This unit looks at processes and case studies to understand the many facets of working with data, and the significant effort in Data Science over and above the core task of Data Analysis. Working with data as part of a business model and the lifecycle in an organisation is considered, as well as business processes and case studies. Data and its handling is also introduced: characteristic kinds of data and its collection, data storage and basic kinds of data preparation, data cleaning and data stream processing. Curation and management are reviewed: archival and architectural practice, policy, legal and ethical issues. Styles of data analysis and outcomes of successful data exploration and analysis are reviewed. Standards, tools and resources are also reviewed.
Minimum total expected workload equals 144 hours per semester comprising:
Online students generally do not attend lecture, tutorial and laboratory sessions, however should plan to spend equivalent time working through resources and participating in discussions.
See also Unit timetable information
(FIT5131 or FIT9131) and (FIT5132 or FIT9132) or equivalent
Wray Buntine
Consultation hours: Wed 10-12
Monash is committed to excellence in education and regularly seeks feedback from students, employers and staff. One of the key formal ways students have to provide feedback is through the Student Evaluation of Teaching and Units (SETU) survey. The University’s student evaluation policy requires that every unit is evaluated each year. Students are strongly encouraged to complete the surveys. The feedback is anonymous and provides the Faculty with evidence of aspects that students are satisfied and areas for improvement.
For more information on Monash’s educational strategy, see:
www.monash.edu.au/about/monash-directions/ and on student evaluations, see: www.policy.monash.edu/policy-bank/academic/education/quality/student-evaluation-policy.html
| Week | Activities | Assessment |
|---|---|---|
| 0 | No formal assessment or activities are undertaken in week 0 | |
| 1 | Overview of data science and what a project looks like. | |
| 2 | Roles of a data scientist, and the impact of the field. | |
| 3 | Review of Python. Data business models. | |
| 4 | Application areas and case studies. | |
| 5 | Characterising data and "big" data. | |
| 6 | Data sources and case studies. | Test 1. |
| 7 | More Python, regular expressions. Resources and standards. | |
| 8 | Resources case studies. | |
| 9 | Data analysis theory. | |
| 10 | Data analysis process. | Test 2. |
| 11 | Issues in data management. | Assignment 3 part 1 due. |
| 12 | Data management frameworks. | Assignment 1, Assignment 2, Assignment 3 part 2 due. |
| SWOT VAC | No formal assessment is undertaken during SWOT VAC | |
| Examination period | LINK to Assessment Policy: http://policy.monash.edu.au/policy-bank/ academic/education/assessment/ assessment-in-coursework-policy.html |
*Unit Schedule details will be maintained and communicated to you via your learning system.
In-semester assessment: 100%
| Assessment Task | Value | Due Date |
|---|---|---|
| Assignment 1: Data Science and me. | 10% | Friday Week 12 |
| Assignment 2: Data Science Resources | 20% | Friday Week 12 |
| Assignment 3: Business and data case study | 40%+10% | Friday Week 11 + Friday Week 12 |
| Test 1: size and scope of data storage and data processing, and their technologies | 10% | Friday Week 6 |
| Test 2: kinds of data analysis and statistical methods | 10% | Friday Week 10 |
Faculty Policy - Unit Assessment Hurdles (http://intranet.monash.edu.au/infotech/resources/staff/edgov/policies/assessment-examinations/assessment-hurdles.html)
Academic Integrity - Please see resources and tutorials at http://www.monash.edu/library/skills/resources/tutorials/academic-integrity/
The completed journal will be assessed on your ability to:
Classify roles in data science project such as statistician, archivist, analyst and systems architect
The report will be assessed on demonstration of:
Classifying the kinds of data analysis and statistical methods available for a data science project.
Identifying and assessing resources, software and tools for a data science project.
The report and video will be assessed on the demonstration and knowledge of unit outcomes. The peer review will be assessed on the analysis of same.
Correctness.
Correctness.
Monash Library Unit Reading List (if applicable to the unit)
http://readinglists.lib.monash.edu/index.html
Types of feedback you can expect to receive in this unit are:
Submission must be made by the due date otherwise penalties will be enforced.
You must negotiate any extensions formally with your campus unit leader via the in-semester special consideration process: http://www.monash.edu.au/exams/special-consideration.html
It is a University requirement (http://www.policy.monash.edu/policy-bank/academic/education/conduct/student-academic-integrity-managing-plagiarism-collusion-procedures.html) for students to submit an assignment coversheet for each assessment item. Faculty Assignment coversheets can be found at http://www.infotech.monash.edu.au/resources/student/forms/. Please check with your Lecturer on the submission method for your assignment coversheet (e.g. attach a file to the online assignment submission, hand-in a hard copy, or use an electronic submission). Please note that it is your responsibility to retain copies of your assessments.
Students must regularly check Moodle for announcements. Video, audio, PDF and ePUBs for unit material will be made available through Moodle so access to a laptop or similar to view the material is necessary. Some workk will be done in the language Python so you must have access to a machine running Python with appropriate libraries.
Monash has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and to provide advice on how they might uphold them. You can find Monash’s Education Policies at: www.policy.monash.edu.au/policy-bank/academic/education/index.html
Important student resources including Faculty policies are located at http://intranet.monash.edu.au/infotech/resources/students/
The University provides many different kinds of support services for you. Contact your tutor if you need advice and see the range of services available at http://www.monash.edu.au/students. For Malaysia see http://www.monash.edu.my/Student-services, and for South Africa see http://www.monash.ac.za/current/.
The Monash University Library provides a range of services, resources and programs that enable you to save time and be more effective in your learning and research. Go to www.lib.monash.edu.au or the library tab in my.monash portal for more information. At Malaysia, visit the Library and Learning Commons at http://www.lib.monash.edu.my/. At South Africa visit http://www.lib.monash.ac.za/.