cse3cix computational intelligence for data analytics
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.
SchoolEngineering and Mathematical Sciences
Credit points15
Subject Co-ordinatorJustin Wang
Available to Study Abroad/Exchange StudentsNo
Subject year levelYear Level 3 - UG
Available as ElectiveNo
Learning ActivitiesN/A
Capstone subjectNo
Subject particulars
Subject rules
PrerequisitesCSE2DBX OR CSE2DCX
Students must be admitted in one of the following courses: SBAIO, SBACTO
Co-requisitesN/A
Incompatible subjectsN/A
Equivalent subjectsN/A
Quota Management StrategyN/A
Quota-conditions or rulesN/A
Special conditionsN/A
Minimum credit point requirementN/A
Assumed knowledgeN/A
Learning resources
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems.
Resource TypeBook
Resource RequirementRecommended
AuthorLin, C.T., Lee, C.S.
Year1996
Edition/VolumeN/A
PublisherPrentice-Hall
ISBNN/A
Chapter/article titleN/A
Chapter/issueN/A
URLN/A
Other descriptionN/A
Source locationN/A
Artificial intelligence-a guide to intelligent systems.
Resource TypeBook
Resource RequirementRecommended
AuthorNegnevitsky, M.
Year2002
Edition/VolumeN/A
PublisherAddison-Wesley
ISBNN/A
Chapter/article titleN/A
Chapter/issueN/A
URLN/A
Other descriptionN/A
Source locationN/A
Computational Intelligence for Data Analytics
Resource TypeBook
Resource RequirementRecommended
AuthorDidasko
Year2018
Edition/VolumeN/A
PublisherDidasko Digital
ISBNN/A
Chapter/article titleN/A
Chapter/issueN/A
URLN/A
Other descriptionN/A
Source locationN/A
Career Ready
Career-focusedNo
Work-based learningNo
Self sourced or Uni sourcedN/A
Entire subject or partial subjectN/A
Total hours/days requiredN/A
Location of WBL activity (region)N/A
WBL addtional requirementsN/A
Graduate capabilities & intended learning outcomes
Graduate Capabilities
Intended Learning Outcomes
Subject options
Select to view your study options…
Online (Didasko), 2020, Study block 1, Online
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorJustin 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 enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorJustin 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 enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorJustin 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 enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorJustin 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 enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorJustin 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 enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorJustin 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 enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorJustin 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 enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorJustin 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 enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorJustin 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 enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorJustin 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 enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorJustin 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 enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorJustin 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 |