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FIT2103 Introduction to programming for data science - DISESTABLISHED

Chief Examiner

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Unit Code, Name, Abbreviation

FIT2103 Introduction to programming for data science - DISESTABLISHED (02 Sep 2016, 2:28pm) [IntroProgDataSc (25 Jul 2016, 10:02am)]

Reasons for Introduction

Reasons for Introduction (25 Jul 2016, 10:02am)

This postgraduate foundation unit is a level 2 unit based on FIT1045. The introduction of this unit will allow us to increase our intake for GDDS by admitting those applicants who do not have the programming background.

Reasons for Change (02 Sep 2016, 2:29pm)

02/09/2016 - this unit was to be part of the foundation in the MDS and GDDS however it has now been replaced and will be developed as FIT9133 Programming foundations in Python.

Objectives

Objectives (25 Jul 2016, 10:03am)

Upon successful completion of this unit students should be able to:

  1. design, construct, test and document small computer programs using Python
  2. recognise the relationship between a problem description and program design;
  3. demonstrate how basic data structures function;
  4. investigate different strategies for algorithm development and evaluate these to select an appropriate solution to a given problem.

Unit Content

ASCED Discipline Group Classification (25 Jul 2016, 10:03am)

020109

Synopsis (25 Jul 2016, 10:04am)

This unit introduces programming fundamentals and the Python language to students. The unit provides a foundational understanding of program design and implementation of algorithms to solve simple problems. Fundamental programming control structures, built in and complex data types and mechanisms for modularity will be presented in Python.

Topics covered will include basic input and output, program control structures, basic data structures and modular program structure. Problem-solving strategies and techniques for algorithm development, iteration and recursion, algorithm.

Teaching Methods

Mode (25 Jul 2016, 10:04am)

Monash Online

Assessment

Assessment Summary (25 Jul 2016, 10:06am)

In-semester assessment: 100%

Monash Online units cannot have exams. Therefore all assessment must be in-semester.

To ensure that the students work is authentic, academic staff closely supervise students participation online and communicate with students by email regularly. They also conduct and document student interviews via the phone or online conferencing software throughout the semester. These methods complement our online assessment tools such as Respondus Lock-down browser and Turnitin.

Workloads

Workload Requirements (25 Jul 2016, 10:09am)

Minimum total expected workload equals 144 hours per semester comprising:

  1. Contact hours for Monash Online students:
    • Two hours/week online group sessions.
    • Online students generally do not attend lecture, tutorial and laboratory sessions, however should plan to spend equivalent time working through resources and participating in discussions.
  2. Additional requirements:
    • A minimum of 22 hours per week for completing lab/tutorial activities, assignments, private study and revision, and for online students, participating in discussions.

Resource Requirements

Prerequisites

Proposed year of Introduction (for new units) (25 Jul 2016, 10:10am)

TP1, 2017

Faculty Information

Proposer

Jeanette Niehus

Contact Person (25 Jul 2016, 10:10am)

Reza Haffari

Approvals

School:
Faculty Education Committee:
Faculty Board:
ADT:
Faculty Manager:
Dean's Advisory Council:
Other:

Version History

25 Jul 2016 Jeanette Niehus modified UnitName; modified Abbreviation; modified ReasonsForIntroduction/RIntro; modified UnitObjectives/Objectives; modified UnitContent/ASCED; modified UnitContent/Synopsis; modified Teaching/Mode; modified Assessment/Summary; modified Workload/ContactHours; modified Workload/ContactHours; modified Workload/ContactHours; modified Workload/ContactHours; modified DateOfIntroduction; modified FacultyInformation/FIContact
02 Sep 2016 Jeanette Niehus Admin: Disestablishing this unit as it has now been replaced with FIT9133.

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