Master of Financial Technology in Data Analytics

Griffith University - Nathan Campus

Australia,Queensland

 0 Shortlist

24 Months

Duration

CAD 38,500/year

Tuition Fee

CAD 50

Application Fee

Jul 2025

Apply Date

Australia, Queensland

Type: University

Location Type: Semi-Urban

Founded: 1971

Total Students: 50,000 +

Int. Students: 8,500 +

Campus Detail

Main Campus Address

170 Kessels Rd, Nathan QLD 4111, Australia

Master of Financial Technology in Data Analytics

Program Overview

The Master of Financial Technology offers a qualification that provides advanced studies in modern technology with knowledge of the global financial market. The finance industry is becoming more information and data-driven. Businesses have greatly benefited from using advanced data analytics to improve their financial position.

The program is designed for students, either with or without the background in IT or Finance, to enter a rapidly growing FinTech industry, which includes big data analytics, artificial intelligence, blockchain, programming and cybersecurity, while at the same time understanding how financial markets function.

Students will be learning advanced Excel skills combined with the Python programming language, R Studio and Tableau to evaluate a large amount of financial data and assess different investment decisions across various market conditions.

This program provides a unique opportunity to combine these skills in a unified degree, and graduates will comprehend specialised knowledge in the financial services organisation and the application of emerging technologies in the finance industry.


Major: Data Analytics
This course will cover important concepts in Data Analytics including preparing, processing, normalizing, modeling, and visualizing data with the goal of summarizing useful information and supporting decision-making. It will introduce students to techniques and tools in data processing, exploratory data analytics, statistical data analytics, visual data analytics, analytics for special types of data.

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