The Master of Data Science will provide the knowledge, skills and experience to equip the graduate to operate independently as a data scientist within any...
Read moreThe Master of Data Science will provide the knowledge, skills and experience to equip the graduate to operate independently as a data scientist within any application domain. The training it provides also supports several career paths, by: honing data skills at the frontier of machine intelligence research to become a data scientist for hire; up-skilling to build intelligent data-driven systems in an existing area of expertise (e.g., mining analyst); improving scientific research through training in data management, analysis, and modelling.
Some background in computing (specifically in programming and in data management as taught in the Graduate Certificate in Data Science) is assumed....
Read moreSome background in computing (specifically in programming and in data management as taught in the Graduate Certificate in Data Science) is assumed. If you do not have previous IT background, please apply for the Graduate Certificate in Data Science. Applicants who hold a three year bachelor's degree in a quantitative discipline can apply to the Master of Data Science based on employment experience if they can demonstrate a minimum of two years relevant industry experience in IT or Data Science/Data Analytics. This must be supported by a CV and proof of work experience (in the form of an official letter from the employer including details of your position, dates of employment and job description). In all other cases, applicants should apply for the Graduate Certificate in Data Science.
Positives: It's very elaborate and definitely a notch above the basics. It caters to a whole range of topics in Data science and you can clearly do this course and yet be employable for a lot of industries. Teachers are brilliant and the coursework is great
Negatives: The lack of ""applications"" in industries. Academia i...
Read morePositives: It's very elaborate and definitely a notch above the basics. It caters to a whole range of topics in Data science and you can clearly do this course and yet be employable for a lot of industries. Teachers are brilliant and the coursework is great
Negatives: The lack of ""applications"" in industries. Academia is great but it lacks how the industries use data science today and it would be good to hear industry speakers and how they are using these things in their companies
My advice to future students is: Get some work experience before you jump on the bandwagon. Understand what you want out of the course and what you intend to do with it. be proactive than reactive!