Data Science
Honours unit of study table (Table A)
| This page was first published on 15 November 2023 and was last amended on 25 July 2024. View details of the changes below. |
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Honours in Data Science is available via an appended or an embedded or an integrated Honours, depending on the degree a student is enrolled in. The one-year program is comprised of a total of 48-credit points distributed across four 6-credit point selective coursework units and a total of 24-credit point research project in a specialised area of Data Science. The project is conducted under the direction of a supervisor who is an expert in the selected topic and who guides the research throughout the year.
Honours is available to students who have a completed major in an area relevant to their project and have met the requirements outlined in the resolutions. Admittance into the program is determined by the Faculty of Science as well as the data science honours coordinator.
Honours coordinator:
Dr Clara Grazian
clara.grazian@sydney.edu.au
Data Science (Honours) |
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| The Bachelor of Advanced Studies (Honours) (Data Science) requires 48 credit points from this table including: | ||
| (i) 12 credit points of 4000-level and above Honours coursework selective units from List 1, and | ||
| (ii) 12 credit points of 4000-level and above Honours coursework selective units from List 1, List 2, List 4 or List 5 with a maximum of 6 credit points of units from List 5, and | ||
| (iii) 24 credit points of 4000-level Honours research project units |
| Unit of study | Credit points | A: Assumed knowledge P: Prerequisites C: Corequisites N: Prohibition |
|---|---|---|
Honours Coursework Selective |
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List 1 |
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| COMP4446 Natural Language Processing |
6 | A Knowledge of an OO programming language as covered in INFO1113 C Enrolment in a thesis unit. INFO4001 or INFO4911 or INFO4991 or INFO4992 or AMME4111 or BMET4111 or CHNG4811 or CIVL4022 or ELEC4712 or COMP4103 or SOFT4103 or DATA4103 or ISYS4103 N COMP5046 |
| COMP4448 Visual Analytics |
6 | P (COMP2123 or COMP2823) and 126 credit points N COMP5048 or OCMP5048 |
| COMP4328 Advanced Machine Learning |
6 | P 132 credit points C COMP3308 or COMP3608 or COMP4318 or [(INFO1110 or INFO1910 or Distinction result in ENGG1810) and Distinction results in MATHXXXX] N COMP5328 or OCMP5328 |
| COMP4329 Deep Learning |
6 | P COMP3308 or COMP3608 or COMP4318 or BMET2925 C Enrolment in a thesis unit. INFO4001 or INFO4911 or INFO4991 or INFO4992 or AMME4111 or BMET4111 or CHNG4811 or CIVL4022 or ELEC4712 or COMP4103 or SOFT4103 or DATA4103 or ISYS4103 N COMP5329 or OCMP5329 |
| COMP4338 Advanced Data Models |
6 | P (INFO2120 or INFO2820 or ISYS2120) and 126 credit points N COMP5338 or OCMP5338 |
| COMP4349 Cloud Computing |
6 | A Knowledge of OS concepts as covered in INFO1112 P INFO1110 or INFO1910 or ENGG1810 or DATA1002 C Enrolment in a thesis unit. INFO4001 or INFO4911 or INFO4991 or INFO4992 or AMME4111 or BMET4111 or CHNG4811 or CIVL4022 or ELEC4712 or COMP4103 or SOFT4103 or DATA4103 or ISYS4103 N COMP5349 or OCMP5349 |
| STAT4025 Time Series |
6 | P STAT2X11 and (MATH1062 or MATH1962 or MATH1972 or MATH1X03 or MATH1907 or MATH1X23 or MATH1933) N STAT3925 |
| STAT4026 Statistical Consulting |
6 | P At least 12cp from STAT2X11 or STAT2X12 or DATA2X02 or STAT3XXX N STAT3926 |
| STAT4027 Advanced Statistical Modelling |
6 | A A three year major in statistics or equivalent including familiarity with material in DATA2X02 and STAT3X22 (applied statistics and linear models) or equivalent P (STAT3X12 or STAT3X22 or STAT4022) and (STAT3X13 or STAT3X23 or STAT4023) |
List 2 |
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| AMSI4001 AMSI Summer School |
6 | A Completed a first degree with a major in Mathematics, Statistics, Financial Mathematics and Statistics, Data Science or equivalent This unit has been designed to enable University of Sydney students to continue to take advantage of the premier Mathematics and Statistics summer school held in Australia. The University of Queensland and Melbourne already offer similar shell units to their honours and masters students respectively. |
| MATH4061 Metric Spaces |
6 | A Real analysis and vector spaces. For example (MATH2922 or MATH2961) and (MATH2923 or MATH2962) P An average mark of 65 or above in 12cp from the following units (MATH2X21 or MATH2X22 or MATH2X23 or MATH3061 or MATH3066 or MATH3063 or MATH3076 or MATH3078 or MATH3962 or MATH3963 or MATH3968 or MATH3969 or MATH3971 or MATH3974 or MATH3976 or MATH3977 or MATH3978 or MATH3979) N MATH3961 |
| MATH4062 Rings, Fields and Galois Theory |
6 | P (MATH2922 or MATH2961) or a mark of 65 or greater in (MATH2022 or MATH2061) or 12cp from (MATH3061 or MATH3066 or MATH3063 or MATH3076 or MATH3078 or MATH3962 or MATH3963 or MATH3968 or MATH3969 or MATH3971 or MATH3974 or MATH3976 or MATH3977 or MATH3978 or MATH3979) N MATH3062 or MATH3962 |
| MATH4063 Dynamical Systems and Applications |
6 | A Linear ODEs (for example, MATH2921), eigenvalues and eigenvectors of a matrix, determinant and inverse of a matrix and linear coordinate transformations (for example, MATH2922), Cauchy sequence, completeness and uniform convergence (for example, MATH2923) P (A mark of 65 or greater in 12cp of MATH2XXX units of study) or [12cp from (MATH3061 or MATH3066 or MATH3076 or MATH3078 or MATH3961 or MATH3962 or MATH3968 or MATH3969 or MATH3971 or MATH3974 or MATH3976 or MATH3977 or MATH3978 or MATH3979)] N MATH3063 or MATH3963 |
| MATH4068 Differential Geometry |
6 | A Vector calculus, differential equations and real analysis, for example MATH2X21 and MATH2X23 P (A mark of 65 or greater in 12cp of MATH2XXX units of study) or [12cp from (MATH3061 or MATH3066 or MATH3063 or MATH3076 or MATH3078 or MATH3961 or MATH3962 or MATH3963 or MATH3969 or MATH3971 or MATH3974 or MATH3976 or MATH3977 or MATH3978 or MATH3979)] N MATH3968 |
| MATH4069 Measure Theory and Fourier Analysis |
6 | A (MATH2921 and MATH2922) or MATH2961 P (A mark of 65 or greater in 12cp of MATH2XXX units of study) or [12cp from the following units (MATH3061 or MATH3066 or MATH3063 or MATH3076 or MATH3078 or MATH3961 or MATH3962 or MATH3963 or MATH3969 or MATH3971 or MATH3974 or MATH3976 or MATH3977 or MATH3978 or MATH3979)] N MATH3969 |
| MATH4071 Convex Analysis and Optimal Control |
6 | A MATH2X21 and MATH2X23 and STAT2X11 P [A mark of 65 or above in 12cp of (MATH2XXX or STAT2XXX or DATA2X02)] or [12cp of (MATH3XXX or STAT3XXX)] N MATH3971 |
| MATH4074 Fluid Dynamics |
6 | A (MATH2961 and MATH2965) or (MATH2921 and MATH2922) P (A mark of 65 or above in 12cp of MATH2XXX) or (12cp of MATH3XXX) N MATH3974 |
| MATH4076 Computational Mathematics |
6 | A (MATH2X21 and MATH2X22) or (MATH2X61 and MATH2X65) P [A mark of 65 or above in (12cp of MATH2XXX) or (6cp of MATH2XXX and 6cp of STAT2XXX or DATA2X02)] or (12cp of MATH3XXX) N MATH3076 or MATH3976 |
| MATH4077 Lagrangian and Hamiltonian Dynamics |
6 | A 6cp of 1000 level calculus units and 3cp of 1000 level linear algebra and (MATH2X21 or MATH2X61) P (A mark of 65 or greater in 12cp of MATH2XXX units of study) or [12cp from (MATH3061 or MATH3066 or MATH3063 or MATH3076 or MATH3078 or MATH3961 or MATH3962 or MATH3963 or MATH3968 or MATH3969 or MATH3971 or MATH3974 or MATH3976 or MATH3978 or MATH3979)] N MATH3977 |
| MATH4078 PDEs and Applications |
6 | A (MATH2X61 and MATH2X65) or (MATH2X21 and MATH2X22) P [A mark of 65 or greater in 6cp from (MATH2X21 or MATH2X65 or MATH2067) and a mark of 65 or greater 6cp from (MATH2X22 or MATH2X61)] or [12cp from (MATH3061 or MATH3066 or MATH3063 or MATH3076 or MATH3961 or MATH3962 or MATH3963 or MATH3968 or MATH3969 or MATH3971 or MATH3974 or MATH3976 or MATH3977 or MATH3979)] N MATH3078 or MATH3978 |
| MATH4079 Complex Analysis |
6 | A Good knowledge of analysis of functions of one real variable, working knowledge of complex numbers, including their topology, for example MATH2X23 or MATH2962 or MATH3068 P (A mark of 65 or above in 12cp of MATH2XXX) or (12cp of MATH3XXX) N MATH3979 or MATH3964 |
| MATH4311 Algebraic Topology |
6 | A Familiarity with abstract algebra and basic topology, e.g., (MATH2922 or MATH2961 or equivalent), (MATH3961 or equivalent) and (MATH2923 or equivalent) |
| MATH4312 Commutative Algebra |
6 | A Familiarity with abstract algebra, e.g., MATH2922 or equivalent |
| MATH4313 Functional Analysis |
6 | A Real Analysis and abstract linear algebra (e.g., MATH2X23 and MATH2X22 or equivalent), and, preferably, knowledge of Metric Spaces |
| MATH4314 Representation Theory |
6 | A Familiarity with abstract algebra, specifically vector space theory and basic group theory, e.g., MATH2922 or MATH2961 or equivalent N MATH3966 |
| MATH4315 Variational Methods |
6 | A Assumed knowledge of MATH2X23 or equivalent; MATH4061 or MATH3961 or equivalent; MATH3969 or MATH4069 or MATH4313 or equivalent. That is, real analysis, basic functional analysis and some acquaintance with metric spaces or measure theory. |
| MATH4411 Applied Computational Mathematics |
6 | A A thorough knowledge of vector calculus (e.g., MATH2X21) and of linear algebra (e.g., MATH2X22). Some familiarity with partial differential equations (e.g., MATH3X78) and mathematical computing (e.g., MATH3X76) would be useful |
| MATH4412 Advanced Methods in Applied Mathematics |
6 | A A thorough knowledge of vector calculus (e.g., MATH2X21) and of linear algebra (e.g., MATH2X22). Some familiarity with partial differential equations (e.g., MATH3X78) and mathematical computing (e.g., MATH3X76) would be useful |
| MATH4413 Applied Mathematical Modelling |
6 | A MATH2X21 and MATH3X63 or equivalent. That is, a knowledge of linear and simple nonlinear ordinary differential equations and of linear, second order partial differential equations. |
| MATH4414 Advanced Dynamical Systems |
6 | A Assumed knowledge is vector calculus (e.g., MATH2X21), linear algebra (e.g., MATH2X22), dynamical systems and applications (e.g., MATH4063 or MATH3X63) or equivalent. Some familiarity with partial differential equations (e.g., MATH3978) and mathematical computing (e.g., MATH3976) is also assumed. |
| MATH4511 Arbitrage Pricing in Continuous Time |
6 | P MATH2XXX and (a mark of 65 or above in MATH3XXX or STAT3021 or STAT3921) A Familiarity with basic probability (eg STAT2X11), with differential equations (eg MATH3X63, MATH3X78), achievement at credit level or above in MATH3XXX or STAT3XXX units or equivalent |
| MATH4512 Stochastic Analysis |
6 | A Students should have a sound knowledge of probability theory and stochastic processes from, for example, STAT2X11 and STAT3021 or equivalent |
| MATH4513 Topics in Financial Mathematics |
6 | A Students are expected to have working knowledge of Stochastic Processes, Stochastic Calculus and mathematical methods used to price options and other financial derivatives, for example as in MATH4511 or equivalent |
| STAT4021 Stochastic Processes and Applications |
6 | A Students are expected to have a thorough knowledge of basic probability and integral calculus and to have achieved at credit level or above in their studies in these topics N STAT3011 or STAT3911 or STAT3021 or STAT3003 or STAT3903 or STAT3005 or STAT3905 or STAT3921 |
| STAT4022 Linear and Mixed Models |
6 | A Material in DATA2X02 or equivalent and MATH1002 or MATH1X61 or equivalent; that is, a knowledge of applied statistics and an introductory knowledge to linear algebra, including eigenvalues and eigenvectors N STAT3012 or STAT3912 or STAT3022 or STAT3922 or STAT3004 or STAT3904 |
| STAT4023 Theory and Methods of Statistical Inference |
6 | A STAT2X11 and (DATA2X02 or STAT2X12) or equivalent. That is, a grounding in probability theory and a good knowledge of the foundations of applied statistics N STAT3013 or STAT3913 or STAT3023 or STAT3923 |
| STAT4028 Probability and Mathematical Statistics |
6 | A STAT3X23 or equivalent: that is, a sound working and theoretical knowledge of statistical inference N STAT4528 |
List 4 |
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| 5000-level units available in the School of Mathematics and Statistics except STAT5002, STAT5003, DATA5810 or DATA5811. | ||
List 5 |
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| 4000-level or 5000-level units at other Schools at the University | ||
Honours Core Research Project |
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| DATA4103 Data Science Honours Project A |
6 | |
| DATA4104 Data Science Honours Project B |
6 | C DATA4103 |
| DATA4105 Data Science Honours Project C |
6 | C DATA4104 |
| DATA4106 Data Science Honours Project D |
6 | C DATA4105 and SCIE4999 |
| SCIE4999 Final Honours Mark |
0 | |
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