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 during the session. 

Hurdle tasks

The final examination is a hurdle requirement. You must obtain a mark of at least 40% in the final exam to be eligible to pass the unit. 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. 

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. 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 one week 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, 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

The non-examination assessment components should be submitted via iLearn by the due date and time.

The penalty for late submission is deduction of 5% of the possible mark for that item for each 24 hour period (or part) overdue. Assessments will not be accepted for marking if submitted more than 1 week past the due date.  Extensions to the due dates for assignments,  practical assessments, and project will only be considered if requested with valid reason prior to the due date.

Students anticipating or experiencing difficulties in meeting a deadline should discuss this with one of the lecturers in the first instance, ideally ahead of the deadline, if at all possible. Students should also be familiar with the University's provisions for Special Considerations.

Your lecturers in this course are Matt Owers, Cormac Purcell, and Christian Schwab. Each week, there will be 2 hours of face-to-face lectures, as well as one hour of lectorial-type demonstrations.  The lectures will cover astronomy content related to the Milky Way galaxy (Matt Owers) and extra-solar planets (Christian Schwab), while the lectorials will cover techniques used to extract information from datasets (Cormac Purcell).

The lab sessions run from Week 4-12 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 4.

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.

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