COMPUTATIONAL INTELLIGENCE FOR DATA ANALYTICS
CSE3CIX
2020
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.
School: Engineering and Mathematical Sciences (Pre 2022)
Credit points: 15
Subject Co-ordinator: Justin Wang
Available to Study Abroad/Exchange Students: No
Subject year level: Year Level 3 - UG
Available as Elective: No
Learning Activities: N/A
Capstone subject: No
Subject particulars
Subject rules
Prerequisites: CSE2DBX OR CSE2DCX
Students must be admitted in one of the following courses: SBAIO, SBACTO
Co-requisites: N/A
Incompatible subjects: N/A
Equivalent subjects: N/A
Quota Management Strategy: N/A
Quota-conditions or rules: N/A
Special conditions: N/A
Minimum credit point requirement: N/A
Assumed knowledge: N/A
Learning resources
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems.
Resource Type: Book
Resource Requirement: Recommended
Author: Lin, C.T., Lee, C.S.
Year: 1996
Edition/Volume: N/A
Publisher: Prentice-Hall
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Artificial intelligence-a guide to intelligent systems.
Resource Type: Book
Resource Requirement: Recommended
Author: Negnevitsky, M.
Year: 2002
Edition/Volume: N/A
Publisher: Addison-Wesley
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Computational Intelligence for Data Analytics
Resource Type: Book
Resource Requirement: Recommended
Author: Didasko
Year: 2018
Edition/Volume: N/A
Publisher: Didasko Digital
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Career Ready
Career-focused: No
Work-based learning: No
Self sourced or Uni sourced: N/A
Entire subject or partial subject: N/A
Total hours/days required: N/A
Location of WBL activity (region): N/A
WBL addtional requirements: N/A
Graduate capabilities & intended learning outcomes
Graduate Capabilities
Intended Learning Outcomes
Online (Didasko), 2020, Study block 1, Online
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Justin Wang
Class requirements
Unscheduled Online ClassWeek: 2 - 13
One 3.00 hours unscheduled online class per week on any day including weekend during the day from week 2 to week 13 and delivered via online.
Assessments
| Assessment element | Category | Contribution | Hurdle | % | 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. | N/A | N/A | No | 15 | SILO1 |
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 system | N/A | N/A | No | 30 | SILO2 |
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge | N/A | N/A | No | 25 | SILO2, SILO3 |
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. | N/A | N/A | No | 30 | SILO4 |
Online (Didasko), 2020, Study block 10, Online
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Justin Wang
Class requirements
Unscheduled Online ClassWeek: 41 - 52
One 3.00 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 element | Category | Contribution | Hurdle | % | 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. | N/A | N/A | No | 15 | SILO1 |
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 system | N/A | N/A | No | 30 | SILO2 |
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge | N/A | N/A | No | 25 | SILO2, SILO3 |
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. | N/A | N/A | No | 30 | SILO4 |
Online (Didasko), 2020, Study block 11, Online
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Justin Wang
Class requirements
Unscheduled Online ClassWeek: 45 - 0
One 3.00 hours unscheduled online class per week on any day including weekend during the day from week 45 to week 0 and delivered via online.
Assessments
| Assessment element | Category | Contribution | Hurdle | % | 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. | N/A | N/A | No | 15 | SILO1 |
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 system | N/A | N/A | No | 30 | SILO2 |
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge | N/A | N/A | No | 25 | SILO2, SILO3 |
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. | N/A | N/A | No | 30 | SILO4 |
Online (Didasko), 2020, Study block 12, Online
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Justin Wang
Class requirements
Unscheduled Online ClassWeek: 49 - 0
One 3.00 hours unscheduled online class per week on any day including weekend during the day from week 49 to week 0 and delivered via online.
Assessments
| Assessment element | Category | Contribution | Hurdle | % | 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. | N/A | N/A | No | 15 | SILO1 |
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 system | N/A | N/A | No | 30 | SILO2 |
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge | N/A | N/A | No | 25 | SILO2, SILO3 |
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. | N/A | N/A | No | 30 | SILO4 |
Online (Didasko), 2020, Study block 2, Online
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Justin Wang
Class requirements
Unscheduled Online ClassWeek: 6 - 17
One 3.00 hours unscheduled online class per week on any day including weekend during the day from week 6 to week 17 and delivered via online.
Assessments
| Assessment element | Category | Contribution | Hurdle | % | 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. | N/A | N/A | No | 15 | SILO1 |
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 system | N/A | N/A | No | 30 | SILO2 |
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge | N/A | N/A | No | 25 | SILO2, SILO3 |
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. | N/A | N/A | No | 30 | SILO4 |
Online (Didasko), 2020, Study block 3, Online
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Justin Wang
Class requirements
Unscheduled Online ClassWeek: 10 - 21
One 3.00 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 element | Category | Contribution | Hurdle | % | 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. | N/A | N/A | No | 15 | SILO1 |
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 system | N/A | N/A | No | 30 | SILO2 |
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge | N/A | N/A | No | 25 | SILO2, SILO3 |
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. | N/A | N/A | No | 30 | SILO4 |
Online (Didasko), 2020, Study block 4, Online
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Justin Wang
Class requirements
Unscheduled Online ClassWeek: 14 - 25
One 3.00 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 element | Category | Contribution | Hurdle | % | 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. | N/A | N/A | No | 15 | SILO1 |
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 system | N/A | N/A | No | 30 | SILO2 |
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge | N/A | N/A | No | 25 | SILO2, SILO3 |
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. | N/A | N/A | No | 30 | SILO4 |
Online (Didasko), 2020, Study block 5, Online
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Justin Wang
Class requirements
Unscheduled Online ClassWeek: 19 - 30
One 3.00 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 element | Category | Contribution | Hurdle | % | 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. | N/A | N/A | No | 15 | SILO1 |
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 system | N/A | N/A | No | 30 | SILO2 |
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge | N/A | N/A | No | 25 | SILO2, SILO3 |
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. | N/A | N/A | No | 30 | SILO4 |
Online (Didasko), 2020, Study block 6, Online
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Justin Wang
Class requirements
Unscheduled Online ClassWeek: 23 - 34
One 3.00 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 element | Category | Contribution | Hurdle | % | 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. | N/A | N/A | No | 15 | SILO1 |
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 system | N/A | N/A | No | 30 | SILO2 |
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge | N/A | N/A | No | 25 | SILO2, SILO3 |
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. | N/A | N/A | No | 30 | SILO4 |
Online (Didasko), 2020, Study block 7, Online
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Justin Wang
Class requirements
Unscheduled Online ClassWeek: 27 - 38
One 3.00 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 element | Category | Contribution | Hurdle | % | 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. | N/A | N/A | No | 15 | SILO1 |
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 system | N/A | N/A | No | 30 | SILO2 |
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge | N/A | N/A | No | 25 | SILO2, SILO3 |
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. | N/A | N/A | No | 30 | SILO4 |
Online (Didasko), 2020, Study block 8, Online
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Justin Wang
Class requirements
Unscheduled Online ClassWeek: 32 - 43
One 3.00 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 element | Category | Contribution | Hurdle | % | 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. | N/A | N/A | No | 15 | SILO1 |
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 system | N/A | N/A | No | 30 | SILO2 |
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge | N/A | N/A | No | 25 | SILO2, SILO3 |
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. | N/A | N/A | No | 30 | SILO4 |
Online (Didasko), 2020, Study block 9, Online
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Justin Wang
Class requirements
Unscheduled Online ClassWeek: 36 - 47
One 3.00 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 element | Category | Contribution | Hurdle | % | 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. | N/A | N/A | No | 15 | SILO1 |
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 system | N/A | N/A | No | 30 | SILO2 |
Online test (60 minutes) (equivalent to 1000 words)Multiple-choice and/or short answer questions test that covers the theoretical knowledge | N/A | N/A | No | 25 | SILO2, SILO3 |
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. | N/A | N/A | No | 30 | SILO4 |