C09099v1 Bachelor of Science (Honours) in Analytics
Award(s): Bachelor of Science (Honours) in Analytics (BSc(Hons))CRICOS code: 088440D
Commonwealth supported place?: Yes
Load credit points: 48
Course EFTSL: 1
Location: City campus
Overview
Career options
Course intended learning outcomes
Admission requirements
Course duration and attendance
Course structure
Course completion requirements
Course program
Other information
Overview
The Bachelor of Science (Honours) is an introduction into research training and more advanced areas of study in analytics and data science. It also fosters soft skills such as time management and independent learning, and provides hands-on experience in working on and managing a creative project.
Honours is suited to students considering a career in data science and quantitative analysis. The course challenges students to exercise more initiative and independence, and to develop greater depth of knowledge and advanced analytical skills, all attributes that are highly sought after by employers.
Honours degree graduates are particularly sought after by employers and their skills enable them to compete for high entry-level jobs leading to progressive careers in data science and business analytics.
Career options
Career options include data scientist and business analyst roles in consumer analytics and marketing research, logistics management, credit risk management, stock market analysis, providing advice on portfolio management, option pricing, prediction of movements in international money markets and financial risk management. Major employers of graduates include media and marketing companies, professional services and consulting firms, banks, insurance companies, superannuation providers, government regulatory bodies such as APRA and ASIC, and other major financial bodies.
Course intended learning outcomes
| 1.1 | Apply: Develop a well-developed broad range of mathematical, statistical, computational, and data management skills, as well as experience in the use of the information technology required for modern data analysis. |
| 1.2 | Analyse: Examine and combine the principles and concepts of mathematical and statistical analytics, incorporating deductive reasoning and sophisticated analytical methods to solve complex problems. |
| 1.3 | Synthesise: Integrate extensive knowledge of sub-disciplines of the Mathematical Sciences providing a pathway for further learning and research. |
| 2.1 | Apply: Conduct an advanced research project and present the results with intellectual independence. |
| 2.2 | Analyse: Make arguments based on proof and conduct simulations based on selection of approaches (e.g. analytic vs numerical/experimental, different statistical tests, different heuristic algorithms) and various sources of data and knowledge. |
| 2.3 | Synthesise: Apply existing strategies to new problems, and analyse, critically evaluate, and transform complex information to complete a range of activities. |
| 3.1 | Apply: Work effectively and responsibly in an individual or team context with advanced professional and interpersonal skills. |
| 3.2 | Analyse: Organise and manage a complex project demonstrating advanced skills in Mathematical Programming and Specialist Mathematical/Statistical/QM Software using time management and collaborative skills. |
| 3.3 | Synthesise: Ethical application of mathematical and statistical approaches to complex problem-solving and decision-making as relevant to broader societal contexts. |
| 4.1 | Apply: Demonstrate well-developed self-reflection and independent learning strategies to extend existing knowledge. |
| 4.2 | Analyse: Advanced information retrieval and consolidation skills applied to the critical evaluation of the mathematical/statistical aspects of information to think creatively and try different approaches to solving problems. |
| 4.3 | Synthesise: Test advanced critical thinking skills to create innovative solutions for contemporary mathematical sciences problems. |
| 5.1 | Apply: Succinct and accurate presentation of information, reasoning, and conclusions in a variety of modes to diverse expert and non-expert audiences. |
| 5.2 | Analyse: Conduct advanced independent research to clarify a problem or to obtain the information required to develop elegant mathematical solutions. |
| 5.3 | Synthesise: Integrate written and verbal instructions or problem statements to describe a significant complex piece of work and its importance, and place the work in the context of other scholarly research. |
| 6.1 | Apply: Demonstrate an appreciation of historical and contemporary Aboriginal and Torres Strait Islander Knowledges relevant to mathematics. |
| 6.2 | Analyse: Develop cultural awareness for ethical and respectful practices, and when developing community relations. |
| 6.3 | Synthesise: Integrate Aboriginal and Torres Strait Islander knowledges, as both experience and analysis, into professional practice. |
Admission requirements
Applicants must have completed a UTS recognised bachelor's degree in a relevant discipline at an appropriate level.
Students who are eligible to graduate from the Bachelor of Science in Analytics (C10384) with an average mark of 65 per cent or more over all subjects in Years 2 and 3 (full time) are eligible for entry to the honours degree, subject to the approval of the head of the School of Mathematical and Physical Sciences.
Students who have obtained qualifications equivalent to the Bachelor of Science in Analytics degree are considered for entry, upon application, by the head of school on the basis of their assessed potential to complete the honours degree.
The English proficiency requirement for international students or local applicants with international qualifications is: Academic IELTS: 6.5 overall with a writing score of 6.0; or TOEFL: paper based: 550-583 overall with TWE of 4.5, internet based: 79-93 overall with a writing score of 21; or AE5: Pass; or PTE: 58-64; or CAE: 176-184.
Eligibility for admission does not guarantee offer of a place.
International students
Visa requirement: To obtain a student visa to study in Australia, international students must enrol full time and on campus. Australian student visa regulations also require international students studying on student visas to complete the course within the standard full-time duration. Students can extend their courses only in exceptional circumstances.
Course duration and attendance
The course is offered on a one-year, full-time or two-year, part-time basis.
Course structure
The honours course requires completion of subjects comprising 48 credit points, consisting of advanced coursework subjects in mathematics, statistics and finance, together with a substantial project. The project involves a major investigation of some area of finance and provides students with the opportunity to apply the skills developed in their coursework.
Course completion requirements
| STM91112 Core subjects (Analytics) | 30cp | |
| CBK91143 Specialisation choice | 18cp | |
| Total | 48cp |
Course program
The course commences in either Autumn or Spring session. The program shown assumes full-time attendance. Not all subjects may be available.
| Statistical Analysis stream | ||
| Year 1 | ||
| Autumn session | ||
| 37458 Advanced Bayesian Methods | 6cp | |
| 37493 Thesis (Mathematics) Honours Part A | 12cp | |
| Select 6 credit points from the following: | 6cp | |
| STM91113 Statistical Analytics stream | 18cp | |
| Spring session | ||
| 37459 Multivariate Data Analysis | 6cp | |
| 37494 Thesis (Mathematics) Honours Part B | 12cp | |
| Select 6 credit points from the following: | 6cp | |
| STM91113 Statistical Analytics stream | 18cp | |
| Stochastic Analysis stream | ||
| Year 1 | ||
| Autumn session | ||
| 37438 Modern Analysis with Applications | 6cp | |
| 37493 Thesis (Mathematics) Honours Part A | 12cp | |
| Select 6 credit points from the following: | 6cp | |
| STM91114 Stochastic Analytics stream | 18cp | |
| Spring session | ||
| 37459 Multivariate Data Analysis | 6cp | |
| 37464 Advanced Stochastic Processes | 6cp | |
| 37494 Thesis (Mathematics) Honours Part B | 12cp | |
Other information
Further information is available from:
UTS Student Centre
telephone 1300 ask UTS (1300 275 887)
or +61 2 9514 1222
Ask UTS
Further information regarding honours, including available projects and the application process, is available from UTS: Science.