C6011 Master of Applied Data Science
Faculty of Information Technology
Master of Applied Data Science (C6011) is a 72-credit-point, master's degree (coursework) course from the Faculty of Information Technology, taught at Monash Online. Map your units semester by semester with the MonMap planner.
- Credit points
- 72
- Campus
- Monash Online
- Online
This is the 2024 handbook entry. See the 2027 entry.
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Requisite map
Overview
Master of Applied Data Science will develop the core data analytic skills that are essential for a data scientist and prepare you for a career in data science with a critical set of problem-solving skills via bridging the gap between data analytics theorem and practice. You will learn contemporary statistical data analytic techniques that effectively transform data into actionable knowledge via solving real-world problems. The course broadly covers topics in data exploration, data wrangling, big data processing, data management and its role and impact in an organization and society. You will be able to apply your learning, knowledge and skills as part of the assessment process and through a data analytics-focused general practice project.
Course structure
Part A. Foundation studies18 credit points
Part B. Core studies18 credit points
Part C. Specialist studies24 credit points
Part D. Applied practice12 credit points
The handbook's description of this structure
This course is structured in four consecutive parts: Part A: Foundation studies, Part B: Core studies, Part C: Specialist studies and Part D: Applied practice
Part A. Foundation studies
These studies will provide a foundation for applied data science.
Part B. Core studies
These studies will provide an orientation and draw on best practices within the broad field of data science practice and research. Your studies will focus on fundamentals and core knowledge.
Part C. Specialist studies
The focus of these studies is specialising in the area of data science.
Part D. Applied practice
The focus of these studies is professional or scholarly work that can contribute to the portfolio of professional development.
Master's entry points
Depending on prior qualifications you may receive entry level credit (a form of block credit) which determines your point of entry to the course:
- If you are admitted at entry level 1 you complete 72 credit points, comprising Parts A, B, C and D
- If you are admitted at entry level 2 you complete 48 credit points, comprising Parts C and D and two units that have not been completed in Part B
- If you are admitted at entry level 3 you complete 24 credit points, comprising three units that have not been completed from Part C and the remaining unit in Part D.
Course progression map
The course progression map provides guidance on unit enrolment for each teaching period of study.
The course comprises 72 points structured into four parts: Part A. Foundation studies, Part B. Core studies, Part C. Specialist studies and Part D. Applied practice.
Units are 6 points unless otherwise stated.
Part A. Foundation studies (18 points)
You must complete:
- ITO4132 Introduction to database
- ITO4133 Introduction to Python
- MAT9004 Mathematical foundations for data science
Part B. Core studies (18 points)
You must complete:
- ITO5145 Introduction to data science
- ITO5196 Data wrangling
- ITO5197 Statistical data modelling
Part C. Specialist studies (24 points)
You must complete four units (24 points) from the following:
- ITO5147 Data exploration and visualisation
- ITO5149 Applied data analysis
- ITO5201 Machine learning
- ITO5202 Data processing for big data
- ITO5212 Data analysis for semi-structured data
Part D. Applied practice (12 points)
You must complete:
- ITO5001 Applied practice 1
- ITO5002 Applied practice 2
Learning outcomes
These course outcomes are aligned with the Australian Qualifications Framework and Monash Graduate Attributes.
Upon successful completion of this course it is expected that you will be able to:
- 1
demonstrate a technical understanding of data science theories in the practice of data science;
- 2
apply contemporary data exploration, data mining, and machine learning tools and methods to real-world data science problems;
- 3
investigate, analyse, document and communicate the core issues and requirements in developing data analysis capability in a global organisation;
- 4
apply knowledge of the data science lifecycle to projects in new application areas in accordance with professional best practice;
- 5
document and communicate ethical and legal issues and norms in privacy and security, and other areas of community impact regarding the practice of data science;
- 6
communicate data science related tasks to various stakeholders perceptively and effectively.
Entry requirements
English language
Monash Level A, that is: IELTS Academic): 6.5 overall (no band lower than 6.0); or Pearson Test of English (Academic): score of 58 overall with no band lower than 50; or TOEFL Internet-based test: score of 79 overall with minimum scores: Writing: 21, Listening: 12, Reading: 13 and Speaking: 18; or Equivalent approved English test.
Pathways
Graduate Certificate of Applied Data Science (C4012)
Graduate Diploma of Applied Data Science (C5003)
More information
Other information
Master of Applied Data Science will develop the core data analytic skills that are essential for a data scientist and prepare you for a career in data science with a critical set of problem-solving skills via bridging the gap between data analytics theorem and practice. You will learn contemporary statistical data analytic techniques that effectively transform data into actionable knowledge via solving real-world problems. The course broadly covers topics in data exploration, data wrangling, big data processing, data management and its role and impact in an organization and society. You will be able to apply your learning, knowledge and skills as part of the assessment process and through a data analytics-focused general practice project.
Contacts
- Academic Coordinator
- Dr Guanliang Chen
Common questions
Where can I study Master of Applied Data Science?
At Monash Online.
How do I plan my Master of Applied Data Science units?
Open the course in the MonMap planner. It lays out your semesters, checks prerequisites as you drag units in, and tracks the credit points each requirement still needs.