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Data Science Studio 1

Undergraduate | UNE-COSC102 | 2024

Study method
100% online
Assessments
100% online
Enrol by
16 June 2024
Entry requirements
Part of a degree
Duration
16 weeks
Start dates
24 June 2024

Price from

$2,239

Upfront cost

$0

FEE-HELP available

Data Science Studio 1

About this subject

  • Upon completion of this subject, students will be able to:

    1. explain the concepts behind introductory machine learning algorithms for classification and clustering;
    2. apply machine learning libraries and toolkits to explore datasets and discover knowledge;
    3. visualise the output of machine learning algorithms and describe their meaning;
    4. select appropriate techniques to clean and analyse data; and
    5. explain and consider ethical issues in data science.

Entry requirements

Part of a degree

To enrol in this subject you must be accepted into one of the following degrees:

Elective

  • UNE-INF-DIP-2024 - Diploma in Information Technology

Prior study

You must either have successfully completed the following subject(s) before starting this subject, or enrol in the following subject(s) to study at the same time or prior to this subject:

Additional requirements

  • Equipment requirements - Headphones or speakers (required to listen to lectures and other media). Headset, including microphone (highly recommended). Webcam (may be required for participation in virtual classrooms and/or media presentations).
  • Software requirements - It is essential for students to have reliable internet access in order to participate in and complete your units, regardless of whether they contain an on campus attendance or intensive school component. For additional information please visit UNE Hardware Requirements: https://www.une.edu.au/current-students/support/it-services/hardware
  • Other requirements -

    Textbook requirements:
    Textbook information is not available until approximately 8 weeks prior to the commencement of the Teaching period.
    Students are expected to purchase prescribed material.
    Textbook requirements may vary from one teaching period to the next.

Study load

0.125 EFTSL
This is in the range of 10 to 12 hours of study each week.

Equivalent full time study load (EFTSL) is one way to calculate your study load. One (1.0) EFTSL is equivalent to a full-time study load for one year.

Find out more information on Commonwealth Loans to understand what this means to your eligibility for financial support.

Related degrees

Once you’ve completed this subject it can be credited towards one of the following courses

University of New England logo

UndergraduateUNE-INF-DIP

Diploma in Information Technology

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