The following is a brief overview of the modules taken in Junior Sophister year. Current students should refer to my.tcd.ie for full details, including assessment criteria and learning outcomes.
|ST3001 Software Applications III|
|ST3002 Statistical Analysis III|
|ST3004 Research Methods|
|ST3005 Information Systems|
|ST3011 Applied Forecasting|
|ST3008 Management Science Case Studies|
|CS3012 Software Engineering|
This course will introduce students to Visual Basic programming and students will use Visual Basic to learn how to build small software applications. The course will also give students experience in client server database technologies. This course will be based on various databases such as MySQL and Microsoft Access. The course will introduce students to writing database queries using SQL. HTML and PHP will be used to develop user front ends to these databases.
This module aims to provide an opportunity for students to develop their hands on skills in data analysis. Specific methods will be explored to illustrate these approaches. Module content includes the binomial, poisson, multinomial distributions, model based methods and graphical techniques.
Upon completing this module, students should have an understanding of the nature of the research process, drawing upon primary and secondary data sources; be able to locate, analyse and interpret quantitative and qualitative data; and to present the findings.
The objective of this module is to introduce students to information systems in business and examines how management information and decision support systems can support improved organisational performance. Information security and control surrounding these systems and aspects of ethical use of IT are also covered. Specific topics addressed in this module include: Business Processes, Transactions and Information; Introduction to telecommunications and network systems; Emerging Technology; Data Warehousing; Decision Support Systems; Business Intelligence; Digital Markets/Digital Goods; Introduction to Information Systems Security and Information Technology and Ethics.
This module covers classical multivariate techniques of discriminant analysis, principal component analysis, clustering and logistic regression are examined. There is a strong emphasis on the use and interpretation of these techniques. More modern techniques, some of which address the same issues, are covered in the SS module Data Analytics.
In this module several methods of forecasting will be examined, including exponential smoothing and its Holt-Winters extension, auto-regression, moving average, and further regression based methods that take into account seasonal trends of lagged variables (ARIMA). The module will be practical, and will involve every student in extensive analysis of case study material for a variety of time series data.
The overall aim of CS2011 is to develop studentsí interpersonal, teamworking and analytical skills. This is a problem based learning module. It requires students to apply what they have learned in other modules in MSISS in a simulated real life problem. Specific topics addressed include team working, interviewing, problem solving, conflict resolution, reporting writing and self organising skills.
This module provides students with a solid grounding in various aspects related to building large, important software systems. The overall aim of this course is for students to learn the fundamental skills for building large, important software systems. This entails (i) to recognise the general software lifecycle and its stages from domain analysis to maintenance, (ii) to analyse software in the problem domain, (iii) to identify the fundamental approaches to managing software projects and teams, (iv) to distinguish the roles of stakeholders in a software project in general and in software teams in particular, (v) to recognise architectures for building large-scale distributed software systems. This course covers various aspects related to building software systems ranging from the use of software lifecycle models, to project management, to large-scale software architectures. Specifically, software lifecycle models, including variations of the waterfall and spiral models as well as extreme programming and agile, are introduced along with concepts that are relevant to the specific model stages. These concepts include UML-based O-O, and domain analysis, requirements and specification analysis, testing and debugging, and version control. Moreover, strategies for managing large software projects and their contracts as well as project teams are presented and contrasted.
The aim of this module is to develop a deeper understanding of financial accounting and an appreciation for the application of accounting standards, as well as providing information for decision-making and cost-volume profit analysis.
The module is divided into 3 parts:
a. Double Entry Accounting System
In developing a deeper understanding of financial accounting and to fully appreciate the application of accounting standards it is necessary to understand the double entry accounting system. This part of the module will include the essential features of the double entry system from the books of prime entry through to the preparation of financial statements.
b. International Accounting Standards
This section of the module will cover International Accounting Standards both in terms of theoretical knowledge and practical application. This section of the module is a significant development from the knowledge base acquired in the Senior Freshman module, Introduction to Accounting and Financial Management. Prior to embarking on the standards, the Regulatory and Conceptual framework will also be addressed
c. Introduction to Management Accounting
Management accounting deals with the information needs of internal management as distinct from financial accounting which in the main is directed at the needs of external user groups. This section will address the budgeting process, including the management role it plays within organizations. In addition, the practical issue of the preparation of the budget from initial sales forecast to final budgeted income statement, cash flow and balance sheet will be studied. One of the primary objectives of management accounting is to provide information for decision-making and cost-volume profit analysis will be studied as one such example of how the management accounting function can aid short-term decision- making.
This module aims to:
- describe the professional area of work that is concerned with managing employees and their work in organizations;
- contextualize the practice of HRM in the Irish/EU employment law and industrial relations environment;
- expand upon the practices of HRM ( recruitment, training , reward , evaluation) in organizations,
- understand the importance of national, environmental and strategic context for the creation and implementation of HR strategy in organizations.
This is a survey module in financial management and covers topics such as bond pricing, types of fixed interest instruments, Equity Markets, Hedging and International Finance.
This module analyses, at both a practical and theoretical level, the process of investment in financial markets. Its aims are to introduce students to the various types of financial instruments in common use and to the economic theories that explain how they are priced. The types of securities considered include interest-bearing securities, equities and derivatives (options, futures, etc.). The focus for the first half of the module will be on fixed income securities and derivatives. As we will see, the principles to be discussed and the analytical tools to be presented have a much wider application in making decisions under conditions of uncertainty. Students are also required to complete a project involving the collection and analysis of financial data. The second half of the module explores how financial markets operate and how securities are bought and sold. The trade-off between higher average returns and more `risky' pay-offs is then discussed. The problem of determining an optimal investment strategy, given beliefs about the probability distribution of returns, is also addressed. Other issues considered include the informational efficiency of financial markets and systematic pricing failures, the role of behavioural biases, and the relative usefulness of fundamental analysis and technical analysis in predicting price movements. This module does not assume previous knowledge of financial economics and for the most part the level of mathematics and statistics does not extend beyond SF Maths and Stats. Students should note, however, that this is an analytical economics module that makes constant use of tools derived from mathematical and statistical concepts. Students interested in working in areas related to investment and finance are likely to find the course of value for their career.
This module provides students with a broad overview of intermediate-level economy theory, covering both microeconomic theory and macroeconomic theory.
The first part of the module addresses microeconomic theory. The material is built around the study of economic agents (e.g. consumers or producers) maximizing objectives (e.g. utility or profits) in an environment of economic constraints (e.g. income or costs). The theory will be supported by a number of applications (e.g. labour leisure choice or consumption-savings choice).
The second part of the module addresses macroeconomic theory. The material is built around the study of the behaviour of the economy as a whole. The approach is based on microeconomic foundations and progresses from individual maximization problems, as studied in the microeconomics module, to macroeconomic issues and issues confronting the aggregate economy.
This module will describe the fundamentals of probability theory, from the basic axioms of probability to the most commonly used aspects and theorems of the theory. The module covers: Events and Probabilities; The laws of probability; Independence and conditional probability; Discrete random variables; Probability generating functions; Continuous random variables; Multivariate distributions & independence; Moment and characteristic generating functions; The law of averages and The central limit theorem.
Uncertainty and/or variation that is random or unpredictable is a central challenge in devising efficient systems. This course aspires to build confidence in the modelling and manipulation of uncertain information. The central tool is the use of probability to model or approximate a system.
In this course we take a novel approach that reinforces a mathematical introduction to probability with the use of the Monte Carlo method (http://en.wikipedia.org/wiki/Monte_Carlo_method). Students will rapidly acquire the facility to model quite complex stochastic systems. They will subsequently exploit probability to by-pass such methods, or render them more efficient.
Engineering Mathematics V is a one-semester module available to all JS Engineering streams and continues and extends the material from the previous mathematics modules in the first and second years - 1E1, 1E2, 2E1 and 2E2. The emphasis is primarily on the development of analytical techniques. The module covers Fourier Methods, Partial Differential Equations and Optimisation.
This module provides a general introduction to operations management of manufacturing systems. It will explore strategies for operating and optimising the production of products in different varieties and volumes with limited resources and in competitive environments. The impacts of design decisions on manufacturing performance and the physical organisation of plants are explored through various DFM and plant layout strategies.
Formal project management methods will be introduced reflecting the growing use of continuous improvement through project management.
Note: option choices may be subject to change and, due to timetable constraints, students may not always get their first choice.
Note: module overviews may be subject to change