Graduate Diploma of Data Science
Course code: C5003
The Graduate Diploma of Data Science will equip you with the skills needed to put you at the forefront of the exciting field of big data. Data scientists are in demand around the world as companies need professionals capable of managing and making sense of vast amounts of data that can help management teams make important decisions for the business.
100 percent online, flexible study – including all assessments, research, and exams
Six intakes a year – start whenever you are ready
Dedicated support – personalised support team to guide you throughout your studies
Learn with industry standard tools and real-world problems
The course will focus on developing skills in data analysis, data management, and big data processing. You will not only be equipped with the technical knowledge you need to impact business problems, but you will also gain the skills to communicate complex ideas at all levels.
You will complete up to two foundation units, three core units and three to five electives, depending on your pathway academic background and experience.
The course comprises of 48 points and each unit is 6 credit points.
a) Up to two foundation units (0-12 points)
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 computational 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 structures, problem solving strategies and techniques for algorithm development, iteration and recursion.
This unit will introduce the concept of data management in an organisation through relational database technology. Theoretical foundation of relational model, analysis and design, implementation of relational database using SQL will be covered.
b) Three core units (18 points)
This unit looks at processes, case studies and simple tools to understand the many facets of working with data, and the significant effort in Data Science over and above the core task of Data Analysis. Working with data as part of a business model and the lifecycle in an organisation is considered, as well as business processes and case studies. Data and its handling is also introduced: characteristic kinds of data and its collection, data storage and basic kinds of data preparation, data cleaning and data stream processing. Styles of data analysis and outcomes of successful data exploration and analysis are reviewed. Standards, tools and resources are also reviewed. Basic curation and management are reviewed: archival and architectural practice, policy, legal and ethical issues.
Here you will develop the skills required to prepare raw data for analytics, including data cleansing and pre-processing. Python and the Pandas environment will be used as part of this unit.
c) Three to five units (18-30 points) selected from
This unit provides students with an understanding of the tasks and the main issues associated with the management of data in modern organisations and communities for business and societal purposes. The unit will examine some of the key issues that affect the data management function, incorporating recordkeeping, information accessibility, knowledge management and the governance and accountability for the data repositories. This will be used as a basis for explaining the nature of specialist work in this field and associated professional roles and responsibilities. Topics cover digital repository infrastructures, digital continuity planning; data archiving; data migration; the development of systems to support data discovery and reuse; mediated access to digital information; negotiation of data rights (ownership, copyright, access, privacy etc); utilisation of cloud computing platforms, and the data curation continuum.
This unit explores statistical and visualisation techniques and their role in data science. Different types of visualisation techniques will be presented and evaluated.
This unit introduces the software tools and techniques for data engineering. It covers traditional methods of data processing, introduction to distributed databases and the handling and processing of big data.
This unit will give you the analytical and data modeling skills you will need to data scientist or business analyst. You will be introduced to various data analysis techniques and learn how to use them to address characteristic problems.
This unit presents foundational concepts in machine learning and statistical learning theory. Various different models and algorithms will be presented and interpreted.
An estimated 2.5 quintillion bytes of data are created every day (IBM, 2015), and companies around the world are eagerly searching for data scientists to manage and analyse this huge amount of information.
You may be an IT professional looking to use your skills and knowledge to pursue a career in this growing industry. Or perhaps you have worked in a related area and have a knack for numbers and an analytical mind. Whether it’s a global financial institution, government organisation or technology startup, data scientists can help companies investigate and analyse data to address real business problems.
Upon graduation, you could be employed in a diverse range of industries and hold job titles such as data scientist, data analyst, business intelligence analyst or machine learning engineer. Learn more about the various pathways and career options you will have in this Graduate Diploma of Data Science – Course & Jobs infographic.
Data scientists attract high salaries with the average in Australia being $98,748 per annum and goes up to $140,000 (Payscale). The Institute of Analytics Professionals of Australia (IAPA) Skills and Salary Survey 2017 revealed that data scientists can earn as much as $200,000 plus.
For entry into the course, you will need to prove work experience or previous study in programming, databases, or mathematics. This can be done if you possess:
- A bachelor’s degree in a cognate field at a recognised Australian institution or equivalent;
- Course Prerequisite form
In addition, you will need to:
- Meet minimum entry requirements for admission to Monash University
- Meet the English language requirements
Alternative Entry through Foundation Units
If you don’t possess a cognate degree, you may be eligible to enter via foundation units in programming, databases, and mathematics. You can take a maximum of two foundation units prior to commencing your studies if you have:
- A bachelor’s degree in business, engineering, or science with a mathematics major plus two Foundation Units (i.e. Programming and Databases), or;
- A non-cognate Graduate Diploma or Master’s degree (e.g. MBA) in any field at a recognised Australian institution and two years of relevant professional experience in programming or databases, plus up to two Foundation Units in an area not related to your work experience (i.e. Mathematics plus either Programming or Databases)
$4,062.50 per unit*
1.4 year part-time
Jan, Mar, May, Jul, Aug, Oct
15 March 2019
Graduate Diploma of Data Science – Course & Jobs
Data Science is a much sought after specialisation and there are several pathways to get into the Graduate Diploma of Data Science. This infographic will give you a clearer understanding of the course, pathways to entry and potential career opportunities you will have.Read article
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