Unit workload

The 'estimated time on task' for each assessment item is an estimate of the additional time needed to complete each assessment outside of all scheduled learning activities. These estimates assume that you actively engage with all scheduled learning activities and spend an additional 12 hours of self-led study over the course of the session.

Requirements to Pass this Unit

To pass this unit you must achieve a total mark equal to or greater than 50%, and obtain a mark of at least 40% in the final exam, which is a hurdle assessment. If your mark in the final examination is between 30% and 39% inclusive, you may be a given a second and final chance to attain the required level of performance; the mark awarded for the second exam towards your final unit mark will be capped at 40%, and you will be allowed to sit the second exam only if this mark would be sufficient to pass the unit overall. The final exam is set as a hurdle task in order to ensure that Unit Learning Outcomes 1 and 2 are fulfilled by the student.

Supplementary examinations

If you receive special consideration for the final exam, a supplementary exam will be scheduled after the end of the normal exam period, typically about 3 to 4 weeks after the normal exam period. By making a special consideration application for the final exam you are declaring yourself available for a resit during the supplementary examination period and will not be eligible for a second special consideration approval based on pre-existing commitments. Please ensure you are familiar with the policy prior to submitting an application. Approved applicants will receive an individual notification prior to the exam with the exact date and time of their supplementary examination.

If you are given a second opportunity to sit the final examination as a result of failing to meet the minimum mark required by the hurdle, you will be offered that chance during the same supplementary examination period and will be notified of the exact day and time after the publication of final results for the unit.

Late Assessment Policy

Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark of the task) will be applied for each day a written report or presentation assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a grade of ‘0’ will be awarded even if the assessment is submitted. The submission time for all uploaded assessments is 11:55 pm. A 1-hour grace period will be provided to students who experience a technical concern.

For any late submission of time-sensitive tasks, such as scheduled tests/exams, performance assessments/presentations, and/or scheduled practical assessments/labs, please apply for Special Consideration.

Assessments where Late Submissions will be accepted

• Lab Reports - YES, Standard Late Penalty applies

• Problem Sets - YES, Standard Late Penalty applies

Special Consideration

The Special Consideration Policy aims to support students who have been impacted by short-term circumstances or events that are serious, unavoidable and significantly disruptive, and which may affect their performance in assessment. If you experience circumstances or events that affect your ability to complete the assessments in this unit on time, please inform the convenor and submit a Special Consideration request through Service Connect.

Your lecturers in this course are Andrew Hopkins and Gabriella Quattropani. Each week, there will be 2 hours of lectures that will be delivered on-campus. There will also be a one hour of lectorial-type demonstration delivered on-campus. The 2 hours of lectures will cover astronomy content related to the Milky Way galaxy, while the one hour lectorials will cover techniques used to extract information from datasets (Gabriella Quattropani). Both will begin in Week 1 of the session, and in-person attendance is essential for success in this unit.

The lab sessions run from Week 3-12 on-campus in the Physics and Astronomy computer lab, and will involve a series of computer labs completed using Python Notebooks within the Google Colab environment. Note that labs start in Week 3. Andrew Hopkins and Gabriella Quattropani will be your lab demonstrators. Again, in-person attendance is essential for success the labs.

Resources will be provided on iLearn. There is no required text, although the Milky Way Galaxy component will primarily draw content from the book "Galaxies in the Universe: An Introduction" 2nd Ed. by Sparke and Gallagher, supplemented by material from "An Introduction to Modern Astrophysics" 2nd Ed. by Carroll and Ostlie and "Galactic Astronomy" by Binney and Merrifield. Useful resources for the data science part of the course are the books "Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data" by Ivezic et al. and "Hands-On Machine Learning with Scikit-Learn, Keras, and Tensorflow" by Geron.

Methods of Communication

Communication will be via your university email or through announcements on iLearn. General queries regarding assessments and lecture or lab content should be placed on the iLearn discussion board. Queries of a more personal nature can be sent to the convenor (andrew.hopkins@mq.edu.au) from your university email address.

N.B. This schedule is flexible and subject to change.