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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:
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