Faculty of Science, Engineering and Built Environment
SIT112 Data Science Concepts Deakin University Unit Guide Trimester 1, 2021
CONTENTS
WELCOME ……………………………………………………………………………………………………………………………………………………… 2 WHO IS THE UNIT TEAM? ………………………………………………………………………………………………………………………………… 2 Unit chair: leads the teaching team and is responsible for overall delivery of this unit ……………………………………… 2 Unit chair details ……………………………………………………………………………………………………………………………………… 2 Other members of the team and how to contact them …………………………………………………………………………………. 2 Administrative queries ……………………………………………………………………………………………………………………………… 2 ABOUT THIS UNIT …………………………………………………………………………………………………………………………………………… 3 Unit development in response to student feedback ……………………………………………………………………………………… 3 Your course and Deakin’s Graduate Learning Outcomes ……………………………………………………………………………….. 3 Your Unit Learning Outcomes ……………………………………………………………………………………………………………………. 4 ASSESSING YOUR ACHIEVEMENT OF THE UNIT LEARNING OUTCOMES ………………………………………………………………… 4 Summative assessments …………………………………………………………………………………………………………………………… 4
– Summative assessment task 1
– Summative assessment task 2
– Summative assessment task 3
– Summative assessment task 4
Your learning experiences in this Unit – and your expected commitment ………………………………………………………… 8 Scheduled learning activities – campus ……………………………………………………………………………………………………….. 8 Scheduled learning activities – cloud …………………………………………………………………………………………………………… 8 Note (on-campus learning activities) ………………………………………………………………………………………………………….. 8 Note ……………………………………………………………………………………………………………………………………………………….. 9
…………………………………………………………………………………………………………………. 5 …………………………………………………………………………………………………………………. 5 …………………………………………………………………………………………………………………. 6 …………………………………………………………………………………………………………………. 7
UNIT LEARNING RESOURCES ……………………………………………………………………………………………………………………………. 9 Essential learning resources ………………………………………………………………………………………………………………………. 9
Recommended learning resources …………………………………………………………………………………………………………….. KEY DATES FOR THIS TRIMESTER ……………………………………………………………………………………………………………………… UNIT WEEKLY ACTIVITIES ………………………………………………………………………………………………………………………………. 10
9 9
19 February 2021
Deakin University, Faculty of Science, Engineering and Built Environment SIT112 Data Science Concepts – Trimester 1, 2021
Welcome to the unit SIT112 – Data Science Concepts. Data science is an emerging field and data scientists must be able to know how to make sense of data. This unit will help you develop knowledge and practice of data science, in particular data manipulation and algorithms for analytics. The SIT112 teaching team hopes that you will find this unit both intellectually stimulating and relevant to your studies in your current course and your future directions as a Deakin graduate.
You may need to contact the unit chair at some stage during this trimester. Most communication will be via the discussion boards on the unit site (accessed in DeakinSync), however, you can also contact us directly. If we are not in our offices when you call, please leave a message on our voicemail or email us and we will respond as soon as possible. Additional information on how to contact us and allocated time for contact is available in the class notes.
This Unit Guide provides you with the key information about this Unit. For the best chance of success, you should read it very carefully and refer to it frequently throughout the trimester. Your Unit site (accessed in DeakinSync) also provides information about your rights and responsibilities. We will assume you have read this before the Unit commences, and we expect you to refer to it throughout the trimester.
Due to the coronavirus (COVID-19) situation, you may be learning in a way that is new to you. We appreciate your flexibility and dedication to learning. For a range of helpful services and resources, please go to study support https://www.deakin.edu.au/students/studying/study-support.
WHO IS THE UNIT TEAM?
Unit chair: leads the teaching team and is responsible for overall delivery of this unit Sergiy Shelyag
Unit chair details
WELCOME
Name: Campus:
Email: Phone:
Dr Sergiy Shelyag
Burwood Campus 221 Burwood Hwy BURWOOD VIC 3125
sergiy.shelyag@deakin.edu.au
+61 3 924 68873
Other members of the team and how to contact them
Name: Campus:
Email:
Anagi Gamachchi
Melbourne Burwood Campus 221 Burwood Highway BURWOOD VIC 3125
a.gamachchi@deakin.edu.au
Administrative queries
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Deakin University, Faculty of Science, Engineering and Built Environment SIT112 Data Science Concepts – Trimester 1, 2021
• Contact your Unit Chair or Campus Leader
• Drop in or contact Student Central to speak with a Student Adviser
For additional support information, please see the Rights and Responsibilities section under ‘Content’ in your unit site.
ABOUT THIS UNIT
Data science is an emerging field and data scientists must be able to know how to make sense of data. In SIT112, students will develop knowledge of fundamentals in data science, in particular data manipulation and algorithms for analytics. The unit will also cover the practice of data science including ethical and responsible behaviour when crawling, cleaning, analysing, representing and repurposing the data. Students will be able to obtain data, recognise data formats, summarise and visualise relationships in the data, perform exploratory data analysis tasks and build predictive models.
Unit development in response to student feedback
Every trimester, we ask students to tell us, through eVALUate, what helped and hindered their learning in each Unit. You are strongly encouraged to provide constructive feedback for this Unit when eVALUate opens (you will be emailed a link).
In previous versions of this unit, students have told us that these aspects of the Unit have helped them to achieve the learning outcomes:
• The lectures were particularly engaging and the lecturer clearly had a passion and depth of knowledge on the topic which made it easy to listen and learn.
• The units assignments very relevant to todays real-life situation.
• The theory and computer practicals.
They have also made suggestions for improvement, and so this is what we have done:
• In response to student feedback, we reviewed the number and method of assessments, reduced the size of assignments and introduced a final exam.
• We will keep ensuring that the level of feedback provided by sessional markers for assignments is adequate.
If you have any concerns about the Unit during the trimester, please contact the unit teaching team – preferably early in the trimester – so we can discuss your concerns, and make adjustments, if appropriate.
Your course and Deakin’s Graduate Learning Outcomes
GLO1 Discipline-specific appropriate to the level of study related to a discipline or profession knowledge and
capabilities:
GLO2 Communication:
GLO3 Digital literacy:
GLO4 Critical thinking:
GLO5 Problem solving:
GLO6 Self-management:
GLO7 Teamwork:
GLO8 Global citizenship:
using oral, written and interpersonal communication to inform, motivate and effect change
using technologies to find, use and disseminate information
evaluating information using critical and analytical thinking and judgment
creating solutions to authentic (real world and ill-defined) problems
working and learning independently, and taking responsibility for personal actions
working and learning with others from different disciplines and backgrounds
engaging ethically and productively in the professional context and with diverse communities and cultures in a global context
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Deakin University, Faculty of Science, Engineering and Built Environment SIT112 Data Science Concepts – Trimester 1, 2021
Each Deakin course has course learning outcomes which explain what the Deakin Learning Outcomes mean in your discipline. Learning in each unit builds towards the course learning outcomes.
Your Unit Learning Outcomes
Each Unit in your course is a building block towards these Graduate Learning Outcomes – not all Units develop and assess every Graduate Learning Outcome (GLO).
These are the Learning Outcomes (ULO) for this Unit
At the completion of this Unit successful students can:
Deakin Graduate Learning Outcomes
ULO1
Demonstrate data acquisition, data representation and data pre-processing skills to describe, analyse and repurpose data from a variety of sources.
GLO1: Discipline-specific knowledge and capabilities
GLO2: Communication GLO3: Digital literacy GLO4: Critical thinking GLO5: Problem solving GLO7: Teamwork
ULO2
Apply critical thinking and statistical techniques to understand and visualize relationships in data
GLO2: Communication GLO4: Critical thinking GLO5: Problem solving GLO7: Teamwork
ULO3
Apply machine-learning techniques in exploratory data analysis for problems related to commerce, industry and research.
GLO1: Discipline-specific knowledge and capabilities
GLO3: Digital literacy GLO4: Critical thinking GLO5: Problem solving GLO7: Teamwork
ULO4
Design and compute a statistical relationships in data including correlation and linear regression
GLO1: Discipline-specific knowledge and capabilities
GLO4: Critical thinking GLO5: Problem solving GLO7: Teamwork
ULO5
Design and develop data-driven algorithms for outcome prediction
GLO1: Discipline-specific knowledge and capabilities
GLO5: Problem solving GLO7: Teamwork
These Unit Learning Outcomes are applicable for all teaching periods throughout the year
ASSESSING YOUR ACHIEVEMENT OF THE UNIT LEARNING OUTCOMES
Summative assessments
(tasks that will be graded or marked)
Deakin has a universal assessment submission time of 8 pm AEDT/AEST. A late penalty will apply to assessments submitted
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Deakin University, Faculty of Science, Engineering and Built Environment SIT112 Data Science Concepts – Trimester 1, 2021
NOTE: It is your responsibility to keep a backup copy of every assignment where it is possible (eg written/digital reports, essays, videos, images). In the unusual event that one of your assignments is misplaced, you will need to submit the backup copy. Any work you submit may be checked by electronic or other means for the purposes of detecting collusion and/or plagiarism.
When you are required to submit an assignment through your unit site (accessed in DeakinSync), you should 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 folder after upload, and check for, and keep, the email receipt for the submission.
– Summative assessment task 1
after 11.59 pm AEDT/AEST.
Individual problem solving task
Brief description of assessment task
This assessment task is for students to apply programming skills in crawling and cleaning data. Students will be required to demonstrate ability in data acquisition, representing data available in a variety of forms and apply descriptive statistics to make sense of data.
Detail of student output
This is an individual assessment task of maximum 15 pages including all relevant material, graphs, images and tables. Students will be required to provide responses for series of problem situations related to crawling, testing and manipulating data. They are also required to provide evidence through articulation of the scenario, application of programming skills, analysis techniques and provide a rationale for their response.
Grading and weighting
(% total mark for unit)
25%. This will be marked and graded.
This task assesses your achievement of these Unit Learning Outcome(s)
ULO1 – Demonstrate data acquisition, data representation and data pre-processing skills to describe, analyse and repurpose data from a variety of sources.
ULO2 – Apply critical thinking and statistical techniques to understand and visualize relationships in data
This task assesses your achievement of these Graduate Learning Outcome(s)
GLO1 – through the assessment of student ability to use data acquisition techniques to obtain, manipulate and represent data.
GLO3 – through student ability to use specific programming language and modules to obtain, clean and analyse data.
GLO4 – through assessment of student ability to make decisions to obtain data, use appropriate techniques to represent and visualise complex relationships in the data. GLO5 – through assessment of student ability to solve problems relates to ill- defined data.
How and when you will receive feedback on your work
Campus students will have the opportunity to seek regular feedback during practical sessions. Cloud students will have the opportunity to seek feedback on their progress during designated consultation sessions.
When and how to submit your work
This problem solving task is due in Week 5, Friday 16 April 2021, by 8:00 pm AEST via the unit site (accessed in DeakinSync).
– Summative assessment task 2
Group problem solving task
Brief description of assessment task
This assessment task is for students to develop and demonstrate knowledge of exploratory data analysis and prediction modelling.
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– Summative assessment task 3
Deakin University, Faculty of Science, Engineering and Built Environment SIT112 Data Science Concepts – Trimester 1, 2021
Students will be required to apply machine-learning techniques for data clustering and prediction. They will be tested on their teamwork skills, competency in applying suitable modelling techniques on a real-world scenario.
Detail of student output
This is a group assessment task. Students will be required to analyse a given real-world scenario and contribute to data analysis and predictive models.
The group response to problem solution should not exceed 30 pages. Students will be required to consolidate their individual solutions and propose best solution that evidences each group member’s contribution, relevant analyses and predictive models along with a rationale for the group’s response to solving the problem.
Grading and weighting
(% total mark for unit)
30% (20% for group solution, 10% for individual contribution). This will be marked and graded.
This task assesses your achievement of these Unit Learning Outcome(s)
ULO1 – Demonstrate data acquisition, data representation and data pre- processing skills to describe, analyse and repurpose data from a variety of sources.
ULO2 – Apply critical thinking and statistical techniques to understand and visualize relationships in data.
ULO3 – Apply machine-learning techniques in exploratory data analysis for problems related to commerce, industry and research.
ULO4 – Design and compute a statistical relationships in data including correlation and linear regression
ULO5 – Design and develop data-driven algorithms for outcome prediction.
This task assesses your achievement of these Graduate Learning Outcome(s)
GLO1 – through the assessment of student ability to use advanced data acquisition techniques to obtain, pre-process and prepare the data into suitable form for clustering and prediction.
GLO3 – through student ability to use specific programming language and modules to obtain, pre-process, transform and analyse data.
GLO4 – through assessment of student ability to make decisions to obtain data, use appropriate pre-processing techniques to probe and visualise complex relationships in the data.
GLO5 – through assessment of student ability to deal with ill-defined data and solve problems.
GLO7 – through the assessment of student ability to work in a group to solve problems relating to data analysis and predictive modelling.
How and when you will receive feedback on your work
Campus students will have the opportunity to seek regular feedback during classes and practical sessions. Cloud students will have the opportunity to seek feedback on their progress during designated consultation sessions. Students must reflect on feedback from previous assessment task for improvement.
When and how to submit your work
This problem solving task is due in Week 10, Friday 21 May 2021, by 8:00 pm AEST via the unit site (accessed in DeakinSync).
Quizzes
Brief description of assessment task
This assessment task will test student conception of key topics covered in the unit. Two MCQ tests at different points in time during the trimester will test student knowledge and progress.
Detail of student output
This is an individual assessment task. Students must complete the two quizzes within the stipulated time period.
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– Summative assessment task 4
Deakin University, Faculty of Science, Engineering and Built Environment SIT112 Data Science Concepts – Trimester 1, 2021
Grading and weighting
(% total mark for unit)
20% (10% each). This will be marked and graded.
This task assesses your achievement of these Unit Learning Outcome(s)
ULO2 – Apply machine-learning techniques in exploratory data analysis for problems related to commerce, industry and research.
ULO4 – Design and compute statistical relationships in data including correlation and linear regression.
This task assesses your achievement of these Graduate Learning Outcome(s)
GLO1 – through the assessment of student ability to apply fundamental knowledge in the field of data science, big data, and the ability to manipulate large datasets.
How and when you will receive feedback on your work
MCQ quizzes test student progress with learning key concepts in the unit. Students will have the opportunity to seek feedback during practical sessions leading up to the test.
When and how to submit your work
Quiz will be available for student response via the unit site (accessed in DeakinSync) in Week 4, Thursday 1 April 2021, by 8:00 pm AEDT and Week 9, Friday 14 May, by 8:00 pm AEST
Examination (online)
Brief description of assessment task
The examination will assess and validate student knowledge of and ability to apply critical thinking techniques to identify and analyse problems from technical and non-technical perspectives. Questions will be based on the topics covered in class during the entire trimester of study.
Detail of student output
Students are required to undertake a 2-hour timed online examination. The examination will usually comprise of short answer, long answer and multiple- choice questions, which will require the student to respond in writing.
Grading and weighting
(% total mark for unit)
25%
This task assesses your achievement of these Unit Learning Outcome(s)
ULO1 – Demonstrate data acquisition, data representation and data pre- processing skills to describe, analyse and repurpose data from a variety of sources
ULO2 – Apply critical thinking and statistical techniques to understand and visualize relationships in data
ULO3 – Apply machine-learning techniques in exploratory data analysis for problems related to commerce, industry and research.
ULO4 – Design and compute a statistical relationships in data including correlation and linear regression
This task assesses your achievement of these Graduate Learning Outcome(s)
GLO1, 2, 4, 5 – through the assessment of student knowledge and ability to apply fundamental data processing techniques to real-world data and communicate the results.
GLO5 – through assessment of student ability to deal with defined data sets, and solve problems.
How and when you will receive feedback on your work
Deakin University will release the final assessment results at the stipulated timeframe. Students will receive a mark, which is an indicator of their overall performance in this unit of study.
When and how to submit your work
Students will be required to undertake a timed online assessment during the examination period. It is the responsibility of students to review their examination timetable when it is released via DeakinSync.
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Deakin University, Faculty of Science, Engineering and Built Environment SIT112 Data Science Concepts – Trimester 1, 2021
Your learning experiences in this Unit – and your expected commitment
To be successful in this unit, you must:
• Read all materials in preparation for your classes or seminars, and follow up each with further study and research on the topic;
• Start your assessment tasks well ahead of the due date;
• Read or listen to all feedback carefully, and use it in your future work;
• Attend and engage in all timetabled learning experiences as follows:
Scheduled learning activities – campus
1 x 2 hour class per week, 1 x 2 hour practical per week.
Scheduled learning activities – cloud
1 x 1 hour scheduled online workshop per week.
Note (on-campus learning activities)
Teaching will be delivered in line with the COVIDSafe health guidelines. All classes will be delivered online but other activities may include a combination of online and on-campus activities. Please refer to the details provided below, and check your unit site for announcements and updates.
Activities that are scheduled to run on-campus are:
• Weekly 2 hour practicals
Please refer to the unit site for more details.
Students will on average spend 150 hours over the trimester undertaking the learning and assessment activities for this unit. For campus students this includes class time as described, designated activities in the practical sessions, assessment tasks, readings and study time. For cloud students the time should be divided between online learning activities, discussion boards, designated activities in the practical sessions, assessment tasks, readings and study time.
There are many resources available to you undertaking a study in this unit. Learning opportunities in this unit are offered via classes, practical session and the unit site. Students should begin by reading the unit information, intended unit learning outcomes and assessment activities. Class notes and reading materials provide an overview of the content for each week. Students should review this information for engaging in discussions during classes, practical sessions and consultation sessions.
Students should also conduct further research by examining information on the web, supplementary material in recommended reading and textbooks. Attend classes and designated consultation sessions regularly will enable students to focus on key concepts and engage in discussions with the teaching staff. Class recordings will also be available for review via the unit site. Students must participate in CloudDeakin discussion forums and engage in learning with other students, monitor the forum and respond regularly and appropriately.
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At Deakin,
Deakin University, Faculty of Science, Engineering and Built Environment SIT112 Data Science Concepts – Trimester 1, 2021
Note
• Lectures are referred to as classes (definition: a general meeting for all students, for which students do not need to register and where students are engaged through presentations and learning activities)
• Tutorials, workshops and seminars are referred to as seminars (definition: more interactive meetings for smaller groups of students).
• For the complete list of agreed definitions for learning experiences, see the Course Design and Delivery Procedure.
UNIT LEARNING RESOURCES
Your unit learning resources are available in your unit site accessed in DeakinSync.
The texts and reading list for the unit can be found on the University Library via the link below: SIT112 Note: Select the relevant trimester reading list. Please note that a future teaching period’s reading list may not be available until a month prior to the start of that teaching period so you may wish to use the relevant trimester’s prior year reading list as a guide only.
Essential learning resources
There is no prescribed textbook for this unit.
Recommended learning resources
Due to the interdisciplinary nature of data science, the following books will be recommended for additional readings:
• Data Science from Scratch: First Principles with Python, Joel Grus, O’Reilly Media, 2015. This is an introductory textbook for beginners in data science.
• Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython, Wes McKinney, O’Reilly Media, 2nd edition, 2017. A more practical book for those who want to leverage Python for realistic data science projects. Written by Wes McKinney, the creator of the Python pandas package .
Textbooks, reference books, general books and software may be ordered from the bookshop:
• phone 1800 686 681 (freecall);
• email to DUSA-Bookshop@deakin.edu.au; or
• order online from the University bookshop web site at http://www.dusabookshop.com.au/
KEY DATES FOR THIS TRIMESTER
Trimester begins (classes begin)
Intra-trimester break (a short break during trimester)
Trimester ends (classes cease)
Study period (examination preparation period)
Examinations begin
Examinations end
Monday 8 March 2021
Friday 2 April – Sunday 11 April 2021
Friday 28 May 2021
Monday 31 May – Friday 4 June 2021
Monday 7 June 2021
Friday 18 June 2021
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Deakin University, Faculty of Science, Engineering and Built Environment SIT112 Data Science Concepts – Trimester 1, 2021
Inter-trimester break (the period between trimesters) Monday 21 June – Friday 9 July 2021 Unit results released Thursday 8 July 2021 (6pm)
UNIT WEEKLY ACTIVITIES
Week
Commencing
Topic
Assessment activity
1#
8 March 2021
Introduction to Data Science
2
15 March
Data manipulation: Getting data
3
22 March
Representing Data
4^
29 March
Analytics: Understanding data
Online quiz
5
12 April
Analytics: Finding Dependency
Assignment 1 – Individual problem solving task
6
19 April
Analytics: Machine Learning
7*
26 April
Exploratory Data Analysis
8
3 May
Build prediction models I
9
10 May
Build prediction models II
Online quiz
10
17 May
Model evaluation and testing
Assignment 2 – Group problem
11
24 May
Revision
#Victorian Labour Day public holiday: Monday 8 March – University open
^Easter vacation/intra-trimester break: Friday 2 April – Sunday 11 April 2021 (between weeks 4 and 5) *ANZAC Day observed, Monday 26 April (in lieu of 25 April) – University closed
19 February 2021
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