The Queensland University of Technology is offering free online course on Big Data: Mathematical Modelling. This course is designed for anyone looking to add mathematical methods for data analytics to their skill set.
Applicants will learn how to apply selected mathematical modelling methods to analyse big data in this free online course. The course will start on July 17, 2017.
Course At Glance
Length: 3 weeks
Effort: 3 hours/week
Subject: Big Data: Mathematical Modelling
Institution: Queensland University of Technology and Future learn
Languages: English
Price: Free
Certificate Available: Yes
Session: Course starts on July 17, 2017
Providers’ Details
QUT is a leading Australian university ranked in the top two per cent of universities worldwide in the 2015-16 Times Higher Education World University Rankings. Our courses are in high demand, and our graduates include eight Rhodes Scholars, five of these awarded in the past six years. We are a connected, relevant and collaborative institution that seeks to solve real-world challenges.
About This Course
Mathematics is everywhere, and with the rise of big data it becomes a useful tool when extracting information and analysing large datasets. We begin by explaining how maths underpins many of the tools that are used to manage and analyse big data. We show how very different applied problems can have common mathematical aims, and therefore can be addressed using similar mathematical tools. We then introduce three such tools, based on a linear algebra framework: eigenvalues and eigenvectors for ranking; graph Laplacian for clustering; and singular value decomposition for data compression.
Why Take This Course?
This is a free online course. This MOOC will be offered with Video Transcripts in English. Applicants can get a verified certificate.
Learning Outcomes
- Identify big data application areas
- Explore big data frameworks
- Model and analyse data by applying selected techniques
- Demonstrate an integrated approach to big data
- Develop an awareness of how to participate effectively in a team working with big data experts
Requirements
This course is designed for anyone looking to add mathematical methods for data analytics to their skill set. We provide a multi-layered approach, so you can learn about the methods even if you don’t have a strong maths background, but we provide further information for those with a sound knowledge of undergraduate mathematics. We will assume basic MATLAB (or other) programming skills for some of the practical exercises.
Instructors
Ian Turner
He is Professor of Computational Mathematics at QUT. My interests are in the modelling of complex systems using finite volume methods, fractional calculus and numerical linear algebra.
Steven Psaltis
He is Postdoctoral Fellow in the ARC Centre of Excellence for Mathematical and Statistical Frontiers at QUT. I’m interested in numerical simulation of physical systems, gpu computing and visualisation
How To Join This Course
- Go to the course website link
- Sign Up At FutureLearn
- Select a course and Join
- Once a course has started, applicant will be able to access the course material
- After the start date, students will be able to access the course by following the Go To Course link on My Courses page.
- Applicants can buy, to show that they have completed a FutureLearn course.
- On some FutureLearn courses, learners will be able to pay to take an exam to qualify for a Statement of Attainment. (These are university-branded, printed certificates that provide proof of learning on the course topic(s)).