BANASD603 _Assessment_3_ Presentation, Cert Exam, and Reflection _Module 6.1 Page 1 of 13
ASSESSMENT 3 BRIEF
Subject Code and Title BANASD603 Applied Optimisation in Business
Assessment Presentation with Machine Learning Model, Certification Exam, and
Reflection Presentation
Individual/Group Individual
Length Part A: Presentation (3 minutes, recorded) with Machine Learning
Model
Part B: Certification Exam and Reflection presentation (3 minutes, in
class)
Learning Outcomes The Subject Learning Outcomes demonstrated by successful
completion of the task below include:
c) Critique the selection of optimisation techniques to solve a
business problem.
d) Apply an optimisation technique to inform the business decision
making.
Submission Part A:
• Presentation with Machine Learning Model
Due by 11:55 pm AEST/AEDT Sunday, end of Module 6.1.
Part B:
• Certification Exam
Due by 11:55 pm AEST/AEDT Sunday, end of Module 6.1.
• Reflection Presentation
Due to be completed in the Module 6.2 class.
Weighting 40% (Part A: 22% and Part B: 18%)
Total Marks 100 marks
Assessment Task
You are required to complete three interrelated assessments for this subject with each being
assessed independently on their own merits. Assessment 3, which is the last one, includes two parts.
In Part A, you will conduct a 3 minute presentation (video recording with PowerPoint slides)
critiquing a machine learning model you have built using SAS Viya. The presentation should
demonstrate what analytics you completed (e.g., data preparation, model building and training, etc.)
BANASD603 _Assessment_3_ Presentation, Cert Exam, and Reflection _Module 6.1 Page 2 of 13
and how the results inform decision making. The target audience of your presentation is analytics
professionals. Thus, it is not necessary to explain or discuss technical concepts of data analytics. Part
B involves completing the SAS Certified Specialist: Machine Learning Using SAS Viya exam and
completing a 3 minute reflection presentation during the module 6.2 class. The reflection
presentation will demonstrate knowledge and skills acquired in relation to building machine learning
models using SAS Viya.
To be successful in this assessment, you are required to consolidate knowledge gained from
Modules 1.1 to 6.1 and read the essential resources in Module 6.2.
Context
In Part A of this assessment, you will build and present a final machine learning model to
demonstrate your comprehension of analytics. By completing this assessment, you will demonstrate
your ability to use an industrial tool to apply analytics and optimisation techniques in improving
business decisions and effectively communicating your findings. The assessment aim is to help you
develop necessary skills for turning data into actionable insights. For example, identifying a business
problem to solve, selecting an appropriate data analysis method, building the corresponding model
based on the dataset, and optimising its performance in addressing the business problem.
Part B of this assessment develops your skills in reflection, reflective writing and reflective practice
by communicating your understanding of SAS Viya and how it relates to your professional
development. Reflection is an important learning process involving the critical analysis of past
experiences: what was learned, the personal impact of the learnings and plans for utilising the new
knowledge. Assessment 3 involves thinking deeply about your experiences while learning about SAS
Viya and completing the SAS Certified Specialist: Machine Learning Using SAS Viya exam. This
globally recognised certification assesses your ability to produce quality machine learning models
using SAS Viya.
Instructions
The steps for completing Part A and Part B of Assessment 3 are listed in the two Instruction sections
detailed below.
Part A: Produce a machine learning model and Presentation (with slides)
Formally, Part A of Assessment 3 involves two steps.
1. Build a machine learning model to solve a business problem
Select data and pose analytics questions to solve using a machine learning model built with
SAS Viya. Instructions for setting up your SAS account and accessing the software were
provided in Module 2 (speak with your learning facilitator if you require additional support).
To build and deploy the model, draw upon relevant essential resources and learning
activities contained within Module 2 to 6. If appropriate, include feedback received from
BANASD603 _Assessment_3_ Presentation, Cert Exam, and Reflection _Module 6.1 Page 3 of 13
your Learning Facilitator in relation to Assessment 2 (Data pre-processing and business
proposal).
2. Record an online Presentation critiquing the machine learning model you built
Record a 3 minute video presentation using PowerPoint slides (separate submission of slides
is not required) to summarise and explain the machine learning model you have built. The
target audience of your presentation is analytics professionals. Thus, technical details should
be avoided with a preference of relevancy and conciseness preferred. In your presentations,
you should:
• Introduce yourself
• Present your slides in a logical sequence and use visualisation or diagrams
as appropriate
• Engage with the audience and talk clearly and fluently
• You should use in-text citations on slides where necessary.
Your presentation slides should be structured as follows:
1. Title:
• Title of your presentation and your name
2. Business problem
• The analytics problem and success criteria
3. Data
• Selected data and its source
• Highlight the data preparation and processing steps including features
contained in the dataset
4. Model Building
• Model selection, training, and assessment approach including analytical
method(s) used
5. Conclusion
• Findings based on your analysis
• Summarise your recommendation(s) for action including rationale to
support them
6. References:
• List references used in APA 7th format
7. Appendix:
• Provide a link to the dataset if you select public datasets, or submit
compressed dataset files with this presentation if they are private. Label
your zip file using the following naming convention:
BANASD603_LastnameFirstname_Assessment3Dataset.zip. Full instructions
for how to do so will be provided by your Learning Facilitator. If the dataset
is not a public dataset, you must attach a consent letter from the institution
who owns the dataset in the appendix of this presentation.
Part B: Certification exam and reflection presentation
Part B of Assessment 3: certification exam and reflection presentation involve three key steps, as
outlined below.
BANASD603 _Assessment_3_ Presentation, Cert Exam, and Reflection _Module 6.1 Page 4 of 13
Step 1: Consolidate study notes prepared for each of Modules 2.1 to 6.1 in preparation for the
SAS Certified Specialist exam.
To prepare for the remotely (online) proctored certification exam, collate and review weekly
study notes you have taken while undertaking short course with SAS Viya. Consider the impact
of learnings on you, your career development and future planning, including any evidence you
might like to keep for later use or reference.
These weekly study notes are required to be submitted as part of this assessment.
Step 2: Complete the proctored SAS Viya Certified Specialist: Machine Learning Using SAS Viya
exam remotely (online) by 11:55 pm AEST/AEDT Sunday, end of Module 6.1.
Login to SAS website for more information about registering and undertaking the certification
exam. Detailed guidance will be provided by your learning facilitator in Module 5.
You must include confirmation of your SAS Viya Certified Specialist exam completion/result,
issued by SAS, as an appendix in your reflection for Assessment 3.
Step 3: Perform an in-class presentation that addresses the following requirements.
Perform a 3 minute presentation during the module 6.2 class using PowerPoint slides (separate
submission of slides is not required). The presentation should reflect on your result in the
remote/online proctored SAS Certified Specialist: Machine Learning Using SAS Viya exam to
identify any gap in your machine learning knowledge and skills, and actions to close the gap.
Reflection Presentation Structure
Use the ‘What?’ model to structure your reflection, as shown in Figure 1.
Figure 1: The ‘What?’ model
• PAST
• Describe what
happened
What?
• PRESENT
• Make sense of
experience
So what?
• FUTURE
• Take action
Now what?
BANASD603 _Assessment_3_ Presentation, Cert Exam, and Reflection _Module 6.1 Page 5 of 13
Note: This figure was adapted from Borton (1970), Driscoll (2007) and Rolfe (2014).
APA References:
Borton, T. (1970). Reach, touch and teach. Hutchinson.
Driscoll, J. (ed.) (2007). Practicing clinical supervision: A reflective approach for healthcare
professionals. Elsevier.
Rolfe, G. (2014). Reach touch and teach. Nurse Education Today, 34(4), 488–489.
https://lesa.on.worldcat.org/oclc/5540529221
More specifically, please follow the headings and prompt questions below to guide your
reflection presentation:
1. Title Page
Include course ID and name, student ID, email and name, facilitator name, and date
of submission.
2. What?
For each topic of the SAS Certified Specialist exam, identify and describe learnings you acquired
(or not). Frame the description around facts. What prior knowledge or understanding of the
topics and concepts did you have, what learnings occurred and what tasks were performed to
acquire these learnings? Refer to the weekly study notes you prepared before undertaking the
proctored exam. Listed below are guiding questions for evaluating your learnings ahead of the
reflection presentation.
• Learning How to Build Machine Learning Models Using SAS Viya
o What was your previous understanding of the topics or concepts presented in the
subject?
o What learnings have you gained from content included in Modules 1.1 to 6.1?
o What specific experiences, events, situations, problems, issues, or examples in the
past relate to these learnings?
• Completing the SAS Certified Specialist Exam
o How did you prepare for the proctored exam?
o What was the outcome?
o What did you want to happen?
3. So what?
Makes sense of learnings of machine learning and experiences completing the SAS Certified
Specialist exam. Link positive or negative results with decisions you made while learning
about machine learning or preparing for the proctored exam. Listed below are guiding
questions for evaluating your learnings in your reflection.
• Learning How to Build Machine Learning Models Using SAS Viya
o What learnings and techniques that you used to complete the proctored exam were
successful (or unsuccessful)?
o What actions did you take, or decisions did you make, that led to a successful (or
unsuccessful) outcome?
BANASD603 _Assessment_3_ Presentation, Cert Exam, and Reflection _Module 6.1 Page 6 of 13
• Completing the SAS Certified Specialist Exam
o Why was your proctored exam attempt successful (or unsuccessful)?
o What sense can you make of the result?
o What knowledge helps with understanding the result?
4. Now what?
Identify possible future courses of action to advance your knowledge and skills. Listed below are
guiding questions for evaluating your learnings in your reflection. If you passed the SAS Certified
Specialist exam, appraise the practical application of this reflection in your professional
development. Alternatively, if you did not pass the SAS Certified Specialist exam on your first
attempt, identify what you could do differently to prepare for re-sitting the exam in your own
time.
• Learning How to Build Machine Learning Models Using SAS Viya
o What could you do differently to achieve better learning outcomes?
o What knowledge and skills do you require to extend your learnings of machine
learning?
• Completing the SAS Certified Specialist Exam
o What will you do differently, or the same, next time, to better prepare for the exam
or improve learning outcomes?
o How will you use the knowledge and skills you have acquired in the future?
5. Reference List
6. Appendix – This includes the following:
• Evidence confirming your attempt of the SAS Certified Specialist exam.
For additional guidance, you will find more information on Reflective Writing and Thinking at
the Academic Skills webpage.
Referencing
It is essential that you use appropriate APA style for citing and referencing research. Please see more
information on referencing in the Academic Skills webpage.
Submission Instructions
Submit this task via the Assessment link in the main navigation menu BANASD603: Applied
Optimisation in Business. Your submission will consist of two files:
1. The pre-recorded presentation in a video format.
2. A copy of all weekly study notes in word (doc.) format.
Note: If your dataset is private you must submit compressed dataset files with the presentation.
Label your zip file using the following naming convention:
BANASD603_LastnameFirstname_Assessment3Dataset.zip. Full instructions for how to do so will be
provided by your Learning Facilitator. If the dataset is not a public dataset, you must attach a
consent letter from the institution who owns the dataset in the appendix of this report.
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Please note during the submission process: If you would like to include a second file in your
submission, once your first item has been uploaded, click ‘Browse Your Computer’ to attach the
extra documents. Then, click Final Submit button.
The Learning Facilitator will provide feedback via the Grade Centre in the LMS portal. Feedback can
be viewed in My Grades.
Academic Integrity
All students are responsible for ensuring that all work submitted is their own and is appropriately
referenced and academically written according to the Academic Writing Guide. Students also need
to have read and be aware of Torrens University Australia Academic Integrity Policy and Procedure
and subsequent penalties for academic misconduct. These are viewable online.
Students also must keep a copy of all submitted material and any assessment drafts.
Special Consideration
To apply for special consideration for a modification to an assessment or exam due to unexpected or
extenuating circumstances, please consult the Assessment Policy for Higher Education Coursework
and ELICOS and, if applicable to your circumstance, submit a completed Application for Assessment
Special Consideration Form to your Learning Facilitator
BANASD603 _Assessment_3_ Presentation, Cert Exam, and Reflection _Module 6.1 Page 8 of 13
Assessment Rubric
Assessment
Attributes
Fail
(Yet to achieve
minimum standard)
0-49%
Pass
(Functional)
50-64%
Credit
(Proficient)
65-74%
Distinction
(Advanced)
75-84%
High Distinction
(Exceptional)
85-100%
Part A: Produce a machine learning model and Presentation (with slides)
Part A: Data: Selection,
Preparation, and
Processing
Total Percentage for
this Assessment
Attribute = 10%
2.5% Data Selection
Fails to identify
appropriate data source
for addressing the
business problem and
poorly describes the
features of the dataset.
Data source for addressing
the business problem
somewhat appropriate with
some effort made to describe
features of the dataset.
Data source appropriate for
addressing business
problem but overly
simplistic. Features of the
dataset described at a basic
level.
Data source appropriate for
addressing business
problem. Features of the
dataset described but with
at least one omission or
lack of clarity
Data source appropriate for
addressing business
problem and features of
the dataset are clearly
described and facilitate
comprehensive analysis.
2.5% Data Preparation
Fail to analyse features in
the dataset via descriptive
statistics, or fail to
perform outlier detection
Limited efforts are made to
analyse features in the
dataset via descriptive
statistics, and perform outlier
detection
Basic features analysis via
descriptive statistics and
outlier detection are
provided
Features analysis via
descriptive statistics and
outlier detection are fully
provided, but with at least
one omission
Insightful features analysis
via descriptive statistics and
outlier detection are
provided.
5% Data Processing
Fail to examine the quality
of the data and determine
whether it meets the
requirements of the
analytical techniques
chosen for the project.
Limited effort is made to
determine the quality of data
and improve its quality of
data required by the
analytical techniques chosen
for the project
Basic analysis of the quality
of data and any needed
improvements required by
the analytical techniques
chosen for the project are
provided.
Analysis of the quality of
data and any needed
improvements required by
the analytical techniques
chosen for the project are
fully provided, but with at
least one omission.
Comprehensive analysis of
the quality of data and any
needed improvements
required by the analytical
techniques chosen for the
project are provided.
Part A: Understanding
of business problem,
analytics questions and
model building
5% Business Problem
Business problem and
analytics goals or success
criteria poorly defined
Limited efforts are made to
define business problems,
Basic business problems,
analytics goals, and success
criteria defined.
Business problem, analytics
goals, and success criteria
Insightful and
comprehensive definition
of business problems,
BANASD603 _Assessment_3_ Presentation, Cert Exam, and Reflection _Module 6.1 Page 9 of 13
Total Percentage for
this Assessment
Attribute = 25%
analytics goals, and success
criteria.
well defined but with at
least one minor omission.
analytics goals, and success
criteria
10% Model Training and Assessment
Fail to sample only
portions of the data for
model training or fail to
assess the model
performance.
Limited efforts are made to
partition the data for training
and assess the model
performance.
Data are partitioned in two
parts: training and testing.
Only training data partitions
are used to train the model.
One performance criterion
is chosen to assess the
model performance
Data are partitioned in two
parts: training and testing.
Only training data partitions
are used to train the model.
Multiple performance
criteria are used to assess
the model performance but
the explanations of their
relevance are unclear
Data are appropriately
partitioned in two parts:
training and testing. Both
training and testing data
partitions are used to train
the model. Multiple
performance criteria are
used to assess the model
performance and
adequately explained
10% Model Selection and Optimisation
Fail to justify selection of
champion model and
identify optimisation
techniques that may be
applied to improve its
performance
Limited efforts are made to
justify the selection of
champion model and identify
optimisation techniques that
may be applied to improve its
performance.
Selected champion model
somewhat justified with
optimisation techniques
identified to improve its
performance.
Good justification for
selection of champion
model with optimisation
techniques identified and
applied to improve its
performance.
Excellent justification
provided in support of
selected champion model.
Optimisation techniques
identified and applied to
improve the model
performance. Optimisation
results are shown to
improve the original model.
Part A:
Recommendations for
action
Total Percentage for
this Assessment
Attribute = 10%
5% Ethical/Legal Issues
Fail to discuss ethical/legal
concerns of this analytics
project
Limited efforts are made to
identify ethical/legal
concerns of this analytics
project
Ethical/legal concerns of
this analytics project are
identified and discussed at
the basic level.
Ethical/legal concerns of
this analytics project are
identified, and good
discussion is provided.
Outstanding discussion of
ethical/legal concerns of
this analytics project.
5% Business recommendations
BANASD603 _Assessment_3_ Presentation, Cert Exam, and Reflection _Module 6.1 Page 10 of 13
Fail to provide actionable
recommendations in the
business context or fail to
justify such
recommendations based
on the results of the
project.
Limited efforts are made to
provide actionable
recommendations in the
business context or to justify
such recommendations based
on the results of the project.
Basic actionable
recommendations are
made in the business
context and such
recommendations are
justified based on the
results of the project.
Good actionable
recommendations are
made in the business
context and such
recommendations are
justified based on the
results of the project.
Outstanding actionable
recommendations are
made in the business
context and such
recommendations are well
justified based on the
results of the project.
Part A: Effective
Communication
Total percentage for
this Assessment
Attribute = 10%
5% Use of PowerPoint Slides
No slides are used, or
slides are only
occasionally appropriate
and related to the spoken
message.
Slides require significant
improvement in design,
colour choice, layout
and/or neatness.
Only the minimum number of
slides support the
presentation. They mostly
clarify and reinforce the
spoken message.
Some slides require
improvement in design,
colour choice, layout and/or
neatness.
Some slides show key
information supported by
evidence and citations.
The minimum number of
slides support the
presentation effectively.
They clarify and reinforce
the spoken message.
Slides have an acceptable
level of design, colour
choice, layout and neatness
that support the flow of
information.
Most slides show key
information supported by
evidence and citations.
More than the minimum
number of slides are
carefully prepared and
support the presentation
effectively. They clarify and
reinforce the spoken
message.
Slides add interest to the
presentation through
effective design, colour
choice, layout and neatness
and support the flow of
information.
All slides show key
information supported by
evidence and citations.
More than the minimum
number of slides are
carefully prepared and
support the presentation
effectively. They clarify and
reinforce the spoken
message.
Slides add impact and
interest through a
professional level of design,
colour choice, layout and
neatness and support the
flow of information.
All slides show key
information supported by
substantial evidence and
citations.
5% Verbal Communication
Presentation delivery tone
is too casual, and the
student only reads from
the slide.
Presentation delivery style is
professional.
Student demonstrates
familiarity of the content of
Presentation delivery style
is professional.
Student demonstrates
familiarity of the content of
Presentation delivery style
is professional.
Student demonstrates
familiarity of the content of
Presentation delivery tone
is professional, and the
student demonstrates
familiarity of the content of
BANASD603 _Assessment_3_ Presentation, Cert Exam, and Reflection _Module 6.1 Page 11 of 13
Student’s face and voice is
not clearly presented, and
the recording of the
presentation has poor
audio or video quality,
and the presentation is <2
minutes or > 6 minutes.
their presentation.
Occasionally the presentation
may be incoherent or illogical
Sometimes, student’s face
and voice are not clearly
presented, and the recording
of the presentation has some
quality issues.
their presentation and the
content is coherent and
logical
Occasionally student’s face
and voice are not clearly
presented, and the
recording of the
presentation is well-
prepared.
their presentation and the
content is coherent and
logical
Student’s face and voice are
clearly presented, and the
recording of the
presentation is well-
prepared.
the presentation and the
content is coherent and
logical
Student’s face and voice
are clearly presented, and
the recording of the
presentation is well-
prepared.
The presentation meets the
time requirement
Part B: Certification exam and reflection presentation
Part B: Identification of
knowledge and skills
and their impact on
outcomes
Total percentage for
this Assessment
Attribute = 10%
10% Identify Impact
Does not identify
knowledge and skills
developed and their
impact on outcomes;
evidence of study notes is
missing.
An attempt to identify
knowledge and skills
developed, with evidence of
study notes. The links to
outcomes require further
explanation.
Adequately identified
knowledge and skills
developed, with evidence
of study notes. Links to
outcomes require further
explanation.
Cleary and accurately
identified evidence of
knowledge and skills
developed, with some links
to outcomes.
Expertly and discerningly
identified evidence of
knowledge and skills
developed, with clear links
to outcomes provided.
Part B: Application of
machine learning
knowledge and skills to
future career and
professional
development
Total percentage for
this Assessment
Attribute = 10%
10% Apply Knowledge
Very limited insight of
how to apply the
knowledge and skills to
career and professional
development.
Basic insight of how to apply
the knowledge and skills to
career and professional
development.
Some insights of how to
apply the knowledge and
skills to career and
professional development.
Sufficient insights of how to
apply the knowledge and
skills to career and
professional development.
Insightful description of
how to apply the
knowledge and skills to
career and professional
development.
Part B: Reflection and
analysis of learning and
experiences
10% Reflect on Learning
Reflection of learnings
fails to demonstrate how
the student has
Reflection of learnings is
supported with minimal
details and examples of how
Reflection of learnings is
supported with sufficient
details and examples of
Reflection of learnings is
supported by a thorough
examination of experiences
Reflection of learnings
discerningly examines
experiences in depth
BANASD603 _Assessment_3_ Presentation, Cert Exam, and Reflection _Module 6.1 Page 12 of 13
Total percentage for
this Assessment
Attribute = 10%
developed. Details and
examples provided are
mostly irrelevant.
the student has developed.
Some of the details and
examples provided are
relevant but need further
explanation.
how the student has
developed. Most details
and examples provided are
relevant.
and supported with highly
relevant details and
examples.
through a wide range of
highly relevant details and
insights.
Part B: Completion of
Certification Exam
Total percentage for
this Assessment
Attribute = 7.5%
7.5% Certification Exam
Did not attempt to
complete the certification
exam. No evidence of
result provided.
Attempted to complete the
certification exam with
evidence of enrolment but no
result provided
Completed but failed the
certification exam with
evidence of result provided
Completed and passed the
certification exam with
evidence of result provided.
Completed and passed the
certification exam with
evidence of result provided
with an exemplary score
achieved.
Part B: Effective
Communications
Total Percentage for
this Assessment
Attribute = 7.5%
2.5% Use of PowerPoint Slides
No slides are used, or
slides are only
occasionally appropriate
and related to the spoken
message.
Slides require significant
improvement in design,
colour choice, layout
and/or neatness.
Only the minimum number of
slides support the
presentation. They mostly
clarify and reinforce the
spoken message.
Some slides require
improvement in design,
colour choice, layout and/or
neatness.
Some slides show key
information supported by
evidence and citations.
The minimum number of
slides support the
presentation effectively.
They clarify and reinforce
the spoken message.
Slides have an acceptable
level of design, colour
choice, layout and neatness
that support the flow of
information.
Most slides show key
information supported by
evidence and citations.
More than the minimum
number of slides are
carefully prepared and
support the presentation
effectively. They clarify and
reinforce the spoken
message.
Slides add interest to the
presentation through
effective design, colour
choice, layout and neatness
and support the flow of
information.
All slides show key
information supported by
evidence and citations.
More than the minimum
number of slides are
carefully prepared and
support the presentation
effectively. They clarify and
reinforce the spoken
message.
Slides add impact and
interest through a
professional level of design,
colour choice, layout and
neatness and support the
flow of information.
All slides show key
information supported by
substantial evidence and
citations.
5% Verbal Communication
BANASD603 _Assessment_3_ Presentation, Cert Exam, and Reflection _Module 6.1 Page 13 of 13
Presentation delivery tone
is too casual, and the
student only reads from
the slide.
Student’s face and voice is
not clearly presented, and
the recording of the
presentation has poor
audio or video quality,
and the presentation is <2
minutes or > 6 minutes.
Presentation delivery style is
professional.
Student demonstrates
familiarity of the content of
their presentation.
Occasionally the presentation
may be incoherent or illogical
Sometimes, student’s face
and voice are not clearly
presented, and the recording
of the presentation has some
quality issues.
Presentation delivery style
is professional.
Student demonstrates
familiarity of the content of
their presentation and the
content is coherent and
logical
Occasionally student’s face
and voice are not clearly
presented, and the
recording of the
presentation is well-
prepared.
Presentation delivery style
is professional.
Student demonstrates
familiarity of the content of
their presentation and the
content is coherent and
logical
Student’s face and voice are
clearly presented, and the
recording of the
presentation is well-
prepared.
Presentation delivery tone
is professional, and the
student demonstrates
familiarity of the content of
the presentation and the
content is coherent and
logical
Student’s face and voice
are clearly presented, and
the recording of the
presentation is well-
prepared.
The presentation meets the
time requirement