Study Block 3, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorJustin Wang

Class requirements

Unscheduled Online Class Week: 10 - 21
One 3.0 hours unscheduled online class per week on any day including weekend during the day from week 10 to week 21 and delivered via online.

Assessments

Assessment elementComments% ILO*
Online test (30 minutes) (equivalent to 500 words)Multiple-choice and/or short answer questions on computational intelligence systems. Test will be conducted in week 5.15 01
Assignment on computational intelligence system (equivalent to 1500 words)A practical scenario-based report on developing a computational intelligence system using fuzzy inference systems or neural networks or hybrid intelligent system30 02
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge25 02, 03
Assignment on time-series forecasting (equivalent to 1500 words)A practical scenario-based report on using a tool to implement a fuzzy expert system for resolving a time-series forecasting problem.30 04

Online (Didasko), 2019, Study Block 4, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 14 - 25
One 3.0 hours unscheduled online class per week on any day including weekend during the day from week 14 to week 25 and delivered via online.

Assessments

Assessment elementComments% ILO*
Online test (30 minutes) (equivalent to 500 words)Multiple-choice and/or short answer questions on computational intelligence systems. Test will be conducted in week 5.15 01
Assignment on computational intelligence system (equivalent to 1500 words)A practical scenario-based report on developing a computational intelligence system using fuzzy inference systems or neural networks or hybrid intelligent system30 02
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge25 02, 03
Assignment on time-series forecasting (equivalent to 1500 words)A practical scenario-based report on using a tool to implement a fuzzy expert system for resolving a time-series forecasting problem.30 04

Online (Didasko), 2019, Study Block 5, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 19 - 30
One 3.0 hours unscheduled online class per week on any day including weekend during the day from week 19 to week 30 and delivered via online.

Assessments

Assessment elementComments% ILO*
Online test (30 minutes) (equivalent to 500 words)Multiple-choice and/or short answer questions on computational intelligence systems. Test will be conducted in week 5.15 01
Assignment on computational intelligence system (equivalent to 1500 words)A practical scenario-based report on developing a computational intelligence system using fuzzy inference systems or neural networks or hybrid intelligent system30 02
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge25 02, 03
Assignment on time-series forecasting (equivalent to 1500 words)A practical scenario-based report on using a tool to implement a fuzzy expert system for resolving a time-series forecasting problem.30 04

Online (Didasko), 2019, Study Block 6, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 23 - 34
One 3.0 hours unscheduled online class per week on any day including weekend during the day from week 23 to week 34 and delivered via online.

Assessments

Assessment elementComments% ILO*
Online test (30 minutes) (equivalent to 500 words)Multiple-choice and/or short answer questions on computational intelligence systems. Test will be conducted in week 5.15 01
Assignment on computational intelligence system (equivalent to 1500 words)A practical scenario-based report on developing a computational intelligence system using fuzzy inference systems or neural networks or hybrid intelligent system30 02
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge25 02, 03
Assignment on time-series forecasting (equivalent to 1500 words)A practical scenario-based report on using a tool to implement a fuzzy expert system for resolving a time-series forecasting problem.30 04

Online (Didasko), 2019, Study Block 7, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 27 - 38
One 3.0 hours unscheduled online class per week on any day including weekend during the day from week 27 to week 38 and delivered via online.

Assessments

Assessment elementComments% ILO*
Online test (30 minutes) (equivalent to 500 words)Multiple-choice and/or short answer questions on computational intelligence systems. Test will be conducted in week 5.15 01
Assignment on computational intelligence system (equivalent to 1500 words)A practical scenario-based report on developing a computational intelligence system using fuzzy inference systems or neural networks or hybrid intelligent system30 02
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge25 02, 03
Assignment on time-series forecasting (equivalent to 1500 words)A practical scenario-based report on using a tool to implement a fuzzy expert system for resolving a time-series forecasting problem.30 04

Online (Didasko), 2019, Study Block 8, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 32 - 43
One 3.0 hours unscheduled online class per week on any day including weekend during the day from week 32 to week 43 and delivered via online.

Assessments

Assessment elementComments% ILO*
Online test (30 minutes) (equivalent to 500 words)Multiple-choice and/or short answer questions on computational intelligence systems. Test will be conducted in week 5.15 01
Assignment on computational intelligence system (equivalent to 1500 words)A practical scenario-based report on developing a computational intelligence system using fuzzy inference systems or neural networks or hybrid intelligent system30 02
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge25 02, 03
Assignment on time-series forecasting (equivalent to 1500 words)A practical scenario-based report on using a tool to implement a fuzzy expert system for resolving a time-series forecasting problem.30 04

Online (Didasko), 2019, Study Block 9, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 36 - 47
One 3.0 hours unscheduled online class per week on any day including weekend during the day from week 36 to week 47 and delivered via online.

Assessments

Assessment elementComments% ILO*
Online test (30 minutes) (equivalent to 500 words)Multiple-choice and/or short answer questions on computational intelligence systems. Test will be conducted in week 5.15 01
Assignment on computational intelligence system (equivalent to 1500 words)A practical scenario-based report on developing a computational intelligence system using fuzzy inference systems or neural networks or hybrid intelligent system30 02
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge25 02, 03
Assignment on time-series forecasting (equivalent to 1500 words)A practical scenario-based report on using a tool to implement a fuzzy expert system for resolving a time-series forecasting problem.30 04

Online (Didasko), 2019, Study Block 10, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 41 - 52
One 3.0 hours unscheduled online class per week on any day including weekend during the day from week 41 to week 52 and delivered via online.

Assessments

Assessment elementComments% ILO*
Online test (30 minutes) (equivalent to 500 words)Multiple-choice and/or short answer questions on computational intelligence systems. Test will be conducted in week 5.15 01
Assignment on computational intelligence system (equivalent to 1500 words)A practical scenario-based report on developing a computational intelligence system using fuzzy inference systems or neural networks or hybrid intelligent system30 02
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge25 02, 03
Assignment on time-series forecasting (equivalent to 1500 words)A practical scenario-based report on using a tool to implement a fuzzy expert system for resolving a time-series forecasting problem.30 04

Online (Didasko), 2019, Study Block 11, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 45
One 3.0 hours unscheduled online class per week on any day including weekend during the day in week 45 and delivered via online.

Assessments

Assessment elementComments% ILO*
Online test (30 minutes) (equivalent to 500 words)Multiple-choice and/or short answer questions on computational intelligence systems. Test will be conducted in week 5.15 01
Assignment on computational intelligence system (equivalent to 1500 words)A practical scenario-based report on developing a computational intelligence system using fuzzy inference systems or neural networks or hybrid intelligent system30 02
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge25 02, 03
Assignment on time-series forecasting (equivalent to 1500 words)A practical scenario-based report on using a tool to implement a fuzzy expert system for resolving a time-series forecasting problem.30 04

Online (Didasko), 2019, Study Block 12, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 49
One 3.0 hours unscheduled online class per week on any day including weekend during the day in week 49 and delivered via online.

Assessments

Assessment elementComments% ILO*
Online test (30 minutes) (equivalent to 500 words)Multiple-choice and/or short answer questions on computational intelligence systems. Test will be conducted in week 5.15 01
Assignment on computational intelligence system (equivalent to 1500 words)A practical scenario-based report on developing a computational intelligence system using fuzzy inference systems or neural networks or hybrid intelligent system30 02
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge25 02, 03
Assignment on time-series forecasting (equivalent to 1500 words)A practical scenario-based report on using a tool to implement a fuzzy expert system for resolving a time-series forecasting problem.30 04