MIS373 –Artificial Intelligence for Business
Trimester 1, 2022
Assessment 3 (Individual) – Business Report
DUE DATE AND TIME: Due 5th June 2022 8:00PM AEST
PERCENTAGE OF FINAL GRADE: 30%
WORD LIMIT: 2000 words
Word limits is applied for this assignment. Note that cover page, references, table of contents, tables and figures (if any) are not included in the word count.
Learning Outcome Details
|Unit Learning Outcome (ULO)||Graduate Learning Outcome (GLO)|
|ULO3: Critically evaluate feasibility and applicability of Artificial Intelligence techniques in business environments.||GLO1: Discipline-specific knowledge and capabilities GLO4: Critical thinking|
This is the final assessment task in MIS373. Marks and feedbacks will be returned to students after the unit results are released
No extensions will be considered unless a written request is submitted and negotiated with the Unit Chair before the due date and time. Extensions will only be considered if a draft assignment is attached with your request for an extension, which shows progress has been made. Extension request form must be filled and sent to the unit chair, which is accompanied by appropriate documentary evidence for the extension. Submissions after the due date/time without an approved extension will be considered late.
Extensions are only granted in extreme circumstances, such as ongoing health, personal hardship or work-related problems. Temporary illnesses, normal work pressures, multiple assignments due at the same time, failure to keep backups, technology failure, etc are not reasons for an extension. Extension request form can be access from https://www.deakin.edu.au/students/faculties/buslaw/student-support/assignment-extensions
This assignment aims for students to learn to:
- Understand the applications of analytics and AI solutions in various business context.
- Appraise the suitability of the solutions to solve business problems.
- Critically evaluate the outcomes of the solutions and practical implications of the findings.
You are to conduct research and write a report about business applications of specific analytics and AI solutions. You are to search on the Internet (e.g., business websites) and Academic Databases (e.g. SCOPUS, Science Direct) for business case studies that employed the selected solutions. Each business case study can be a business report or a scholarly (journal/conference) article about a specific solution. You should read the collected articles, understand their business problems, and critically evaluate the employed analytics/AI solutions. You should write a critical review and analyse each of the case studies following the (suggested) points below:
- Businesses problem: Which industry does the firm(s)/organization(s) belong? Summarize and define their business problem(s).
- Methodology: What insights are to be discovered? Or What tasks are to be solved? Critically evaluate and justify why such Analytics/AI approach was used in relation to the business problem(s)? Was the Analytics/AI approach used in combination with other Analytics/AI approach approaches? If yes, why and how? If no, why not?
- Data: Describe the data used in the case study: data source, data collection, attributes, and/or other relevant information.
- Analysis: Describe the steps taken to process the collected data. Explain how the Analytics/AI was applied to the processed data. Note that explanation should link to the relevant technical concepts of the analytics/AI techniques introduced in the weekly contents (where applicable).
- Result: Describe the major results and findings. Critically evaluate and explain why the outcomes are sufficient or insufficient to address the business problem defined in the case study.
- Implication: What practical implications were offered? What benefits can the firm(s)/organization(s) gain from such recommendations/solutions?
Note that above points should be treated mainly as a guide. It is depending on the specific case study and analytics/AI solution, so that the specific contents can be varied where necessary. You will select three case studies for your assignment.
The first case study should be relevant to one of the below topics:
· Text analytics – modelling and basic concepts (Week 5)
- Text analytics applications – sentiment analysis (Week 6)
- Advanced text analytics: NER and topic modelling (Week 7) The second case study should be relevant to one of the below topics:
· Feature and model selection in predictive modelling (Week 8)
- Anomaly detection with PCA and one-class SVMs (Week 9)
· Signal data classification with Hidden Markov Models (Week 10)
The third case study can be any AI related topic of your choice and can be beyond the topics covered in this unit.
Among the selected case studies, at least two must come from scholarly articles published in Academic Databases. In addition to the case studies, you should also research and use extra resources to support your critical evaluation throughout the report. You can use text, tables or figures from the online resources; however, appropriate paraphrasing and summarization must be applied, citations and references must be provided.
The preferred referencing styles for this assignment is APA7. Other referencing styles are alco accepted. However, ensure that all references are consistently formatted following the same chosen referencing style. Refer to Deakin Referencing Guide for detailed information https://www.deakin.edu.au/students/studying/study-support/referencing.
The report should be written following Academic writing style https://www.deakin.edu.au/students/studying/study-support/academic-skills/academic-style
Scholarly articles can be accessed from Academic Databases through Deakin Library https://www.deakin.edu.au/library/a-z/databases
A business report that contains
- Case Study 1: Identify the business case study and the analytics/AI solution and write a critical review.
- Case Study 2: Identify the business case study and the analytics/AI solution and write a critical review.
- Case Study 3: Identify the business case study and the analytics/AI solution and write a critical review.
- Reflection: Investigate the industry and potential companies that you plan work in the future. Identify potential business problems. Explain how your future company/business can benefit from adopting some of the analytics/AI solutions discussed the previous sections. If the previously discussed analytics/AI solutions are not suitable for your future situation, then identify and explain about other solutions that you think applicable.
In addition to the above sections, a professional report should also contain cover page, table of content and reference sections. Your report should be written and presented following the highest standard. Marks are allocated to the presentation of the report.
See CloudDeakin for more info about this assignment, especially the marking rubric.
The assignment must be prepared using Microsoft Word. There is no template provided for this assignment. However, the report must be professionally formatted following the structure outlined above. Sections and subsections must be named and numbered appropriately. Upon completion of the assignment, name your file as your firstname_lastname_MIS373A3 (e.g. John_Smith_MIS373A3.docx).
You are to submit your assignment in the individual Assignment Dropbox in the MIS373 CloudDeakin unit site on or before the due date. Do NOT zip the file. Any submission contained in a zip file will not be marked.
Do not upload files obtained from the Internet or Academic Database to your submission dropbox as you do not own the copyrights. Instead, provide references and in-text citations in your report where appropriate.
- Any work you submit may be checked by electronic or other means for the purposes of detecting collusion and/or plagiarism
- Feel free to discuss concepts and ideas with peers but remember your submission must be your own work. Be careful not to allow others to copy your work.
- You must keep a backup copy of every assignment you submit, until the marked assignment has been returned to you. In the unlikely event that one of your assignments is misplaced, you will need to submit your backup copy.
- When you are required to submit an assignment through your CloudDeakin unit site, you will receive an email to your Deakin email address confirming that it has been submitted. You should check that you can see your assignment in the Submissions view of the Assignment dropbox folder after upload, and check for, and
keep, the email receipt of the submission.
- Penalties for late submission: The following marking penalties will apply if you submit an assessment task after the due date without an approved extension: 5% will be deducted from available marks for each day up to five days, and work that is submitted more than five days after the due date will not be marked. You will receive 0% for the task. ‘Day’ means working day for paper submissions and calendar day for electronic submissions. The Unit Chair may refuse to accept a late submission where it is unreasonable or impracticable to assess the task after the due date.
Get expert help for MIS373 –Artificial Intelligence for Business and many more. 24X7 help, plag-free solution. Order online now!