100-LEVEL COURSES

COMP 112 Introduction to Computer Science 15 PTS Tri 1

COMP 102 CRN 943 Introduction to 15 PTS Tri 1 & 2 9792 Computer Program Design

Restriction: COMP 112

Coordinator: Dr Peter Andreae (Tri 1), Dr Xiaoying Gao (Tri 2) Laboratories: 2 hours per week

Text: Lewis, DePasquale and Chase, Java Foundations: Introduction to Program Design and Data Structures (2^nd edition), Pearson, 2011.

This course introduces the fundamentals of programming in a high-level programming language (Java), using an object oriented approach to program design. Students develop their programming skills by constructing computer programs for a variety of applications. The course provides a foundation for all later courses in computer science, and develops

programming skills useful for students in many other disciplines.

COMP 112 CRN 26034 Introduction to Computer Science 15 PTS Tri 1 Prerequisite: 14 AS level 3 NCEA credits in Digital Technology, including 6

credits in Computer Programming, or COMP 102, or INFO 102 or equivalent programming experience.

Restriction: COMP 103

Coordinator: Dr Peter Andreae Laboratories: 2 hours per week

This course introduces a range of important concepts and topics across Computer Science, Software Engineering and Network Engineering. Students will also gain a solid foundation of programming skills in object oriented programming. The course is an entry point to the BE(Hons) and the BSc in Computer Science for students who already have basic programming skills.

COMP 103 CRN 945 Introduction to Data Structures 15 PTS Tri 2 and Algorithms

Prerequisite: COMP 112 or B- or higher in COMP 102 Coordinator: Dr Marcus Frean

Tutorials: 1 hour per week

Text: Lewis, DePasquale and Chase, Java Foundations: Introduction to Program Design and Data Structures (2^nd edition), Pearson, 2011.

This course builds on COMP 102, focusing on the techniques for designing, building and analysing computer programs that deal with large collections of data. The course addresses techniques for programming with collections of data, and the data structures and algorithms needed to implement these collections. The course expands programming skills and

provides an understanding of the principles of data abstraction, algorithm design, and the analysis of algorithms fundamental to computer science.

ENGR 101 CRN 15243 Engineering Technology 15 PTS Tri 1 Prerequisite: Enrolment in the BE(Hons)

Restrictions: ENGR 120, TECH 102 Coordinator: Dr Rebecca Ford

Lecturers: Dr Bryan Ng, Dr Stuart Marshall Laboratories: 3 hours per week

Text: Browne, Linton and Pearce, Engr 101: Engineering Technology, McGraw-Hill

This course provides a general introduction to the fundamental technical concepts needed to understand the design and engineering of electronic, mechatronic, networked and software systems. Experience is gained in basic engineering practice, with assembly and testing of basic hardware, software and networked systems, and construction of a personal computer.

ENGR 110 CRN 26051 Engineering Technology 15 PTS Tri 2 Prerequisite: COMP 102 or 112 or ENGR 101

Coordinator: Dr Will Browne Lecturer: Dr Peter Andreae Laboratories: 2 hours per week

Text: UML in Practice: THE ART OF MODELING SOFTWARE SYSTEMS DEMONSTRATED THROUGH WORKED EXAMPLES AND

SOLUTIONS, Pascal Roques

This course introduces the role of modelling in the engineering design process. Different modelling techniques will be presented and techniques for evaluating each that can aid design decisions will be demonstrated. Practical work will support the learning of different modelling and simulation techniques.

37 Victoria University of Wellington

ENGR 121 CRN 26052 Engineering Mathematics 15 PTS Tri 1 Foundations

Prerequisite: 16 AS credits NCEA Level 3 Mathematics (or equivalent) or MATH 132

Restriction: Any pair (MATH 141 or QUAN 111) and (MATH 151 or 161 or 177) Coordinator: Dr Mark Johnston

Text: Croft, A., Davison, R., Hargreaves, M., & Flint, J. (2013).

Engineering mathematics. (4th ed.). Harlow, England: Pearson Stroud, K. A. (2013). Engineering mathematics (7th ed.). New York:

Palgrave McMillan.

An introduction to the range of mathematical techniques employed by engineers, including functions and calculus, linear algebra and vector geometry, probability and statistics. There is an emphasis on applications and modelling.

ENGR 122 CRN 26053 Engineering Mathematics 15 PTS Tri 2 With Calculus

Prerequisite: ENGR 121 or MATH 141 Restriction: The pair (MATH 142, 151) Coordinator: Dr Dimitrios Mitsotakis

Text: Croft, A., Davison, R., Hargreaves, M., & Flint, J. (2013) Engineering mathematics. (4th ed.). Harlow, England: Pearson Stroud, K. A. (2013). Engineering mathematics (7th ed.). New York:

Palgrave McMillan.

Further mathematical techniques employed by electronic and computer systems engineers, with emphasis on methods of calculus, differential equations and linear algebra. There is an emphasis on engineering applications and use of software.

ENGR 123 CRN 27044 Engineering Mathematics 15 PTS Tri 2 with Logic and Statistics

Prerequisite: ENGR 121

Restriction: The pair MATH 161, (MATH 177, QUAN 102 or STAT 193) Coordinator: Dr David Balduzzi

Text: TBA

Mathematical techniques employed by network and software engineers, including methods of combinatorics, logic, probability and decision theory. The course emphasises engineering applications of these techniques.

ENGR 142 CRN 27045 Engineering Physics for 15 PTS Tri 2 Electronics and Computer Systems

Prerequisite: (Approved levels of achievement in NCEA level 3 physics and calculus or equivalent) or (ENGR 121 or MATH 141; PHYS 122 or PHYS 131)

Coordinator: TBA

Physics theory and practice relevant to electronics and computer systems engineering.

Topics covered will include electrostatics (charge, force, field, potential), magnetic field and force, DC and AC circuits, electromagnetic induction and other selected topics. Lectures, assignments and laboratory work will all focus on the application of physics to engineering situations.

39 Victoria University of Wellington

MATH 132 CRN 17150 Introduction to Mathematical Thinking 15 PTS Tri 1 & 3 17286

Prerequisite: None

Restrictions: MATH 100-199, QUAN 103,111 Coordinator: Dr Dillon Mayhew

This course covers the fundamental skills and ideas required to study mathematics at university. Topics will include elementary arithmetic, algebra, geometry, functions, and an introduction to the basic ideas of differential calculus. There will be an emphasis on the history of mathematical ideas and how they have evolved: the goal is not only to apply mathematical tools correctly, but to understand them.

MATH 141 CRN 17151 Calculus 1A 15 PTS Tri 1

Prerequisites: 16 AS credits NCEA level 3 Mathematics (or equivalent) or MATH 132

Restrictions: ENGR 122, MATH 142, QUAN 111 Coordinator: Prof Matt Visser

The properties of functions of one variable and their use for modelling continuous phenomena, including ideas and applications of differential and integral calculus.

MATH 142 CRN 17160 Calculus 1B 15 PTS Tri 2

Prerequisite: MATH 141 or (NCEA Level 3 achievement standards 3.3 (trigonometry, AS91575), 3.6 (differentiation, AS91578) and 3.7 (integration, AS91579) and at least two should be with merit or excellence. Equivalent qualifications will be acceptable.

Coordinator: Dr Peter Donelan

Text (recommended): Anton, H., Bivens, I., and Davis, S., Calculus - Early

Transcendentals, Ninth or Tenth Edition, Wiley, 2009 or later Further topics in differential and integral calculus, including l’Hôpital’s Rule; Taylor

polynomials; implicit, parametric and polar representation of curves; the Riemann integral, techniques of integration; differential equations; functions or 2 variables and their properties.

MATH 151 CRN 17161 Algebra 15 PTS Tri 1

Prerequisite: 16 AS credits NCEA level 3 Mathematics (or equivalent) or MATH 132

Coordinator: Prof Rob Goldblatt

An introduction to linear algebra, including matrices and vectors, complex numbers and algebraic structures.

MATH 161 CRN 17162 Discrete Mathematics and Logic 15 PTS Tri 2 Prerequisite: 16 AS credits NCEA level 3 Maths (or equivalent) or MATH 132 Coordinator: Prof Geoff Whittle

Polynomials, complex numbers, and basic number theory will also be covered. The second half of the course is an introduction to graph theory, including trees and networks.

MATH 177 CRN 19803 Probability and Decision Modelling 15 PTS Tri 2 Prerequisites: 16 AS credits NCEA level 3 Mathematics or Statistics, including

AS 3.6 (differentiation, AS91578) and 3.7 (integration, AS91579), or MATH 141 or equivalent background in Mathematics.

Coordinator: Dr John Haywood

Course Materials: A suitable scientific calculator. Course notes, from Student Notes, cost approximately $15.

An introduction to probability models in statistics, decision making and operations research including key concepts of probability, random variables and their distribution, decision theory and queueing systems. Goodness of fit tests are used to check the validity of fitted models.

PHYS 114 CRN7534 Physics 1A 15 PTS Tri 1

Prerequisites: 12 credits of Mathematics including standards AS91578

(differentiation) and AS91579 (integration) or (MATH 141 or ENGR 121);

18 credits of NCEA level 3 Physics including standards AS91524 (mechanical systems) and AS91526 (electrical systems) and either AS91523 (wave systems) or AS91521 (practical investigation) or (PHYS 122 or 131)

Equivalent qualifications also accepted Coordinator: Dr Ben Ruck

Laboratories: 3 hours per week

Text: Serway Jewett, Wilson and Wilson. Physics, volume 1 (Asia and Pacific Edition), Cengage Learning. ISBN 9780170189309.

This course covers non-relativistic mechanics, wave motion and quantum mechanics using calculus-based mathematics. Topics include kinematics and dynamics, fundamental

conservation laws, rotational motion and oscillations, mechanical waves and an introduction to quantum physics.

41 Victoria University of Wellington

PHYS 115 CRN7535 Physics 1B 15 PTS Tri 2

Prerequisites: 12 credits of Mathematics including standards AS91578 (differentiation) and AS91579 (integration) or MATH 141;

Equivalent qualifications also accepted Coordinator: A/Prof Gillian Turner

Lecturers: A/Prof Gillian Turner, Dr Natalie Plank Laboratories: 3 hours per week

Text: Serway Jewett, Wilson and Wilson. Physics, volumes 1 and 2.

(Asia and Pacific Edition), Cengage Learning. ISBN 9780170189309 and 9780170189408.

This course builds on NCEA-level electromagnetism, electric circuits, geometric and physical optics, thermal properties of matter and thermodynamics, and their applications using

calculus-based mathematics.

PHYS 122 CRN18194 Introduction to Physics for 15 PTS Tri 1 Scientists and Engineers

Restrictions: PHYS 114, 115, 130, 131, 134, SARC 122 Coordinator: John Hannah

Lecturers: John Hannah, Dr Howard Lukefahr Laboratories: 3 hours per week

Text: Hewitt, Conceptual Physics, Harper Collins

PHYS 122 provides students who have little previous study in physics and/or mathematics with an introduction to physics, applied physics and quantitative methods. The course will include modules designed for students aiming to specialize in physics and engineering.

STAT 193 CRN STATISTICS FOR THE NATURAL 15 PTS 1/3

(SEE STREAMS) AND SOCIAL SCIENCES 2/3

Restrictions: MATH 277, QUAN 102 Coordinator: Dr Richard Arnold

Lecturers: Dr Yuichi Hirose, Dr Ivy (I-Ming) Liu, Dr Nokuthaba Sibanda

Streams: 1/3: Stream A (CRN 1791)

Stream B (CRN 11333) 2/3: Stream A (CRN 4442)

Stream B (CRN 6164)

Tutorials: 1 hour per week, TBA, including one Tagata Pasifika tutorial for Māori and Pacific students.

10 hours per week of help sessions (at times to be advised) will be available for individual assistance.

Assignments: An alternation of ordinary and practical data assignments Course materials: An approved graphics calculator is required—the Casio

fx-9750Gii is recommended (approximately $130) Text: Clark, M.J. & Randal, J.A, A First Course in Applied

Statistics: with applications in biology, business and social sciences, Pearson, 2004 (or 2011), approximately $85

An applied statistics course for students who will be advancing in other disciplines as well as those majoring in Statistics. It is particularly suitable for students majoring in Biological Science subjects, Geography, Linguistics, Psychology, social sciences such as Education, and is also suitable for BCA students. This course assumes no previous knowledge of Statistics, but Mathematics to Year 12 is preferred.

Topics covered include estimation, confidence intervals and hypothesis testing, comparison of means and proportions, simple regression and correlation, and analysis of variance.

43 Victoria University of Wellington

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