Title: Management Information Systems (mis)



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Title:

Management Information Systems (MIS)


Lecture hours:

30 hours of lectures + 20 hours of tutorial classes


Study period:

Winter or Summer semester


Level:

Basic


Location:

Wrocław


Examination:

Assignments and written test (the latter in case of a larger class when the originality of assignment answers cannot be fully validated).


Language:

English


Prerequisites:

N/A


Course content:

Management Information Systems is concerned with studies of “soft” aspects of computing and information systems and combines them with behavioural issues traditionally studied in management science, economics, sociology, and psychology. MIS is predominantly an applied endeavour that studies application and use of information systems in (and by) business, government and society at large.
Course topics:

  1. Information Systems in Global Business Today

    1. The Role of Informatics in Business Today

    2. Perspectives on Business Systems and Information Technology

    3. Contemporary Approaches to Information Systems

  2. E-Business: How Businesses Use Information Systems

    1. Business Processes and Information Systems

    2. Types of Business Information Systems

    3. Systems That Span the Enterprise

    4. The Information Systems Function in Business

  3. Information Systems, Organizations, and Strategy

    1. Organizations and Business Informatics

    2. Using Information Systems to Achieve Competitive Advantage

    3. Managing Information Systems

  4. Ethical and Social Issues in Information Systems

    1. Understanding Ethical and Social Issues Related to Systems

    2. Ethics in an Information Society

    3. The Moral Dimensions of Information Systems




Learning outcomes:

  • Understanding how information systems are transforming business and how do they relate to globalization.

  • Appreciation why information systems are so essential for running and managing a business today.

  • Thorough knowledge of what exactly is an information system and what are its management, organization, and technology components.

  • Understanding the relationships between business processes and information systems.

  • Identification how systems serve the various levels of management in a business.

  • Recognition of the differences between e-business, e-commerce, and e-government.

  • Recognition of the significance of using information systems to develop competitive strategies.

  • Appreciation of ethical, social, and political issues raised by information systems.

  • Understanding of how and why do contemporary information systems and technology pose challenges to the protection of individual privacy and intellectual property.

  • In depth inside into how information systems and technology affect everyday life.




Contact person:

Prof. Leszek A. Maciaszek

email: leszek.maciaszek@ue.wroc.pl



web: http://www.iie.ue.wroc.pl/lmaciaszek/en


Literature:

Laudon K., Laudon J., Management Information Systems : Managing the Digital Firm, 12th ed., Upper Saddle River, Pearson, 2012


Faculty:

This is a service course for all students



Czy przedmiot jest kopią przedmiotu prowadzonego na UE?

Tak:

  1. Informatyka w zarządzaniu (IwZ)
    II rok licencjat
    studenci różnych kierunków

  2. Podstawy systemów informacyjnych (PSI)
    I rok licencjat
    Informatyka w Biznesie







Title:

Systems Analysis and Design (SAD)


Lecture hours:

30 hours of lectures + 20 hours of mixed tutorial and practical sessions


Study period:

Winter or Summer semester


Level:

Basic


Location:

Wrocław


Examination:

Assignments and written test (the latter in case of a larger class when the originality of assignment answers cannot be fully validated).


Language:

English


Prerequisites:

  1. Understanding of principles of information systems.

  2. Understanding of fundamental information technologies.




Course content:

The course aims to provide an introduction to and competency in requirements acquisition, problem domain analysis and computer-based system design methods ensuring a close link between requirements and the resulting computer system. This course emphasises the skills of problem formulation, modelling and problem solving.
Course topics:

  1. Systems and Development Methodologies

    1. Types of Systems

    2. Integrating Technologies for Systems

    3. Need for Systems Analysis and Design

    4. The Systems Development Life Cycle

  2. The Software Development Process

    1. The Nature of Software Development

    2. System Planning

    3. Systems for Different Management Levels

    4. Systems Development Phases and Activities

  3. User Requirements Determination

    1. From Business Processes to Solution Envisioning

    2. Requirements Elicitation

    3. Requirements Negotiation and Validation

    4. Requirements Management

    5. Requirements Business Model

    6. Requirements Document

  4. Fundamentals of Systems Analysis

    1. Depicting Systems Graphically

    2. Modeling of Business Processes

    3. Modeling of Business Data

    4. Modeling of Business States

  5. Fundamentals of Systems Design

    1. Moving from Requirements to Software Solution

    2. Designing the System Architecture

    3. Designing the Data

    4. Designing the Software

    5. Designing the Graphical User Interface




Learning outcomes:

  • Understanding of various kinds of information systems and various approaches to development and integration of systems.

  • Awareness of the life cycle of system development.

  • Knowledge of requirements elicitation techniques and understanding of particular problem domains.

  • Ability to analyse the system requirements and build a logical model of the problem.

  • Appreciation of the importance of software and system architecture.

  • Ability to turn the logical model from the analysis phase into a design model from which a system can be built.

  • Recognition of how contemporary information technology and tools assist developers in production of information systems.




Contact person:

Prof. Leszek A. Maciaszek

email: leszek.maciaszek@ue.wroc.pl



web: http://www.iie.ue.wroc.pl/lmaciaszek/en


Literature:

MACIASZEK, L.A. (2007): Requirements Analysis and System Design, 3rd ed., Pearson, 642p. ISBN 978-0-321-44036-5


Faculty:

Management, Informatics and Finance



Czy przedmiot jest kopią przedmiotu prowadzonego na UE?

Tak:

  1. Analiza i Modelowanie Systemów Informacyjnych (AiMSI)
    I rok licencjat
    Informatyka i Ekonometria

  2. Analiza Systemów Informacyjnych (ASI)
    I rok licencjat
    Informatyka w Biznesie







Title:

Basics of Logistics in SAP ERP

Lecture hours:

20

Study period:

Both

Level:

Intermediate

Location:

Wrocław

Examination:

Computer test

Language:

English

Prerequisites:

Basics of Logistics

Course content:

The aim of the course is to introduce basic transactions of SAP ERP system. Main topics:

  1. Introduction to SAP ERP – installing the client, user interface, navigation

  2. Material Management

  3. Production Planning

  4. Sales and Distribution

Learning outcomes:

Rising demand for centralized information in the contemporary companies results in growing interest in integrated information systems. One of the best known solutions from this field is the SAP ERP system. Basic knowledge of this system is more and more often one of the important requirements in the recruitment procedure.

After completion of this course student will be able to:

  1. Navigate in SAP ERP user interface

  2. Use SAP Workplace

  3. Do basic operations from the field of logistics

  4. Find additional information about transactions in SAP ERP

Contact person:

Marek Kośny, e-mail: marek.kosny@ue.wroc.pl

Literature:

Dowling K.N., SAP project system handbook, McGraw Hill, 2008.

Mazzullo J., Wheatley P., SAP R/3 for Everyone: Step-by-Step Instructions, Practical Advice, and Other Tips and Tricks for Working with SAP, Prentice Hall, 2005

Faculty:

All

czy przedmiot jest kopią przedmiotu prowadzonego na UE?

tak

nazwa przedmiotu: Systemy informatyczne w logistyce - system R3

wydział: Zarządzania, Informatyki i Finansów

kierunek: Zarządzanie

specjalność: Logistyka

rok: III (LS)




Title:

Artificial Intelligence in Economics and Finance

Lecture hours:

Lectures: 15 hours; laboratories: 15 hours

Study period:

Winter and Summer semester

Level:

Master Studies

Location:

Wrocław

Examination:

Written exam and assignments

Language:

English

Prerequisites:

Basic notions in Computer Science and Economics

Course content:

Topics: Introduction to artificial intelligence. Problems and solutions, universal problem solver concepts. Methods of artificial intelligence overview. Knowledge representation and reasoning techniques in intelligent systems. Machine learning and inductive knowledge. Data and process mining techniques. Intelligent applications in economics and finance: decision support in management, economic predictions, market basket analysis, bankruptcy prediction, credit scoring.

Teaching methods: lectures, lab activities with intelligent system project preparation.



Learning outcomes:

The course will help students understand an essence and methods of artificial intelligence including application aspects. Course participants will learn:

  • what are the crucial properties of artificial intelligence approach,

  • how intelligent systems are designed and implemented,

  • what intelligent techniques and tools can be used to support decisions in management and finance

Contact person:

Prof. Jerzy Korczak, prof. Mieczysław Owoc

e-mail:< jerzy.korczak,mieczyslaw.owoc>@ue.wroc.pl

Literature:

Luger G., Artificial Intelligence: Structures and strategies for Complex Problem Solving, Pearson Education 2009.

Turban E., Aronson J.E, Liang T-P: Decision Support Systems and

Intelligent Systems (7th Edition). Prentice Hall, 2004

Russel S., Norvig P., Artificial Intelligence: A Modern Approach, Prentice Hall, 2009.

Voges K, Pope L., Business Application and Computational Intelligence, Idea Group Pub., 2006

Witten, J., Eibe, F. : Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations, Morgan Kaufmann, 2005.

Binner J.M, Kendall G., Chen S-H.: Applications of Artificial Intelligence in Finance and Economic. Emerald Group Publishing Limited,2005

Faculty:

Management, Computer Science and Finance

czy przedmiot jest kopią przedmiotu prowadzonego na UE?

tak

częściowo - nazwa przedmiotu: Podstawy sztucznej inteligencji

wydział: ZIF

kierunek: Informatyka i ekonometria, Informatyka w biznesie

specjalność:

rok:




Title:

DATABASES

Lecture hours:

15 lectures + 15 labs

Study period:

Whole year

Level:

Basic

Location:

Wrocław

Examination:

Written form: Report prepared by students confirming a designed database application and/or multiple choice question – single answer test

Language:

English

Prerequisites:

Fundamentals of computer science and optionally: Information Systems Design, Computer Networks

Course content:

Topics: Basic concepts of databases. Database infrastructure. Query languages overview. SQL – an universal access language to modern databases. Query and transaction processing. Advances topics of databases: distributed databases, post-relational databases. Universal DBMS server and future trends in databases.

Teaching methods: lectures, lab activities with database project preparation.



Learning outcomes:

Understanding an essence and features of database technology.

Ability to model and define a database for the specific domain.

Capability to process a database using queries (with SQL commands).

Basic knowledge about processing modern databases (using transactions and queries respecting database features) on universal database servers).

Orientation in future trends in database technology.

Contact person:

Prof. Mieczysław Owoc, Maciej Pondel Ph.D. (mieczyslaw.owoc,maciej.pondel)@ue.wroc.pl; phone: 36-80-503, building Z, room. 602,614;

Literature:

Connolly T.M, Begg C.E.: Concepts of Database Management. Addison-Wesley , Reading 2009

Coronel C., Morris S., Robb P.: Database Systems: Design, Implementation, and Management. Course Technology Cengage Learning, Boston 2013

Hoffer A.A, Prescott M., Topi H.: Modern Database Management. Addison-Wesley, Reading, 2008

Kroenke D.M., Auer D.: Database Concepts. Prentice-Hall, Englewood Cliffs, 2009

Silberschatz A., Korth H.F., Sudarshan S.: Database System Concepts. McGraw-Hill 2010

Taylor A.G.: SQL For Dummies. Wiley Publishing, 2010

Faculty:

All students

czy przedmiot jest kopią przedmiotu prowadzonego na UE?




tak - nazwa przedmiotu: Bazy danych

wydział: ZIF

kierunek: Informatyka i ekonometria; Informatyka w biznesie

specjalność: wszystkie

rok:II




Title:

Probability

Lecture hours:

30 (20+10) [minimal number of students – 10]

Study period:

Both summer and winter terms

Level:

Basic

Location:

Wrocław

Examination:

Test (in writing)

Language:

English

Prerequisites:

Algebra, Analysis

Course content:

Probability space, random events as sets;

Definitions of probability measures;

Conditional probability and Bayes’ rule;

Independence of random events;

Distributions and their parameters;

Correlation and independence of random variables;

Limit theorems.

Learning outcomes:

Understanding of uncertainity and statistical approaches, distinguishing more and less probable possibilities.

Contact person:

Dr inż. Albert Gardoń, B-6, Albert.Gardon@ue.wroc.pl

Literature:

Pitman J. “Probability”. Springer, New York 1993.

Lupton R. “Statistics in Theory and Practice”. Princeton U. P. 1993.

McClave J.T., Dietrich F.H. “Statistics”. Dellen, San Francisco 1988.

Faculty:

All

czy przedmiot jest kopią przedmiotu prowadzonego na UE?

nie

tak - nazwa przedmiotu: Rachunek prawdopodobieństwa

wydział: ZIF

kierunek: wszystkie

specjalność: wszystkie

rok: 1 lub 2




Title:

Statistics

Lecture hours:

30 (20+10) [minimal number of students – 10]

Study period:

Both summer and winter terms

Level:

Basic

Location:

Wrocław

Examination:

Test (in writing)

Language:

English

Prerequisites:

Mathematics, Probability

Course content:

Ordering statistical data, empirical density and distribution functions;

Estimation, basic statistical measures (mean, variance, skewness, correlation);

Linear regression model;

Confidence intervals;

Statistical tests (parametric and non-parametric).

Learning outcomes:

Ability for making statistical inferences, knowing the basis of data analysis, using mathematical tools in decision making.

Contact person:

Dr inż. Albert Gardoń, B-6, Albert.Gardon@ue.wroc.pl

Literature:

Lupton R. “Statistics in Theory and Practice”. Princeton U. P. 1993.

McClave J.T., Benson P.G. “Statistics for Business and Economics”. Dellen, San Francisco 1985.

Faculty:

All

czy przedmiot jest kopią przedmiotu prowadzonego na UE?

nie

tak - nazwa przedmiotu: Statystyka

wydział: wszystkie

kierunek: wszystkie

specjalność: wszystkie

rok: 1 lub 2




Title:

INTELLIGENT SYSTEMS

Lecture hours:

15 lectures + 15 labs

Study period:

Whole year

Level:

Basic

Location:

Wrocław

Examination:

Written form: Report prepared by students confirming a designed intelligent application and/or multiple choice question – single answer test

Language:

English

Prerequisites:

Databases, Basics of Problem-Solving

Course content:

Topics: Introduction to artificial intelligence. Problems and solutions, universal problem solver concepts. Taxonomy and properties of intelligent systems. Approaches to intelligent systems development. Knowledge representation and validation techniques. Architecture of expert systems. Machine learning and inductive knowledge. Modern intelligent systems and its applications: neural nets, evolution algorithms, agent systems.

Teaching methods: lectures, lab activities with an intelligent application preparation.



Learning outcomes:

Understanding an essence and specialty of intelligent systems. Basic knowledge about intelligent systems development including different intelligent techniques. Ability to represent a domain knowledge and to conclude with the defined problem area. Orientation in modern and future trends in artificial intelligence applications.

Contact person:

Prof. Mieczysław Owoc, mieczyslaw.owoc@ue.wroc.pl; phone: 36-80-503, building Z, room. 602

Literature:

1. Schalkoff R.J.: Intelligent Systems: Principles, Paradigms and Pragmatics. Jones and Bartlett Publishers, 2011

2. Turban E., Aronson J.E, Liang T-P: Decision Support Systems and

Intelligent Systems (7th Edition). Pearsons, Prentice Hall, 2005

3. Russell S., Norvig P.: Artificial Intelligence: A Modern Approach.

Prentice-Hall, 2002

4. Hopgood A.A.: Intelligent Systems for Engineers and Scientists. Taylor & Francis Group, LLC 2012

5. Negnevitsky M.: Artificial Intelligence: A Guide to Intelligent Systems.

Addison-Wesley, 2004

6. Jones M.T.: Artificial Intelligence. A Systems Approach. Infiniti Science Press, 2008

Faculty:

All students

czy przedmiot jest kopią przedmiotu prowadzonego na UE?




częściowo - nazwa przedmiotu: Podstawy sztucznej inteligencji

wydział:ZIF

kierunek:Informatyka i ekonometria; Informatyka w biznesie

specjalność: wszystkie

rok:II




Title:

Data Warehouses (DW)

Lecture hours:

15 lectures + 15 labs

Study period:

Whole year

Level:

Basic

Location:

Wrocław

Examination:

Written form: Report prepared by students confirming performed data warehouse applications and/or multiple choice question – single answer test

Language:

English

Prerequisites:

Fundamentals of computer science and relational databases

Course content:

Basic concepts of data warehouses, data, warehouse architecture, data models in DW, ETL, designing of DW, data warehouse types, future trends in data warehousing

Learning outcomes:

Understanding an essence and features of data warehouses technology, ability to model and define a data warehouse for a specific domain, ability to project a data warehouse using Oracle Warehouse Builder, orientation in future trends in data warehousing

Contact person:

Małgorzata Nycz, Ph.D. hab. prof.UE, malgorzata.nycz@ue.wroc.pl ;

Phone: 36-80-507, building Z, room 612

Literature:

Inmon W.H.: Building the Data Warehouse, Wiley&Sons, 2002

Kimbal R., Ross M.: The Data Warehouse Toolkit, The Complete Guide to Dimensional Modeling, Wile&Sons, 2010

TodmanC.: Designing a Data Warehouse, Prentice Hall, 2011

Kimbal R.: The Data Warehouse Lifecycle Toolkit, Wiley&Sons, 2009

Rittman M.: Oracle Business Intelligence 10g Developers Guide, 2012

Faculty:

All students

czy przedmiot jest kopią przedmiotu prowadzonego na UE?




tak - nazwa przedmiotu: Hurtownie danych, Data Warehouses w ramach Databases

wydział: ZIF

kierunek: Informatyka i Ekonometria, Informatyka w biznesie

specjalność: wszystkie

rok: II, I




Title:

Business Forecasting

Lecture hours:

30 workshops

Study period:

Winter semester

Level:

Basic

Location:

Wrocław

Examination:

test

Language:

English

Prerequisites:

Basic statistics and econometrics

Course content:

  1. Basic concepts of forecasting (forecast functions, forecast and forecasting, forecast basis, types of forecast, steps in the forecasting task)

  2. Forecasting data statistical adjustment and analysis (transformation, aggregation, completion of the missing data, identifying outlying observations, turning points, and data pattern – ACF and PACF functions)

  3. Time series decomposition (principles of decomposition, moving averages, classical decomposition, Census Bureau methods)

  4. Forecasting based on smoothing methods (averaging: mean-as-forecast, moving average, double moving average; exponential smoothing methods: single exponential smoothing, adaptive-response-rate single exponential smoothing, Holt’s linear model, Winter’s model)

  5. Trend – line forecasting (choosing a curve, building and evaluating a model, setting a forecast, measuring forecast accuracy, setting a predicting interval)

  6. Trend – seasonality forecasting (types of seasonal pattern, building and evaluating a model with seasonal rates)

  7. Forecasting using ARIMA models (model identification – ACF and PACF function, estimating and evaluating a model, setting a forecast, measuring forecast accuracy)

  8. Forecasting using simple and multiple regression (forecasting assumptions, building and evaluating a model, setting a forecast, measuring forecast accuracy, setting a predicting interval)

  9. Qualitative variables in regression analysis (probit transformation, regression of seasonality)

  10. Forecasting the long term (analogies, leading indicators)

  11. Judgmental forecasting (choosing the experts, testing the level of agreement among experts, the Delphi Method, the Brain Storm Method, personal probability, formal models II type)

  12. Scenario building (types of scenarios, construction steps, examples)

  13. Corporate forecasting system (system’s function and construction, combining statistical and judgmental forecast, forecast monitoring and revision)

Contact person:

dr Aleksandra Szpulak, Department of Economic Analysis and Forecasting

Literature:

  1. M.P. Clements, D.F. Hendry: “A companion to economic forecasting” Blackwell Publishers 2002

  2. J.C. Compton, S.B. Compton: “Successful business forecasting” Liberty Hall Press 1990

  3. C.W.J. Granger: “Forecasting in business and economics” Academic Press, San Diego 1989

  4. S. Makridakis, S.C. Weelwright, R.J. Hyndman “ Forecasting. Methods and Applications” John Wiley & Sons. Inc., New York 1998

Faculty:

Finance, marketing, management

czy przedmiot jest kopią przedmiotu prowadzonego na AE?




tak – nazwa przedmiotu: Prognozowanie i symulacje, Prognozowanie finansowe

wydział: NE, ZI

kierunek: all

specjalność: all

rok: IV(lub III)





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