Recent Question/Assignment

Weighting: 30% Learning Outcomes: 4,5,6,7
Graduate Attributes: 1,3,4,6 Length: 1500 words Due date: Week 11
Machine Learning applications have become a part of everyday life, particularly in business and industry.
Write a report on two past business & financial services activities that have now been taken over by machine learning functionality.
1. What are the machine learning applications that you will report on? Please describe.
2. What business & financial services activities do they replace?
3. What are their advantages?
4. What are their disadvantages?
5. Are there any ethical considerations in the use of machine learning products?
6. Many employees feel threatened because they believe that their jobs will be replaced by machine learning functionality. Do you agree or disagree with this belief? Please make sure that your point of view is well supported by solid research.
7. Explain how managers in the business & financial services industry plan, organise, lead and control a workplace that integrates machine learning functions with a human workforce.
Please use this format:
Title Page
Table of Contents
Executive Summary
1.0 Introduction
2.0 Machine Learning in business & financial services—Two applications
3.0 Business & financial services activities replaced
4.0 Advantages and disadvantages of machine learning applications
4.1 (First application) - Advantages and disadvantages
4.2 (Second application) - Advantages and disadvantages
5.0 Ethical considerations in using products of machine learning
6.0 Machine Learning applications — employee beliefs
7.0 Managerial functions in a machine learning integrated workplace
8.0 Conclusions
9.0 Recommendations
Reference List
You must:
• Read the Business Reports Helpsheet. It is in the Welcome to Management Fundamentals tab of the Moodie.
• Pay attention to any report tuition given in Academic Foundations subject
• Provide in-text referencing — minimum of 6
• Generally, section 1.0 - Introduction should guide the reader on how you are going to approach the topic. It should provide a brief overview of the key areas you are going to cover and your main recommendations.
• The discussion section 2.0 through to 7.0 should integrate your research and ideas into key arguments and cover the report requirements.
• The conclusion and recommendation sections — 8.0 and 9.0 should comment on the implications of your findings for industry practice.
TAFE NSW — Higher Education Semester 2, 2019 Page I 21
Subject Guide: BUMGT101A/ACBUS102A Management Fundamentals
• The report should be 1500 words in length (excluding title page and references) and professionally presented. 12 point, 1'% spaced, Arial or Calibri font is preferred. Word counts must be within 4. or -10 % of 1500 words excluding the Title Page, Table of Contents, Executive Summary and Reference List
• The report should be written in using academic conventions with proper citations and references. As a
guide, at least 4 academic references are envisaged. Appropriate sources of reference material are:
• Prescribed textbook (Robbins 4th Ed)
• Government website/s
• Academic journal/s
• Industry association website/s or article/s
• References must be documented using TAFE NSW Harvard reference style.
• Work submitted for all assessments must be accompanied by a completed and signed copy of the Assessment Cover Sheet. Students must always retain an electronic copy of all assessments.
• The following Marking Rubric will guide you on how your work will be marked out of 100
• Grading: High Distinction: 85-100 Distinction: 75-84 Credit: 65-74 Pass: 50-64 Fail: Less than 50%
7. Explain how managers in the business & financial services industry plan, organise, lead and control a workplace that integrates machine learning functions with a human workforce.
Please use this format:
Title Page
Table of Contents
Executive Summary
1.0 Introduction
2.0 Machine Learning in business & financial services—Two applications
3.0 Business & financial services activities replaced
4.0 Advantages and disadvantages of machine learning applications
4.1 (First application) - Advantages and disadvantages
4.2 (Second application) - Advantages and disadvantages
5.0 Ethical considerations in using products of machine learning
6.0 Machine Learning applications — employee beliefs
7.0 Managerial functions in a machine learning integrated workplace
8.0 Conclusions
9.0 Recommendations
Reference List
You must:
• Read the Business Reports Helpsheet. It is in the Welcome to Management Fundamentals tab of the Moodie.
• Pay attention to any report tuition given in Academic Foundations subject
• Provide in-text referencing — minimum of 6
• Generally, section 1.0 - Introduction should guide the reader on how you are going to approach the topic. It should provide a brief overview of the key areas you are going to cover and your main recommendations.
• The discussion section 2.0 through to 7.0 should integrate your research and ideas into key arguments and cover the report requirements.
• The conclusion and recommendation sections — 8.0 and 9.0 should comment on the implications of your findings for industry practice.
TAFE NSW — Higher Education Semester 2, 2019 Page I 21
Subject Guide: BUMGT101A/ACBUS102A Management Fundamentals
• The report should be 1500 words in length (excluding title page and references) and professionally presented. 12 point, 1''I spaced, Arial or Calibri font is preferred. Word counts must be within + or -10 % of 1500 words excluding the Title Page, Table of Contents, Executive Summary and Reference List
• The report should be written in using academic conventions with proper citations and references. As a guide, at least 4 academic references are envisaged. Appropriate sources of reference material are:
• Prescribed textbook (Robbins 4th Ed)
• Government website/s
• Academic journal/s
• Industry association website/s or article/s
• References must be documented using TAFE NSW Harvard reference style.
• Work submitted for all assessments must be accompanied by a completed and signed copy of the Assessment Cover Sheet. Students must always retain an electronic copy of all assessments.
• The following Marking Rubric will guide you on how your work will be marked out of 100
• Grading: High Distinction: 85-100 Distinction: 75-84 Credit: 65-74 Pass: 50-64 Fail: Less than 50%
Fail Pass Credit Distinction High
Distinction
Response Response is Most of the main All of the main issues are All of the main All of the main
superficial, issues are identified identified and most are issues are issues are
inadequate or but there is limited elaborated on identified identified
incomplete or elaboration of the and question is including
word limit issues answered in full exploration of

Editable Microsoft Word Document
Word Count: 1859 words including References

Title: MACHINE LEARNING IN BUSINESS


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