DATA1002: Informatics: Data and Computation

• Early feedback task: A simple MCQ covering the first 3 weeks of content to help students aware of the progress and knowledge understanding, so that students can make plan and decision to study this unit of study.

  • Late work and simple extension are not accepted for these assessments. 
  • When special consideration is approved for a task, the appropriate consideration should be “mark adjustment” based on estimating a grade using the average from other tasks or the final exam.
• Weekly coding tasks: Tasks where the student must write a Python program to produce precisely described output. The program will be run automatically against test cases. Grade is based on participation. These are started in tutorial, and completed in students’ own time.
  • Late work and simple extension are not accepted for these assessments. 
  • When special consideration is approved for a task, the appropriate consideration should be “mark adjustment” based on estimating a grade using the average from other tasks or the final exam.
• Practice Python coding test: Done in student’s own time. There are several tasks in the test. For some of tasks, the student must extend a Python code skeleton, for others, the student must develop the code from scratch. The aims are the same, i.e. to calculate precisely described output from data in a file. Each task is graded automatically, by comparing the output produced on several different inputs to what is described. This carries no weight in final grade, but is intended to accustom students to the setting in preparation for the later coding test, and to trigger remedial learning for any student who does not succeed in the practice.
  • Late work is not accepted for this assessment. 
  • When special consideration is approved, the appropriate consideration should be “No action”.
• Python coding test: Held during your lab session. There are several tasks in the test. For some of tasks, the student must extend a Python code skeleton, for others, the student must develop the code from scratch. The aims are the same, i.e. to calculate precisely described output from data in a file. Each task is graded automatically, by comparing the output produced on several different inputs to what is described.
  • Late work and simple extension are not accepted for these assessments. 
  • When special consideration is approved for a task, the appropriate consideration should be “mark adjustment” where this 10% will be added to your exam, i.e. your exam will carry 60% of the total mark.
• Project Stage 1: This is the first part of a group project (the students in a group must 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. The group will also use computational tools to explore the data, and report on both what was done and what was found (using appropriate summaries and charts). A report is required. It is crucial that each group manages its internal working effectively, and use mechanisms to detect problems and report them to the coordinator early.
  • Late work and simple extesnsion not accepted for these assessments. 
  • When special consideration is approved, the appropriate consideration should be “extension of time”.
• Project Stage 2: The group will use computational tools to produce a predictive model for some aspect of the data, and evaluate this model; deliverable is a presentation 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.
  • Late work and simple extesnsion not accepted for these assessments. 
  • When special consideration is approved, the appropriate consideration should be “submission of a 5min video of the student's part on C1 and C2 for Stage 2 of the project”.
• Exam: The exam contains multiple-choice and essay questions. Covering knowledge, conceptual content, skills, and experiences.
  • Late work and simple extesnsion are not accepted for these assessments. 
  • When special consideration is approved, the appropriate action should be “replacement exam”.

Detailed information for each assessment can be found on Canvas.

Minimum requirement: It is a double-pass policy of the School of Computer Science that in order to pass this unit, a student must achieve at least 40% in the written examination. For subjects without a final exam, the 40% minimum requirement applies to the corresponding major assessment component specified by the lecturer. A student must also achieve an overall final mark of 50 or more. Any student not meeting these requirements may be given a maximum final mark of no more than 45 regardless of their average.