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CSC3501 Principles of Data Science and Visualisation

Semester 2, 2021 On-campus Toowoomba
Short Description: Principles Data Science&Visual
Units : 1
Faculty or Section : Faculty of Health, Engineering and Sciences
School or Department : School of Sciences
Student contribution band : Band 2
ASCED code : 020199 - Computer Science not elsewhere
Grading basis : Graded
Version produced : 21 July 2021


Examiner: Zhaohui Tang


Pre-requisite: STA3200

Other requisites

Requisite: knowledge of computing consistent with CSC1401 Foundation Programming


Government, private enterprise and science have always been data-driven, what is changing dramatically is the sheer amount of data now generated. Data Science, sometimes also referred to as Big Data, is a rapidly evolving field which studies how to organize, analyse and communicate relevant data through appropriate data visualisations as well as written and oral communications. While data science’s technical foundations arise from Mathematics, Statistics and Computer Science, the area is fundamentally both multi and interdisciplinary. It is most often performed in collaborations across disciplines to bring together the necessary skills and relevant application knowledge. Those with a technical background related to data science need an understanding of the data relevant to the particular problem application area. Those with expertise in the application area must acquire the relevant technical knowledge in order to effectively and accurately make use of data science tools and methodologies.


This course covers the fundamental principles of data science concepts and introduces the student to some of its common tools, methodologies and visualisations. Students will learn how to extract knowledge from data through hands-on experience with common data science programming tools and methodologies. They will create data visualisations to conduct exploratory and confirmatory data analysis. And will gain an appreciation of the breadth of data science applications and their potential value across disciplines.


On successful completion of this course students should be able to:

  1. differentiate between common data science algorithms and identify their appropriate application.
  2. create a reproducible data science project report which includes: all relevant data files, data processing code, visualisations, analyses, reasoning and conclusions.
  3. evaluate a data science problem and apply the appropriate data analyses and problem-solving skills for the successful completion of the data science project.
  4. plan and execute a data science project.


Description Weighting(%)
1. Basic data science algorithms and their applications, such as recommender systems, online advertising, and others depending on selected case studies 20.00
2. Common tools for programming, development and data management 20.00
3. Creating data visualisations for exploratory and confirmatory analysis 20.00
4. Data wrangling 15.00
5. Creating and presenting visualisation models 15.00
6. Mining text from the social web 5.00
7. ethics and data visualization: avoiding misleading graphs 5.00

Text and materials required to be purchased or accessed

ALL textbooks and materials available to be purchased can be sourced from USQ's Online Bookshop (unless otherwise stated). (

Please contact us for alternative purchase options from USQ Bookshop. (

Cairo, A 2016, The Truthful Art, New RIders.
VanderPlas, J 2016, Python Data Science Handbook, O'Reilly Media.

Reference materials

Reference materials are materials that, if accessed by students, may improve their knowledge and understanding of the material in the course and enrich their learning experience.
VanderPlas, J 2016, A Whirlwind Tour of Python, O'Reilly Media.
(available from

Student workload expectations

Activity Hours
Assessments 58.00
Private Study 60.00
Workshops 52.00

Assessment details

Description Marks out of Wtg (%) Due Date Objectives Assessed Notes
Assignment 1 100 20 24 Aug 2021 1,2,3
Assignment 2 100 30 05 Oct 2021 1,2,3,4
Open Examination - Online 100 50 End S2 1,2,3 (see note 1)

  1. This will be an online exam. Students will be provided further instruction regarding the exam by their course examiner via StudyDesk. The examination date will be available via UConnect when the Alternate Assessment Schedule has been released.

Important assessment information

  1. Attendance requirements:
    It is the students' responsibility to attend and participate appropriately in all activities (such as lectures and tutorials) scheduled for them, and to study all material provided to them or required to be accessed by them to maximise their chance of meeting the objectives of the course and to be informed of course-related activities and administration.

  2. Requirements for students to complete each assessment item satisfactorily:
    To satisfactorily complete an individual assessment item a student must achieve at least 50% of the marks for that item.

  3. Penalties for late submission of required work:
    Students should refer to the Assessment Procedure (point 4.2.4).

  4. Requirements for student to be awarded a passing grade in the course:
    To be assured of receiving a passing grade a student must obtain at least 50% of the total weighted marks available for the course (i.e. the Primary Hurdle), and have satisfied the Secondary Hurdle (Supervised), i.e. the end of semester examination by achieving at least 40% of the weighted marks available for that assessment item.

    Supplementary assessment may be offered where a student has undertaken all of the required summative assessment items and has passed the Primary Hurdle but failed to satisfy the Secondary Hurdle (Supervised), or has satisfied the Secondary Hurdle (Supervised) but failed to achieve a passing Final Grade by 5% or less of the total weighted Marks.

    To be awarded a passing grade for a supplementary assessment item (if applicable), a student must achieve at least 50% of the available marks for the supplementary assessment item as per the Assessment Procedure (point 4.4.2).

  5. Method used to combine assessment results to attain final grade:
    The final grades for students will be assigned on the basis of the aggregate of the weighted marks obtained for each of the summative items for the course.

  6. Examination information:
    An Online Examination is one in which candidates may have access to any printed, written, or online material as well as a calculator.

  7. Examination period when Deferred/Supplementary examinations will be held:
    Deferred and Supplementary examinations will be held in accordance with the Assessment Procedure

  8. University Student Policies:
    Students should read the USQ policies: Definitions, Assessment and Student Academic Misconduct to avoid actions which might contravene University policies and practices. These policies can be found at

Assessment notes

  1. Students must familiarise themselves with the USQ Assessment Procedures (

  2. Referencing in Assignments must comply with the Harvard (AGPS) referencing system. This system should be used by students to format details of the information sources they have cited in their work. The Harvard (APGS) style to be used is defined by the USQ library’s referencing guide. These policies can be found at

Evaluation and benchmarking

In meeting the University’s aims to establish quality learning and teaching for all programs, this course monitors and ensures quality assurance and improvements in at least two ways. This course:
1. conforms to the USQ Policy on Evaluation of Teaching, Courses and Programs to ensure ongoing monitoring and systematic improvement.
2. forms part of the BITC and is benchmarked against the internal USQ accreditation/reaccreditation processes which include (i) stringent standards in the independent accreditation of its academic programs, (ii) close integration between business and academic planning, and (iii) regular and rigorous review.

Other requirements

  1. Computer, e-mail and Internet access:
    Students are required to have access to a personal computer, e-mail capabilities and Internet access to UConnect. Current details of computer requirements can be found at

  2. Students can expect that questions in assessment items in this course may draw upon knowledge and skills that they can reasonably be expected to have acquired before enrolling in this course. This includes knowledge contained in pre-requisite courses and appropriate communication, information literacy, analytical, critical thinking, problem solving or numeracy skills. Students who do not possess such knowledge and skills should not expect the same grades as those students who do possess them.

Date printed 21 July 2021