• Weekly Python and shell tasks: The material in the GrokLearning platform includes tasks where the student must write a Python program or shell task to produce precisely described output. The program will be graded automatically. These are started in tutorial, and completed in students own time. If special consideration is approved, the appropriate consideration should be “mark adjustment” based on estimating a mark from that on other tasks or final exam.
• Weekly quizzes: Each quiz consists of multiple-choice questions related to the lecture content from the previous week. Done in students own time. If special consideration is approved, the appropriate consideration should be “mark adjustment” based on estimating a mark from that on other tasks or final exam.
• Practice Python coding test: Held during scheduled tutorial sessions. Each student will be required to produce Python code that calculates precisely described output from data in a file. This carries no weight in final grade, but is intended to accustom students to the setting in preparation for the later coding test. If special consideration is approved, the appropriate consideration is “no action” as this is unweighted and purely formative.
• Python coding test: Held during scheduled tutorial sessions. Each student will be required to produce Python code that calculates precisely described output from data in a file. If special consideration is approved, the appropriate consideration should be “new or varied assessment”.
• Draft project stage 1. This carries no weight in final grade, but allows feedback from tutors or peers. If special consideration is approved, the appropriate consideration is “no action” as this is unweighted and purely formative.
• Project Stage 1: This is the first part of a group project (the students in a group should all be attending the same scheduled lab session). This stage involves finding data from a domain of interest for the students, data cleaning and importing to a tool, and doing a very simple analysis from some of the data. A report is required that describes the dataset, how it was obtained, and how it was processed by the tool. If this stage is missed or badly done, the group can be given a clean data set, for a domain chosen by the instructor, to use in the rest of the project. It is crucial that each group manages its internal working effectively, and use mechanisms to detect problems and report them to the coordinator early. If special consideration is approved, the appropriate consideration should be “extension of time”.
• Draft project stage 2. This carries no weight in final grade, but allows feedback from tutors or peers. If special consideration is approved, the appropriate consideration is “no action” as this is unweighted and purely formative.
• Project Stage 2: The group will use computational tools to explore the data, and report on both what was done and what was found (using appropriate summaries and charts). It is crucial that each group manages its internal working effectively, and use mechanisms to detect problems and report them to the coordinator early. If special consideration is approved, the appropriate consideration should be “extension of time”.
• Draft project stage 3. This carries no weight in final grade, but allows feedback from tutors or peers. If special consideration is approved, the appropriate consideration is “no action” as this is unweighted and purely formative.
• Project Stage 3: The group will use computational tools to produce a predictive model for some aspect of the data, and evaluate this model; deliverable is a report on both what was done and what was found. It is crucial that each group manages its internal working effectively, and use mechanisms to detect problems and report them to the coordinator early. If special consideration is approved, the appropriate consideration should be “extension of time”.
• Draft project stage 4. This carries no weight in final grade, but allows feedback from tutors or peers.
• Project Stage 4: The group will use computational tools to produce an interactive visualisation for some aspect of the data; deliverable is a report on what was done and a system that provides the interaction. It is crucial that each group manages its internal working effectively, and use mechanisms to detect problems and report them to the coordinator early. If special consideration is approved, the appropriate consideration should be “extension of time”. If special consideration is approved, the appropriate consideration is “no action” as this is unweighted and purely formative.
• Practice final exam: In 3 hrs in students own time, produce and upload a document with answers to a set of questions covering conceptual content, skills, and experiences. This carries no weight in final grade, but is intended to accustom students to the setting in preparation for the later final exam. If special consideration is approved, the appropriate consideration is “no action” as this is unweighted and purely formative.
• Exam: A written exam, covering conceptual content, skills, and experiences. Some of the questions are common with data1002 final exam, and some are distinct on the additional topics covered. If special consideration is approved, the appropriate consideration is “replacement exam”.
• Oral exam barrier: a short online conversation with tutor or lecturer, for student to demonstrate knowledge of the main factual content, in a situation where identity can be checked (eg by sighting a student card). This carries no weight in final grade, but satisfactory performance is a barrier required to Pass the unit. If special consideration is approved, the appropriate consideration is “new or varied assessment”.

Detailed information for each assessment can be found on Canvas.

Minimum requirement: To Pass thius unit, a student must achieve an overall mark of at least 50, and also, they must have satisfactory performance in the hurdle task “oral exam barrier”.