C11376v1 Graduate Certificate in Applied Artificial Intelligence for Finance

Award(s): Graduate Certificate in Applied Artificial Intelligence for Finance (GradCertAppAIFin)
Commonwealth supported place?: No
Load credit points: 24
Course EFTSL: 0.5
Location: City campus

Notes

This course is not offered to international students.

Overview
Course aims
Career options
Course intended learning outcomes
Admission requirements
Inherent requirements
Assumed knowledge
Recognition of prior learning
Course duration and attendance
Course structure
Course completion requirements
Other information

Overview

This course is intended for current and aspiring business professionals, finance industry insiders, and recent graduates eager to harness the power of AI in the finance industry. Choose this course to enhance their digital skills, gain a competitive edge in the job market, and meet the increasing demand for AI solutions to business challenges.

The Graduate Certificate in Applied Artificial Intelligence for Finance stands out by offering practical knowledge of AI technologies and machine learning, tailored towards applications in areas such as wealth management, algorithmic trading, and sustainable finance. They acquire skills in data analysis, automation, and applications of AI in finance, under the guidance of world-class academics and industry experts.

The course emphasises hands-on learning through real-world case studies. Content is delivered via interactive lectures, guest lectures from industry experts, and practical exercises, all of which equip them with the expertise to thrive in the AI-enhanced landscape of modern finance.

Course aims

The Graduate Certificate in Applied Artificial Intelligence for Finance has clear and focused aims, designed to empower students with the skills and knowledge they need to excel in the ever-evolving landscape of AI in finance:

Comprehensive Understanding: The primary goal of this course is to provide students with a comprehensive understanding of Artificial Intelligence (AI) within the context of the finance industry. It delves into the fundamentals of AI, its historical development, and its transformative impact on finance.
Practical Skills: The course aims to equip students with practical skills that are directly applicable to real-world scenarios in finance. This includes proficiency in data analysis, machine learning, deep learning, and AI model deployment, enabling graduates to effectively address financial challenges with AI-driven solutions.
Informed Decision-Making: Graduates of this course will have the ability to make informed decisions regarding AI technologies in finance. They will understand how AI can be strategically deployed to optimise processes, enhance decision-making, and drive innovation in financial institutions.
Contributors to Transformation: This course aims to produce graduates who are not only well-versed in AI but also capable of actively contributing to the ongoing digital transformation of the finance industry. Graduates will be prepared to lead and implement AI initiatives that have a positive impact on financial institutions and the broader financial ecosystem.
Ethical Considerations: The course also emphasises the ethical dimensions of AI in finance, ensuring that graduates are equipped to navigate the ethical challenges and responsibilities associated with AI technologies in the financial sector.

By achieving these aims, this course empowers students to become adept AI practitioners, critical thinkers, and contributors to the advancement of AI in the finance industry.

Career options

Graduates of the Graduate Certificate in Applied Artificial Intelligence for Finance possess a versatile skill set that opens doors to a wide range of career opportunities. They are well-equipped to excel in various organisations and roles within the finance sector and beyond. Career options include positions in:

Banking Institutions: Graduates can pursue roles such as financial analysts, risk managers, or AI strategy consultants within banking institutions, where they apply AI to enhance decision-making, risk assessment, and customer experience.
Consulting Firms: Graduates can join consulting firms specialising in financial technology and AI, providing expert advice to financial clients on AI strategy, implementation, and optimisation.
Financial Technology (FinTech) Companies: Many FinTech firms seek professionals who can develop AI-driven solutions for payments, lending, robo-advising, and fraud detection.
Investment Firms: Graduates can work as quantitative analysts or portfolio managers, utilising AI to optimise investment strategies, identify market opportunities, and manage portfolios.
Regulatory Bodies: Regulatory agencies increasingly rely on AI for monitoring compliance and detecting financial misconduct, offering opportunities for graduates to contribute to regulatory oversight.
Startups: Graduates can join AI startups in the finance space, where innovation and entrepreneurship thrive. They may contribute to the development of disruptive AI technologies.
Wealth Management Companies: In the wealth management sector, graduates can leverage AI to provide tailored investment advice, wealth planning, and client services.
Insurance Companies: Graduates can play a pivotal role in AI-driven underwriting, claims processing, and risk assessment for insurance firms.
Government and Public Sector: Government agencies often require AI expertise for policy analysis, economic forecasting, and data-driven decision-making in areas related to finance and economics.
Academia and Research: For those inclined towards academia, graduates can pursue further studies or research positions, contributing to the advancement of AI in finance through academic institutions.
Entrepreneurship: Equipped with AI skills, some graduates may choose to start their own AI-focused businesses, offering AI solutions or consultancy services to various clients.

The career paths for graduates of this course are diverse and offer the flexibility to align with individual interests and goals, making it an ideal choice for anyone seeking a dynamic and rewarding career in the intersection of finance and AI.

Course intended learning outcomes

1.1	Implement critical, analytical, and innovative problem-solving skills to identify and propose effective solutions to contemporary finance issues using AI technologies
1.2	Evaluate and assess the suitability of AI techniques to address specific finance challenges, considering factors such as data availability, computational requirements, and ethical considerations
2.1	Communicate complex AI concepts and findings clearly and effectively to diverse stakeholders, adapting the communication style to suit the audience's level of technical understanding
2.2	Collaborate with colleagues, clients, and stakeholders from multidisciplinary backgrounds to develop and implement AI-based strategies, projects, and initiatives that achieve desired outcomes while considering business objectives, regulatory requirements, and ethical standards
3.1	Ensure ethical AI practices in finance that are inclusive, fair, and transparent
4.1	Integrate high-level technical skills in AI and machine learning with an understanding of finance principles, enabling the application of AI-based models, algorithms, and tools to address complex financial problems, optimise processes, and support decision-making in diverse finance domains
5.1	Critically reflect on the rights to consent, privacy, data sovereignty and self determination to work ethically with and for Indigenous Australians across finance professions

Admission requirements

To be eligible for admission to this course, applicants must meet the following criteria.

Applicants must have one of the following:

Completed Australian bachelor's degree or higher qualification, or overseas equivalent

A minimum of 5 years full-time, or equivalent part-time, relevant post-secondary professional experience AND a general capacity to undertake tertiary education

Relevant professional experience refers to any current work experience in which you have developed skills, knowledge, and competencies directly related to the course for which you are applying. This includes roles such as managers, professionals, technicians, community, personal service, clerical, administrative, or sales workers across various industries.

Supporting documentation to be submitted with the application

For applicants who need to demonstrate work experience:

Curriculum Vitae AND Statement of service in one of the following formats:
- A 'Statement of Service' provided by the employer
- A completed 'UTS statement of service’ signed by the employer
- A statutory declaration confirming work experience (for Australian Residents only)
- An official letter from the applicant’s accountant or solicitor on their company letterhead confirming the applicant’s work experience or engagement with the business, duration of operations, and the nature of the business
- A business certificate of registration in original language and English (e.g. provision of ASIC documentation or ABN or similar documentation for Australian Businesses)

The English proficiency requirement for local applicants with international qualifications is: IELTS Academic: 6.5 overall with a writing score of 6.0; or TOEFL iBT: 79-93 overall with a writing score of 21; or AE5: Pass; or PTE: 58-64 with a writing score of 50; or C1A/C2P: 176-184 with a writing score of 169.

Eligibility for admission does not guarantee offer of a place.

Inherent requirements

Inherent requirements are academic and non-academic requirements that are essential to the successful completion of a course. For more information about inherent requirements and where prospective and current students can get assistance and advice regarding these, see the UTS Inherent requirements page.

Prospective and current students should carefully read the Inherent Requirements Statement below and consider whether they might experience challenges in successfully completing this course.

UTS will make reasonable adjustments to teaching and learning, assessment, professional experiences, course related work experience and other course activities to facilitate maximum participation by students with disabilities, carer responsibilities, and religious or cultural obligations in their courses.

For course specific information see the UTS Business School Inherent Requirements Statement.

Assumed knowledge

There is no assumed knowledge for the Graduate Certificate in Applied Artificial Intelligence for Finance. A foundational understanding of finance concepts can enhance the learning experience in this course.

Recognition of prior learning

There is no recognition of prior learning available for this course.

Course duration and attendance

The course can be completed in a minimum of eight months study (i.e. 1 x 6 credit points subject per session over 4 x 7-week teaching sessions).

Course structure

The course comprises 24 credit points, made up of four compulsory subjects.

Course completion requirements

STM91889 Core subjects (GCAAF)		24cp
Total		24cp