Big Data, Cloud Computing and Machine Learning

Singapore University of Social Sciences

Big Data, Cloud Computing and Machine Learning (FIN559)

Synopsis

FIN559 Big Data, Cloud Computing and Machine learning provides an overview of computing and cloud technology that brings disruptive changes to various businesses including financial services. It starts with providing a foundational understanding of big data processing framework and approaches, and follows by introducing relevant tools to students through case studies and hands-on training. The course then examines the core elements of cloud computing, the different types of clouds, and the risk and security issues in cloud computing. It provides a framework for selecting the optimal combination of cloud technology to meet business requirements. Furthermore, the course introduces machine learning, covering both supervised and unsupervised algorithms. It discusses biasvariance trade-off for selecting the appropriate models and introduces neural networks and convolutional neural networks. Lastly the course discusses the applications of artificial intelligence and machine learning via case studies.

Level: 5
Credit Units: 5
Presentation Pattern: EVERY JAN

Topics

Challenges of big-data computing (the 5 V’s of big data)
Big-data computing requirements and framework
Programming tool and API for big-data computing
Integrating big-data computing in smart solutions
Core elements of cloud computing and different types of clouds
Security and privacy threats in cloud computing
Risk management plan for cloud computing
Technical and business models of cloud computing: IaaS, PaaS and SaaS
Implementing cloud computing using open source software
Introduction to machine learning
Supervised learning and unsupervised learning
Bias-variance tradeoff
Neural networks and convolutional neural networks
Artificial intelligence and machine learning applications and case studies

Learning Outcome

Appraise big-data computing framework, the challenges in big-data computing issues and the approaches to resolve them
Assess different types of clouds, core elements and risk management plans of cloud computing
Evaluate IaaS, PaaS and SaaS technology
Compare supervised learning against unsupervised learning, and neural networks against convolutional neural networks
Construct smart solution based on big-data computing
Formulate calculation for practicing cloud economics
Implement cloud computing using open source software
Design and develop machine learning applications