Through the course, you’ll learn how to:
analyse the lifecycle of data through an organisation, apply major theories in data analysis and exploration in common contexts and challenges
plan a data science project in a new area of application
investigate, analyse, document and communicate the core issues and requirements of developing a global organisation’s data analysis capabilities
demonstrate an understanding of data science to the standard of senior professional practice
review, assess, synthesise and apply modern data science theories for professional or academic purposes Scholarships - View all scholarships Internships
Duration: 2 Year(s)Fees: Not available
Intake | Location |
---|---|
Semester 1 (February), 2024 | Clayton |
Semester 2 (July), 2024 | Clayton |
Semester 2 (July), 2024 | CLAYTON - Online Start |
Semester 1 (February), 2025 | Clayton |
Semester 2 (July), 2025 | Clayton |
Semester 1 (February), 2026 | Clayton |
Semester 2 (July), 2026 | Clayton |
Entry level 1: Duration: 2 years full-time, 4 years part-time (96 points to complete) - An Australian undergraduate degree, not necessarily in IT, with at least a 60% average, or qualification deemed by the faculty to be a satisfactory equivalent.
Entry level 2: Duration: 1.5 years full-time, 3 years part-time (72 points to complete) - An Australian undergraduate degree in a cognate discipline relating to IT, or a business, engineering or science degree with an IT major including programming, databases and mathematics, with at least a 60% average, or qualification deemed by the faculty to be a satisfactory equivalent. or A four-year Australian honours degree with a research thesis consisting of at least 37.5% of a one year full time load and with at least a pass a 60% average, or qualification deemed by the faculty to be a satisfactory equivalent.
Entry level 3: Duration: 1 years full-time, 2 years part-time (48 points to complete) - A four-year Australian honours degree in a cognate discipline relating to IT, or a business, science or engineering degree with an IT major including programming, databases and mathematics, with a research thesis consisting of at least 37.5% of a one year full time load and with at least a 60% average, or qualification deemed by the faculty to be a satisfactory equivalent.
6.5
Overall IELTS band score
Book IELTS
About IELTS
Practice and prepare
TOEFL Internet based overall score: 79.0
Pathway options to study at this institution
54th / 1250
THE World ranking
Master of Data ScienceRated5/5based on1 student reviews
My course is challenging and we need to work hard to pass and get good grades. But marking is fair. I get to practice and learn a lot of new skills with assignments which help us to apply our knowledge. They act like real world project environments. Since the assignments also have deadlines, we also have to manage our time amongst the demands of all the units(4 units in total). In this course, we also have a lot of unit options to choose from and learn different aspects of our field. In the first semester, we had introductory units which were very helpful for someone like me who was from a different background(commerce and accounting). If you work hard, you can do well in this course. The deadlines and all the study requirements of this course will make you work hard even if you are lazy because the alternative is failing a unit, which nobody wants. But that said it is manageable, over time as you get accustomed to the workload, the requirements of the course and the resources available to you, you will know exactly how much effort is required for you. The first semester is the toughest according to me, not because the units/subjects are tough, but because you don't know what to expect and how much effort you need to put in. Word of advice, do not underestimate the requirements of the course, the more you postpone, delay doing something, miss lectures, etc these backlogs will only grow and will be difficult for you to cover up towards the end. So make sure to not keep any backlogs, finish work when they are scheduled to be done. As the semester progresses, your work pressure will only increase, so you have to keep up. If you keep up, you will be fine, if you don't, you will be pretty stressed towards the end of the semester. You get very little time to study before the exams, so the more you study and keep up during the semester, the better it is for you. The semester passes by in the blink of an eye, so keep pace or otherwise, you might not find time to catch up later on. But if you do catch up, you will be fine and get good grades. This is my experience. I am a person from a non-IT background. But I feel it applies to any student who wants to do well. And you would want to do well as jobs are scarce, competition is high and hence you need to put your best foot forward. But I am sure you will you will have a great time, as the facililites at Monash are very good. The students and teachers are very friendly and cooperative. There are a lot of resources at your disposal. There are lots of campus activities every week where you can have fun. You will meet a lot of nice people and make friends along the way. So you will have a great time. The only challenge that I am facing with the course is that is very expensive for me as an international student, but yes it can be paid off if you find a job. But yes, finding a job or an internship can be challenging as well. Not impossible, but challenging. It takes time and a lot of applications. You have to cast your net really wide. But people do find jobs! Also apply for internships and graduate positions during the semester when the applications open, as after the semester ends and the vacations start, they will not remain available anymore. Companies their application windows by then.Customer reviews:Master of Data Science -byRahul,2020-01-085.0/ 5 stars