Fascinated by the concept of machine learning? Ready to branch out into a new area of IT? Monash Online’s Data Analysis Algorithms unit could be just the course for you.
This single unit course provides an introduction to machine learning and statistical learning theory. Through six weeks of online study, you’ll discover key concepts of data analysis, from bias-variance to model selection. You’ll examine a series of different models and algorithms to help you gain a broader overall understanding of machine learning.
When you’ve completed this unit, you can choose to credit it towards further study in the field of data science or incorporate your new knowledge into your current career. The choice is entirely yours.
To be eligible to study this course, applicants must meet the following entry requirements:
- Have completed FIT5197 – Modelling for Data Analysis
What You’ll Learn
This is a single-unit course and may be used toward credit for future studies in data science.
Why study with Monash University?
Monash University offers its students a unique learning opportunity with their 100% online courses. Receive a premier experience with their personalised and interactive online courses in health, psychology and technology.
Undertake an online course and receive full access to instructors, fellow students, and dedicated tools including discussion forums and live video chat. With over 280,000 graduates and a ranking in the top 1% of the world’s universities (Times Higher Education Learning 2016-’17), Monash University is widely recognised and renowned as innovators of education.
As a student of Monash Online, you’ll be able to access their study planner tool, which will aid you with your time management and act as your personalised study timetable.
Their simple to navigate online courses makes online learning as seamless as possible, plus you'll have a personal Student Success Advisor to guide you throughout your learning journey.
Exchange ideas, receive feedback and generate opportunities by connecting with instructors and peers in real time.