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	Critical analysis
Brief description of assessment task	This is an individual assessment task based on the understanding of Data Science, Big Data and their applications.
Detail of student output	This assessment contains a written report on the specified topic or application scenario. It is an individual task. It is based on topics presented during Weeks 1 to 4.
Grading and weighting (% total mark for unit)	25% marked and graded.
This task assesses your achievement of these Unit Learning Outcome(s)	ULO1- Develop knowledge of and discuss new and emerging fields in data science. ULO2- Describe advanced constituents and underlying theoretical foundation of data science. ULO3- Evaluate modern data analytics and its implication in real-world applications.
This task assesses your achievement of these Graduate Learning Outcome(s)	GLO 3 - Digital literacy. GLO 5 - Explaining problem solving techniques. GLO 6 - Meeting deadlines. GLO 8 - Global citizenship.
How and when you will receive feedback on your work	Students will be provided with feedback and directing students to areas that require improvements.
When and how to submit your work	Students are required to submit problem solutions via the unit site (accessed in DeakinSync) by 11.59pm AEST, Saturday 11 April 2020 (Week 5).

Summative assessment task 2

	Project
Brief description of assessment task	This is a small group project where students will be expected to work in teams of three. More detailed information about this assessment task will be provided in the unit site.
Detail of student output	Students are required to submit a project report that comprises data collection, data analysis and programming details, together with the project implementation.
Grading and weighting (% total mark for unit)	40% marked and graded.
This task assesses your achievement of these Unit Learning Outcome(s)	ULO3 - Evaluate modern data analytics and its implication in real-world applications. ULO4 – Use appropriate platform to collect and process relatively large datasets. ULO5 - Collect, model and conduct inferential as well predictive tasks from data.
This task assesses your achievement of these Graduate Learning Outcome(s)	GLO 1, 2 , 4, 5 - Designing and developing algorithms using IT standards. GLO5 - Explaining problem solving techniques. GLO6 - Meeting deadlines.
How and when you will receive feedback on your work	Students will be provided with feedback and will also be directed to areas that require improvements.

When and how to submit your work

Students are required to submit problem solutions via the unit site (accessed in DeakinSync) by 11.59pm AEST, Saturday 23 May 2020 (Week 10).

Summative assessment task 3

	Quiz (online)
Brief description of assessment task	Students will be required to complete one online quiz, and will be given one hour to complete the quiz.
Detail of student output	The online quiz will comprise of multiple choice questions (MCQ) and the like, and will be based on topics presented in the classes and practical programming exercises.
Grading and weighting (% total mark for unit)	5% marked and graded
This task assesses your achievement of these Unit Learning Outcome(s)	ULO1- Develop knowledge of and discuss new and emerging fields in data science. ULO2- Describe advanced constituents and underlying theoretical foundation of data science. ULO4 – Use appropriate platform to collect and process relatively large datasets.
This task assesses your achievement of these Graduate Learning Outcome(s)	GLO5 - Explaining problem solving techniques. GLO6 - Meeting deadlines.
How and when you will receive feedback on your work	Students will be provided with immediate online feedback and will also be directed to areas that require improvements.
When and how to submit your work	The online quiz will be open on Monday 18 May 2020 (week 10), and you will have only one chance to attempt the quiz.

Summative assessment task 4

	Examination
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 a range of topics covered in class during Weeks 1 to 10.
Detail of student output	Students are required to sit the 2-hour closed book examination under supervised conditions. 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)	30%

This task assesses your achievement of these Unit Learning Outcome(s)	ULO 1- Develop knowledge of and discuss new and emerging fields in data science. ULO2- Describe advanced constituents and underlying theoretical foundation of data science. ULO3- Evaluate modern data analytics and its implication in real-world applications. ULO4 – Use appropriate platform to collect and process relatively large datasets. ULO5 - Collect, model and conduct inferential as well predictive tasks from data.
This task assesses your achievement of these Graduate Learning Outcome(s)	GLO 1, 2, 4, 5 - The examination will at a minimum cover argument types, symbolic logic and developing an algorithm. GLO6 - Meeting deadlines.
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 attend a supervised examination during the end of trimester examination period. It is the responsibility of students to review their examination timetable when it is released via DeakinSync.

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: