To provide students undertaking any type of degree study with an introductory knowledge of accounting and finance

Information Technology (IT) is rapidly achieving ubiquity in the workplace. All areas of the business community are achieving expansion in IT and investing huge sums of money in this area. The strategic nature of technology also means that managing IT has become a core competence for modern organisations and is therefore an important part of the task of general and functional managers.

This course aims to equip students with IT management skills for the workplace. By this, we refer to those attributes that they will need to make appropriate use of IT as general or functional managers in an information-based age.

Following on from the learning aims and objectives, the course is divided into two main parts: Part I considers why IT is strategic and how it can affect the competitive environment, taking stock of the opportunities and problems it provides. It consists of lectures, discussion, case studies. The objective is to investigate the business impact of IS.

Part II examines a variety of technologies available to the manager and examines how they have been used in organisations. A number of problem-oriented case studies will be given to project groups to examine and discuss. The results may then be presented in class, and are open for debate.

In summary, the aim of the course is to provide the knowledge from which students should be able to make appropriate use of computing and information technology in forthcoming careers. This necessitates some technical understanding of computing, but not at an advanced level.

To introduce the concepts of logic that underlie all mathematical reasoning and the notions of set theory that provide a rigorous foundation for mathematics.

By the end of this course, the students will be able to: understand and work with a formal definition; determine whether straight-forward definitions of particular mappings etc. are correct; determine whether straight-forward operations are, or are not, commutative; read and understand fairly complicated statements expressing, with the use of quantifiers, convergence properties of sequences.

Logic:

• Definitions and Axioms
• Predicates and relations
• Logical equivalence and logical consequence
• Direct and indirect methods of proof
• Proof by contradiction
• Counter-examples
• Analysis of statements using Semantic Tableaux
• Definitions of proof and deduction

Sets and Functions:

• Sets
• Cardinality of finite sets
• Countability and uncountability
• Maxima and minima of finite sets
• Unions, intersections, and/or statements and de Morgan's laws
• Functions as rules, domain, co-domain, image
• Injective (1-1), surjective (onto), bijective (1-1, onto) functions
• Permutations as bijections
• Functions and de Morgan's laws
• Inverse functions and inverse images of sets
• Relations and equivalence relations
• Arithmetic mod p.

Sequences:

• Definition and numerous examples
• Convergent sequences and their manipulation
• Arithmetic of limits

To introduce functional programming while drawing out the similarities with abstract mathematics.
To show that the mathematical thought process is a natural one for programming.
To provide a gentle introduction to practical functional programming.

Students should be able to write simple functions, to understand the nature of types and to use data types appropriately. They should also appreciate the value and use of recursion.

Expressions, choice, scope and extent, functions, recursion, recursive datatypes, higher-order objects.

To introduce students to the basic principles of computer operation and architecture.

Familiarity with the von Neumann model, the nature and function of each of the components, and general principles of operation of the machines, including input and output transfers and basic numeric manipulations.

To ensure students appreciate the concept of an algorithm as an effective procedure.
To introduce criteria by which algorithms may be chosen, and to demonstrate non-obvious algorithms.
To provide practical skills at reading and writing programs in ISO Standard C.

Students should be able to determine the time and space complexity of short algorithms, and know 3 sorting algorithms and 2 searching algorithms.

Students should be able to design, construct and test short programs in C, using standard libraries as appropriate. They should be able to read and comprehend the behaviour of programs written by others.

To provide practical skills in low-level programming and basic computer services

Algorithms:

• Introduction: Definition of an algorithm and characteristics of them.
• Basic Complexity: The efficiency of different algorithmic solutions.
• Best, average and worst case complexity in time and space.
• Fundamental Algorithms: Sorting and Searching.
• Space-time trade-offs.
• Graphs.
• Dijkstra's shortest path.

C Programming:

• Introduction: C as a simplified programming language
• ISO Standards
• Basic Concepts: Functions, variables, weak typing.
• Statements and expressions.
• Data Structuring: Enumeration, struct and arrays.
• Pointers and construction of complex structures.
• The preprocessor: #include, #if and #define

Programming:

• Input-output.
• Use of standard libraries.
• Multiple file programs.
• User interfaces.
• Professionalism: Coding standards, defensive programming, documentation, testing.
• Ethics.

To introduce students to the structure, basic design, operation and programming of conventional, von Neumann and non-von Neumann computers at the machine level.
To explore the correspondence between high level programming language control and data structures and what happens at the machine level.

To demonstrate an understanding of how the forms and conventions of high level languages are related to the machine level.
To experience how structured programming can be applied in low as well as high level languages.
To be able to assess the potential advantages and disadvantages of different architectures.

• Principles of digital computer operation: use of registers and the instruction cycle; simple addressing concepts; Integers and floating point numbers.
• Input and output.
• Introduction to digital logic.
• Aspects of modern computer architectures: Von Neumann and Non von Neumann architectures and modern approaches to machine design, including, for example, RISC (vs CISC) architectures.
• Topics in contemporary machine design, such as pipelining; parallel processing and multiprocessors.
• The interaction between hardware and software.
• Writing short assembler-level programs.

To provide students with a basic introduction to the mathematical skills necessary to tackle process engineering design applications.

To introduce students to the use of a workstation, to word-processing, spreadsheets and relational data bases, and to the basic ideas of computing, and to the range of applications and misapplications of computers in science.
To give students some experience of working in small groups.

Students should have a practical ability to use contemporary information management facilities. They should be able to write a good report, and they should have the confidence and the language to enable criticism of the use of computers in science.

• Introduction: hardware, software, networking
• Use of the workstation
• Social issues
• The relationship between computing and science
• Computers as calculators, as simulating engines, and as new realities
• Mathematical and computational models
• The difficulty of validating or criticising computational models
• Example of fluid flow, and the numerical wind tunnel
• Experiment and decision making using computational models
• Artificial intelligence, expert systems, neural nets, artificial evolution
• The use and abuse of computers in science
• Word processing
• HTML
• Scientific journalism and scientific reports
• The goals of succinctness and clarity
• Spreadsheets, organizing, exploring and presenting numerical data
• Introduction to Statistics: Mean, standard deviation, histograms, the idea of probability density functions

To introduce students to the use of a workstation, to wordprocessing, spreadsheets and relational databases, and to the basic ideas of computing, and to the range of applications and misapplications of computers in science.
To give students some experience of working in small groups.

Students should have a practical ability to use contemporary information management facilities. They should be able to write a good report, and they should have the confidence and the language to enable criticism of the use of computers in science.

• Normal and Poisson distributions
• A simple introduction to confidence intervals and hypothesis testing
• Elementary tools for dealing with non-normal data
• An introduction to correlation
• Computational experiments
• Databases
• Notations of set theory
• Data types and structures
• Hierarchical, network, and relational databases
• Some natural operations on relations: union, projection, selection, Cartesian product, set difference
• Design of relational databases
• Access as an example of a database system
• The integrated use of word processing, spreadsheets and relational databases