MACHINE LEARNING

CSE2MLX

2020

Credit points: 15

Subject outline

This subject introduces students to the fundamentals of machine learning (history, algorithm types, uses) and then covers an efficient implementation of machine learning algorithms on real-world data of moderate complexity using an open source ecosystem and MapReduce and R environments. Students explore the practical aspects of this subject using the AWS platform.

SchoolEngineering and Mathematical Sciences

Credit points15

Subject Co-ordinatorRabei Alhadad

Available to Study Abroad/Exchange StudentsNo

Subject year levelYear Level 2 - UG

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectNo

Subject particulars

Subject rules

PrerequisitesCSE1IOX AND CSE1CFX
Students must be admitted in the following course: 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

Readings

Machine Learning: Hands-On for Developers and Technical Professionals

Resource TypePrescribed

Resource RequirementN/A

AuthorBell J.

Year2015

Edition/VolumeN/A

PublisherWiley

ISBNN/A

Chapter/article titleN/A

Chapter/issueN/A

URLN/A

Other descriptionN/A

Source locationN/A

Amazon Web Services online training

Resource TypeRecommended

Resource RequirementN/A

AuthorAmazon Web Services Educate

YearN/A

Edition/VolumeN/A

PublisherAmazon Web Services

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

COMMUNICATION - Communicating and Influencing
INQUIRY AND ANALYSIS - Creativity and Innovation
INQUIRY AND ANALYSIS - Critical Thinking and Problem Solving
INQUIRY AND ANALYSIS - Research and Evidence-Based Inquiry
PERSONAL AND PROFESSIONAL - Adaptability and Self-Management

Intended Learning Outcomes

01. Appraise machine learning as it can be applied to real-world problems in the cloud environment
02. Analyse the strengths and weaknesses of a wide variety of machine learning algorithms
03. Apply machine learning algorithms to solve real-world problems of moderate complexity
04. Compare the various tools that are available for data collection and processing
05. Integrate machine learning libraries, and mathematical and statistical tools with modern technologies like Hadoop distributed file system and MapReduce programming model
06. Employ R programming language to perform efficient implementation of machine learning algorithms on real data

Subject options

Select to view your study options…

Start date between: and    Key dates

Online (Didasko), 2020, Study block 1, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 2 - 13
One 3.00 h 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 elementCommentsCategoryContributionHurdle% ILO*

Online test (250-words equiv.)Multiple-choice and/or short answer questions test on fundamentals of machine learning in cloud environmentTimed assessment

N/AN/AN/ANo10 SILO1

Written assignment on machine learning algorithm (1350-words equiv.)An assignment focused on identifying and applying the most appropriate learning algorithm to solve a real-world problem

N/AN/AN/ANo30 SILO2, SILO3

Written assignment on other machine learning features (1600-words equiv.)A written practical scenario-based lab report on other machine learning features such as batch processing, R and Spring XD

N/AN/AN/ANo35 SILO4, SILO5, SILO6

Online subject test (1000-words equiv.)Multiple-choice and/or short answer questions test that covers all the topicsTimed assessment

N/AN/AN/ANo25 SILO4, SILO5

Online (Didasko), 2020, Study block 10, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 41 - 52
One 3.00 h 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 elementCommentsCategoryContributionHurdle% ILO*

Online test (250-words equiv.)Multiple-choice and/or short answer questions test on fundamentals of machine learning in cloud environmentTimed assessment

N/AN/AN/ANo10 SILO1

Written assignment on machine learning algorithm (1350-words equiv.)An assignment focused on identifying and applying the most appropriate learning algorithm to solve a real-world problem

N/AN/AN/ANo30 SILO2, SILO3

Written assignment on other machine learning features (1600-words equiv.)A written practical scenario-based lab report on other machine learning features such as batch processing, R and Spring XD

N/AN/AN/ANo35 SILO4, SILO5, SILO6

Online subject test (1000-words equiv.)Multiple-choice and/or short answer questions test that covers all the topicsTimed assessment

N/AN/AN/ANo25 SILO4, SILO5

Online (Didasko), 2020, Study block 11, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 45 - 0
One 3.00 h 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 elementCommentsCategoryContributionHurdle% ILO*

Online test (250-words equiv.)Multiple-choice and/or short answer questions test on fundamentals of machine learning in cloud environmentTimed assessment

N/AN/AN/ANo10 SILO1

Written assignment on machine learning algorithm (1350-words equiv.)An assignment focused on identifying and applying the most appropriate learning algorithm to solve a real-world problem

N/AN/AN/ANo30 SILO2, SILO3

Written assignment on other machine learning features (1600-words equiv.)A written practical scenario-based lab report on other machine learning features such as batch processing, R and Spring XD

N/AN/AN/ANo35 SILO4, SILO5, SILO6

Online subject test (1000-words equiv.)Multiple-choice and/or short answer questions test that covers all the topicsTimed assessment

N/AN/AN/ANo25 SILO4, SILO5

Online (Didasko), 2020, Study block 12, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 49 - 0
One 3.00 h 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 elementCommentsCategoryContributionHurdle% ILO*

Online test (250-words equiv.)Multiple-choice and/or short answer questions test on fundamentals of machine learning in cloud environmentTimed assessment

N/AN/AN/ANo10 SILO1

Written assignment on machine learning algorithm (1350-words equiv.)An assignment focused on identifying and applying the most appropriate learning algorithm to solve a real-world problem

N/AN/AN/ANo30 SILO2, SILO3

Written assignment on other machine learning features (1600-words equiv.)A written practical scenario-based lab report on other machine learning features such as batch processing, R and Spring XD

N/AN/AN/ANo35 SILO4, SILO5, SILO6

Online subject test (1000-words equiv.)Multiple-choice and/or short answer questions test that covers all the topicsTimed assessment

N/AN/AN/ANo25 SILO4, SILO5

Online (Didasko), 2020, Study block 2, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 6 - 17
One 3.00 h 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 elementCommentsCategoryContributionHurdle% ILO*

Online test (250-words equiv.)Multiple-choice and/or short answer questions test on fundamentals of machine learning in cloud environmentTimed assessment

N/AN/AN/ANo10 SILO1

Written assignment on machine learning algorithm (1350-words equiv.)An assignment focused on identifying and applying the most appropriate learning algorithm to solve a real-world problem

N/AN/AN/ANo30 SILO2, SILO3

Written assignment on other machine learning features (1600-words equiv.)A written practical scenario-based lab report on other machine learning features such as batch processing, R and Spring XD

N/AN/AN/ANo35 SILO4, SILO5, SILO6

Online subject test (1000-words equiv.)Multiple-choice and/or short answer questions test that covers all the topicsTimed assessment

N/AN/AN/ANo25 SILO4, SILO5

Online (Didasko), 2020, Study block 3, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 10 - 21
One 3.00 h 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 elementCommentsCategoryContributionHurdle% ILO*

Online test (250-words equiv.)Multiple-choice and/or short answer questions test on fundamentals of machine learning in cloud environmentTimed assessment

N/AN/AN/ANo10 SILO1

Written assignment on machine learning algorithm (1350-words equiv.)An assignment focused on identifying and applying the most appropriate learning algorithm to solve a real-world problem

N/AN/AN/ANo30 SILO2, SILO3

Written assignment on other machine learning features (1600-words equiv.)A written practical scenario-based lab report on other machine learning features such as batch processing, R and Spring XD

N/AN/AN/ANo35 SILO4, SILO5, SILO6

Online subject test (1000-words equiv.)Multiple-choice and/or short answer questions test that covers all the topicsTimed assessment

N/AN/AN/ANo25 SILO4, SILO5

Online (Didasko), 2020, Study block 4, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 14 - 25
One 3.00 h 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 elementCommentsCategoryContributionHurdle% ILO*

Online test (250-words equiv.)Multiple-choice and/or short answer questions test on fundamentals of machine learning in cloud environmentTimed assessment

N/AN/AN/ANo10 SILO1

Written assignment on machine learning algorithm (1350-words equiv.)An assignment focused on identifying and applying the most appropriate learning algorithm to solve a real-world problem

N/AN/AN/ANo30 SILO2, SILO3

Written assignment on other machine learning features (1600-words equiv.)A written practical scenario-based lab report on other machine learning features such as batch processing, R and Spring XD

N/AN/AN/ANo35 SILO4, SILO5, SILO6

Online subject test (1000-words equiv.)Multiple-choice and/or short answer questions test that covers all the topicsTimed assessment

N/AN/AN/ANo25 SILO4, SILO5

Online (Didasko), 2020, Study block 5, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 19 - 30
One 3.00 h 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 elementCommentsCategoryContributionHurdle% ILO*

Online test (250-words equiv.)Multiple-choice and/or short answer questions test on fundamentals of machine learning in cloud environmentTimed assessment

N/AN/AN/ANo10 SILO1

Written assignment on machine learning algorithm (1350-words equiv.)An assignment focused on identifying and applying the most appropriate learning algorithm to solve a real-world problem

N/AN/AN/ANo30 SILO2, SILO3

Written assignment on other machine learning features (1600-words equiv.)A written practical scenario-based lab report on other machine learning features such as batch processing, R and Spring XD

N/AN/AN/ANo35 SILO4, SILO5, SILO6

Online subject test (1000-words equiv.)Multiple-choice and/or short answer questions test that covers all the topicsTimed assessment

N/AN/AN/ANo25 SILO4, SILO5

Online (Didasko), 2020, Study block 6, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 23 - 34
One 3.00 h 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 elementCommentsCategoryContributionHurdle% ILO*

Online test (250-words equiv.)Multiple-choice and/or short answer questions test on fundamentals of machine learning in cloud environmentTimed assessment

N/AN/AN/ANo10 SILO1

Written assignment on machine learning algorithm (1350-words equiv.)An assignment focused on identifying and applying the most appropriate learning algorithm to solve a real-world problem

N/AN/AN/ANo30 SILO2, SILO3

Written assignment on other machine learning features (1600-words equiv.)A written practical scenario-based lab report on other machine learning features such as batch processing, R and Spring XD

N/AN/AN/ANo35 SILO4, SILO5, SILO6

Online subject test (1000-words equiv.)Multiple-choice and/or short answer questions test that covers all the topicsTimed assessment

N/AN/AN/ANo25 SILO4, SILO5

Online (Didasko), 2020, Study block 7, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 27 - 38
One 3.00 h 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 elementCommentsCategoryContributionHurdle% ILO*

Online test (250-words equiv.)Multiple-choice and/or short answer questions test on fundamentals of machine learning in cloud environmentTimed assessment

N/AN/AN/ANo10 SILO1

Written assignment on machine learning algorithm (1350-words equiv.)An assignment focused on identifying and applying the most appropriate learning algorithm to solve a real-world problem

N/AN/AN/ANo30 SILO2, SILO3

Written assignment on other machine learning features (1600-words equiv.)A written practical scenario-based lab report on other machine learning features such as batch processing, R and Spring XD

N/AN/AN/ANo35 SILO4, SILO5, SILO6

Online subject test (1000-words equiv.)Multiple-choice and/or short answer questions test that covers all the topicsTimed assessment

N/AN/AN/ANo25 SILO4, SILO5

Online (Didasko), 2020, Study block 8, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 32 - 43
One 3.00 h 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 elementCommentsCategoryContributionHurdle% ILO*

Online test (250-words equiv.)Multiple-choice and/or short answer questions test on fundamentals of machine learning in cloud environmentTimed assessment

N/AN/AN/ANo10 SILO1

Written assignment on machine learning algorithm (1350-words equiv.)An assignment focused on identifying and applying the most appropriate learning algorithm to solve a real-world problem

N/AN/AN/ANo30 SILO2, SILO3

Written assignment on other machine learning features (1600-words equiv.)A written practical scenario-based lab report on other machine learning features such as batch processing, R and Spring XD

N/AN/AN/ANo35 SILO4, SILO5, SILO6

Online subject test (1000-words equiv.)Multiple-choice and/or short answer questions test that covers all the topicsTimed assessment

N/AN/AN/ANo25 SILO4, SILO5

Online (Didasko), 2020, Study block 9, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorRabei Alhadad

Class requirements

Unscheduled Online Class Week: 36 - 47
One 3.00 h 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 elementCommentsCategoryContributionHurdle% ILO*

Online test (250-words equiv.)Multiple-choice and/or short answer questions test on fundamentals of machine learning in cloud environmentTimed assessment

N/AN/AN/ANo10 SILO1

Written assignment on machine learning algorithm (1350-words equiv.)An assignment focused on identifying and applying the most appropriate learning algorithm to solve a real-world problem

N/AN/AN/ANo30 SILO2, SILO3

Written assignment on other machine learning features (1600-words equiv.)A written practical scenario-based lab report on other machine learning features such as batch processing, R and Spring XD

N/AN/AN/ANo35 SILO4, SILO5, SILO6

Online subject test (1000-words equiv.)Multiple-choice and/or short answer questions test that covers all the topicsTimed assessment

N/AN/AN/ANo25 SILO4, SILO5