How is the Master of Data Analytics in Deakin University?
Choosing a university for your Masters can be a daunting task and information is the key — I wish a lot of answers were readily available before I made my choice, but luckily, a lot of research, conversations with professors and previous students helped me choose a decent Analytics program — which is why I’m going to try and be as elaborate as I can with my answer — and possibly address every question that I faced as an applicant.
Before I list the Pros and Cons of studying Data Analytics at Deakin University, let me clarify a common misconception that Deakin isn’t good for IT or that the Program in Data Analytics is mostly Business Analytics — and not pure Data Science.
There’s already a very well established Business Analytics program at Deakin which has some strong connections with the Industry — but the DA program, although sharing similar foundational courses with BA, goes right into the Data Science Specialization with advanced courses in Statistics, Machine Learning and R.
- Content — If you’re like me and you really want to learn Data Science rather than merely getting through to find some job, Deakin’s curriculum should really satisfy you.
- My interest is in Machine Learning, and Deakin offers two courses — “Machine Learning” and “Practical Machine Learning”. The professors who teach these courses are also well experienced and do great research on their own.
- You get to apply Python in courses like “Modern Data Science” and “Machine Learning”
- R is taught in most of the Statistics courses, along with “Real World Analytics”, which further expands on Game theory, Linear Programming, Graph theory and Operations Research
- You will be able to build an advanced Statistics tool-kit by the end of the courses with modules like “Multivariate and Categorical Data Analytics” teaching Probabilistic Graphical Models (akin to the one on coursera) and “Statistical Data Analysis” teaching Probability Theory and Supervised Learning Methods.
- Spark is taught in the 2nd half of “Modern Data Science”
- Professors — Deakin has a top class research group called “Centre for Pattern Recognition and Data Analytics (PRaDA). I suggest you to go through their excellect work in Machine Learning and Healthcare Analytics. One significant advantage you have is that a lot of these classes are taught by PRaDa researchers — so if you’re planning to do research, this could be very helpful.
- I would strongly urge you to look in to the profile and the work of professors like Gang Li, Jacob Cybulski, Wei Luo, Sunil Gupta and Maia Angelova.
- “Security and Privacy Issues in Analytics” is taught by Prof. Matthew Warren, who is one of the leading Cybersecurity experts in Australia and often even features in the news.
Having covered the major factors, other notable perks of DA at Deakin include these -
- Deakin ranks the 3rd in Graduate Employability in Australia — above Unimelb, Usyd and UNSW! Moreover, they recently launched DeakinTalent — an online platform that connects with employers for Part-time jobs and internships.
- It’s relatively much easier to manage your Part-time job and your study at Deakin — as opposed to say RMIT, Unimelb or Monash — they are often intensive and a lot of my friends complain about being too stressed out and end up quitting their job. Deakin isn’t too strict about attendance and you have option to study 25% of your course through cloud — so you won’t have to attend classses. While I would recommend you to avoid that and have the full class experience, it’s still good to know that you have this option when you really need it.
- There’s a “start anytime” unit (“Foundation Skills in Data Analytics”) which means you could either finish the unit in as less as 1 month or upto 1 whole year. This could be helpful if you’re feeling really stressed out in your 1st semester and you can’t afford to give valid time for all your classes.
- Classes are held in in the evening — this is a plus or not, depending on your situation
- Ranking wise, Deakin has been on a surge over the last 4 years — recently leaping into the 300 uni list — in most of the rankings, it is well above RMIT, Swinburne and La Trobe (other competitors in Melbourne).
- Deakin consistently ranks high in Student Satisfaction and Teaching satisfaction (4 stars) well above Monash (2 stars), RMIT (1 star) and Unimelb.
- If you’re a student from India, you will be eligible for a 20% percent scholarship if you get above 65% marks in your Bachelors. This make Deakin quite affordable compared to Monash and Unimelb.
- Deakin does not quite have the brand name of Monash and Unimelb. If you’re a kind of person who thinks that University name really matters in finding a job — then maybe go for Monash Data Science. However, if you think employers don’t really take it that seriously, but rather see your skills and knowledge, Deakin should be more than good enough.
- If you’re really focused on Big Data — you might be a bit dissapointed as Deakin does not have a platform for Hadoop, which is why Hadoop isn’t dealt in detail. Instead, you will be learning Spark.
- The course is relatively new. If it’s really important to you that there be employability records and stats and you want a course that has stood the test of time — you could choose Monash or any other similar programs.
- There aren’t as many electives for this course as there are for RMIT or Monash (except with the option of choosing an internship or doing a thesis). RMIT’s program in Analytics has over 50+ electives! from Logistics, Supply Chain Management and Statistics to Finance and Economcs! Deakin’s program however, is very air-tight.
- There aren’t as many industry partners for this course yet, as there are for Monash’s program or RMIT’s Data Science/Analytics program or Unimelb. There are certainly a lot of opportunities for the talented — with regular internships at SEEK and new companies lining up, however being a relatively new program, this could get competitive for you.
- On the other hand, the Business Analytics program has plenty of industry collaborations with IBM, PwC and many more. Its possible that there will be more for the DA program in the next year or further.
And yes, you will be able to do an internship as part of your program (which carries 4 credits).
Hope this helps and good luck!