جامعة الخليل - برنامج تكنولوجيا المعلومات وادارة الانظمة

كلية الدراسات العليا

وصف المساقات

T1711    Strategic Planning for Information Systems   التخطيط الاستراتيجي لأنظمة المعلومات

Intended learning objectives and outcomes of the curricular unit:

The main objectives are:

  • The students will understand the fundamental aspects related to planning of information systems, including analysis, design and implementation of the IS strategy, in order to put the SI at the service of business objectives;
  • To understand the applicability of the models used to design the organizations information systems strategy, the process inherent in the development of action plans, as well as analysis of the benefits, costs and risks associated with the use of SI.

And the outcomes of this course are:

  • To Know how to interpret the strategic organizations, positioning its SI in terms of efficiency and strategic value and how to characterize its alignment with the objectives and needs of the company;
  • To Know how to apply the concepts and methodologies for establishing action plans and requirements for technological and organizational reform to support the company's strategy.

Syllabus:

  1. The changing role of ITS in Organizations - Strategic Perspective;
  2. Business Strategy Concepts and Implications for Strategy of ITS;
  • ITS Strategy Development - Establish effective procedures;
  1. Evaluating the current situation with regard to ITS in the Organization;
  2. Determination of the future potential of ITS;
  3. Conceptual frameworks for planning ITS;
  • Managing the Applications portfolio;

Demonstration of the syllabus coherence with the curricular unit’s intended learning outcomes. Contents I and II help to achieve (obj. 1) and provide students with outcome 1; The remaining contents are designed to help students to reach objective 2 and acquire competencies related with outcome 2.

Teaching Methodologies (including evaluation):

Expository classes complemented with case studies and the analysis of scientific articles on the matters addressed. Students will be assessed on the basis of a written test (60%) and a group project (40%).

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes.

We feel that a multiple methodology must be adopted in order to suit the teaching methodology to the subject’s objectives. Accordingly, we will use the expository method to present the theoretical concepts required to understand the subjects and the case study method to encourage reflection (preparation of case studies and scientific articles before class) and inter-activity among the students in-class.

Bibliography/Literae:

Kenneth C. Laudon and Jane P. Laudon (2015) Management Information Systems: Managing the Digital Firm (14th Edition). 14th Edition. Pearson.  ISBN: 978-0133898163.

John Ward e Joe Peppard, (2002). Strategic Planning for Information Systems, Cranfield School of Management. John Wiley & Sons, Ltd, Third Edition. 624 páginas. (ISBN 0 470841478).

Robert Galliers, e Dorothy Leidner (2003). Strategic Information Management – Challenges and Strategies in Managing Information Systems. Butterworth Heinemann, Third Edition.

 

 

T2712   Systems and Technologies 2.0   أنظمة وتقنيات الويب 2.0                                     

Intended learning objectives and outcomes of the curricular unit:

This course aims to:

  1. Deepen the concepts of systems and technologies Web 2.0 such as wikis, social networks and blogs;
  2. To introduce Web 2.0 standards and understand their use in organizations;
  3. Analyze the benefits of Web 2.0 applications in existing businesses and government;
  4. Implement the concepts acquired during the course in the wiki technology.

 

The outcomes to be acquired are as follows:

  1. To enable students to understand how the systems and technologies Web 2.0 add value to companies;
  2. To enable students to identify the needs of different organizations with regard to systems and technologies Web 2.0;
  3. To develop the ability to learn and implement new technologies.

Syllabus:

  1. From Web 1.0 to Web 2.0: Examples of applications
  2. Web 2.0 technologies
    • Really Simple Syndication (RSS)
    • Service Oriented Architecture (SOA)
    • Software as a Service pattern (SaaS)
    • Cloud Computing
    • Participation-Collaboration Pattern
    • AJAX
    • Mashups
    • Rich User Experience (or RIA)
    • Collaborative Systems labels (Folksonomy)
    • Sharing information and knowledge (Wiki)
  • Social Networks
    • FOAF
    • hCard and XFN
    • The Facebook Platform
    • Blogging, microblogging, forums and software for messaging
  1. Web 2.0 Applications in Business and Government
    • Government 2.0
    • Medicine 2.0
    • Travel 2.0
    • Library 2.0

Demonstration of the syllabus coherence with the curricular unit’s intended learning outcomes.

  • The first goal is achieved with the study of the syllabus from 1 to 5.
  • The second goal is achieved with the study of the syllabus 2 and 4.
  • The third goal is achieved by studying the syllabus 6.
  • The fourth goal is achieved by studying the syllabus 3.

Teaching methodologies (including evaluation):

  1. Lectures on the topics listed in the syllabus;
  2. Discussion of case studies of companies that use systems and technologies 2.0;
  3. Analysis of scientific papers on the use of systems and technologies of Web 2.0 in business;
  4. Presentation of works by students;
  5. Follow the development of students' work;
  6. Practical exercises with Web 2.0 technologies (e. creation, use and management of wikis). Evaluation: Test (60%), written work group (20%) and practical work group (20%)

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes.

  • Teaching methods 1, 2 and 3 are consistent with the objectives 1 and 2;
  • The teaching method 2 is consistent with the objective 3;
  • Teaching methods 5 and 6 are consistent with the objective 4.

Bibliography/Literature:

  • Liyang Yu (2015) A Developer’s Guide to the Semantic. ISBN: 978-3662437957.
  • Daniel Power (2013) Decision Support, Analytics, and Business Intelligence. Second Edition. Business Expert Press. ISBN: 978-1606496183.
  • Breslin, John , Passant, Alexandre, Decker, Stefan (2010). The Social Semantic Web. Springer, 300 p. ISBN-13:978-3-642-01171-9.
  • Shelly, Gary e Frydenberg, Mark (2010). Web 2.0: Concepts and Applications. CourseTechnology; 1st edition, 312 p. ISBN-13: 978-1439048023.
  • Bernal, Joey (2009). Web 2.0 and Social Networking for the Enterprise: Guidelines and Examples for Implementation and Management within Your Organizatio IBM Press, first edition, 312 p. ISBN-13: 978-0137004898
  • Governor, James; Hinchcliffe, Dion e Nickull, Duane (2009). Web 2.0 Architectures: What Entrepreneurs and Information Architects Need to Know. O'Reilly; 1st edition, 272 p. ISBN-13: 978-0596514433
  • Funk, Tom (2008). Web 2.0 and Beyond: Understanding the New Online Business Models, Trends, and Technologies. Praeger. 192 p. ISBN-13: 978-031335187

 

 

 

T3713   Telecommunications Networks and Information Security  شبكات الاتصالات وامن المعلومات                 

Intended learning outcomes of the curricular unit:

Students should acquire deep knowledge about problems related with Data Communications Security between computers in a network; main vulnerabilities and threats to the information flow between network computers, as well as the most adequate countermeasures.

Syllabus:

Introduction to Data Communications; Reference Models: ISSO/OSI and TCP/IP; Threats; Vulnerabilities;

Cryptography; Hash functions; Authentication; Authorization; Security Protocols.

Demonstration of the syllabus coherence with the curricular unit’s intended learning outcomes.

Following and taking advantage of the Communications Networks courses within the major program, this course intends to give the students a clear notion of the mos relevant problems of modern days’ communications systems, its vulnerabilities, the threats they are subject to and possible measures to be taken in order to minimize the risks arising from these issues.

Teaching methodologies (including evaluation):

Students should attend theoretical/practical classes where the basic concepts will be delivered. During classes, exercises related to the previously transmitted theory will be solved. These exercises shall, as much as possible, depict real, although simple, situations.

On their own time, students will, also, develop more complex team projects in order to drive the acquisition of adequate skills regarding what will, most certainly, be their future work experience. Grading will be the result of a written test (65%), a team project (25%) and the students’ ability to orally present it (10%).

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes.

The combination of simple exercises and more complex team projects will allow the students to achieve an, as deep as possible, knowledge on how to apply the set of different techniques that have been learned as a way to solve complex problems which will surely wait for them after entering professional life.

Bibliography/Literature:

  • Kurose JF and Ross K.W. (2013) Computer Networking - A Top-Down Approach (6th Edition). Pearson.
  • Tanenbaum A.S. and Wetherall D.J. (2010). Computer Networks (5th Edition). Pearson.
  • Stamp, ; Information Security: Principles and Practice; Wiley; 2ª Ed.; 2011
  • Zúquete, Segurança em Redes Informáticas; FCA; 3ª Ed.; 2010.
  • Forouzan, B.; Data Communications and Networking; McGraw-Hill; 4ª Ed.; 2007
  • Easttom, C.; Computer Security Fundamentals; Prentice Hall; 2005
  • Kaufman, C., Perlman, R., Speciner, ; Network Security: Private Communication in a Public World; Prentice Hall; 2002

 

 

 

T1715    Advanced Statistics طرق الإحصاء المتقدم                                                       

Intended learning outcomes of the curricular unit:

The purpose of this course is to provide students with the necessary competences, in order to develop a master thesis based on quantitative methods.

Syllabus:

  • Basic notions of descriptive statisti Population and sample. Frequencies tables. Graphic representation of data. Localization parameters. Dispersion parameters. Symmetry parameters. Curtose measures. Applications with SPSS.
  • Correlation and Linear Regression. Graphic representation – dispersion diagram. Covariance e correlatio Simple linear regression models.
  • Applications on SPS Minimum squares method. Interpretation of the coefficients a e b. Previsions with the regression line. Applications on SPSS. Estimation Punctual estimation.
  • Estimation by interval Hypothesis Tests. Parametric tests. Non-parametric tests.

Demonstration of the syllabus coherence with the curricular unit’s intended learning outcomes.

For each statistical concept that is presented we consider its utility, implementation and principal caractheristics and properties. Complemented with the applications to specific situations, shows coherence with the targets of the unit’s objectives.

Teaching methodologies (including evaluation):

We use the expositive method. There are three written tests with percentage 20%, 20% and 60%, respectively. As an alternative, the students can present to a final exam, with percentage 100%.

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes.

We use the expositive method, complemented with the demonstrative method. The methodology used in order to the students understand the main concepts and theoretical results, is the following:

  • Motivation through examples
  • Theoretical presentation of the concept
  • Resolution of applied examples
  • Applications to economy.

Bibliography/Literature:

  1. Balakrishnan, N. Handbook of the Logistic Distributi [S.l.]: Marcel Dekker, Inc.,1991.
  2. Guimarães, Rui & Cabral, José (1999), Estatístic Lisboa: McGraw-Hill.
  3. Hosmer, David W. Applied Logistic Regression, 2nd ed. [S.l.]: New York; Chichester, Wiley,

Murteira, Bento & et al (2004), Introdução à Estatística, Lisboa: McGraw Hill."Anexo IV - Métodos de Avaliação de Investimentos em SI/Information Systems Evaluation Methods

 

 

 

T1721   Information Systems Evaluation Methods     أساليب تقييم نظم المعلومات               

Intended learning outcomes of the curricular unit:

The main objectives of this course are investment evaluation of Information Systems projects:

  • To define context, return of investments and associated risks;
  • To understand the benefits and adequacy of the assessment mo

The expected outcomes are the acquisition of competencies and skills:

Syllabus:

  • Concept of Total Cost Ownership (TCO);
  • The State of Enterprise TCO, The Value associated with technology adoption;
  • The evaluation of risk in IT investments;
  • The TCO Method Used by Software Decisions 
  • Using TCO for Better Decision Making

Demonstration of the syllabus coherence with the curricular unit’s intended learning outcomes.

The topics 1 to 4 of the syllabus are according with competencies outcome 1) and the topic 5 of the syllabus are related with competency outcome 2.

Teaching methodologies (including evaluation):

Explanatory classes complemented by case studies. Analysis and discussion of scientific    papers and management and expert opinions on the topics covered. Students will be assessed on the basis of a written test (60%) and a group project (40%).

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes.

The teaching methods that led to the allocation of students with the knowledge contained in   the basic concepts used in the preparation and evaluation of investment projects in  information systems, and the application of such concepts in the preparation of casestudies  and discussion in class, have full consistency with the objectives of thecourse. Students will be given to the necessary expertise and sufficient to develop and evaluate investment  projects in information systems.

Bibliography/Literature:

  • PE, C., Mr. Dean Fanning. (2014). Life Cycle Costing: How to calculate life cycle costs and total ownership Cost. Create Space Independent Publishing Platform.
  • Peppard, J., & Ward, J. (2016). The Strategic Management of Information Systems: Building a Digital Strategy. John Wiley & Sons.
  • Rodríguez, A., Ortega, F., & Concepción, R. (2016). A method for the evaluation of risk in IT projects. Expert Systems with Applications, 45, 273–285. https://doi.org/10.1016/j.eswa.2015.09.056
  • Snapp, S. (2013). Enterprise Software TCO: Calculating and Using Total Cost of Ownership for Decision Making. SCM Focus.

Ukai, Y. (Ed.). (2005). Economic Analysis of Information System Investment in Banking Industry (2005 edition). Tokyo ; New York: Springer

 

 

T1722   Advanced Topics in Information Systems for Management   مواضيع متقدمة في نظم المعلومات الادارية        

Intended learning outcomes of the curricular unit:

This discipline provides an overall perspective and characterizes the diverse types of Information Systems that organizations can plan, develop, implement and use in their business processes.

  • To enable students to select and implement systems in organizations to support the globalization of business, enterprise resource planning systems (ERP) Customer Relationship Management systems(CRM) systems to support the relationship with suppliers; systems to support the relationship with the public administration;
  • To enable students to understand the various decision support systems used in organizations.

Syllabus:

  • Information systems to support the globalization of business;
  • Information systems to support the relationship with customers;
  • Information systems to support the Integrated Enterprise Resource Management;
  • Decision Support Systems;
  • Information systems to support the relationship with suppliers;
  • Information systems to support the relationship with the Public Administration;

Demonstration of the syllabus coherence with the curricular unit’s intended learning outcomes.

The unit considers the planning and implementation of each type of information system as well as their main features, functionalities and organizational impact, in keeping with the objectives of this curricular unit.

Teaching methodologies (including evaluation):

Explanatory classes coupled with case studies and analyses of scientific articles about the subjects discussed in the classes. Students will be assessed on the basis of a written test (60%) and a group project (40%).

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes.

A multiple methodology has been adopted to ensure that the teaching methodology is suitable for the objectives of the discipline.

Thus, the course uses an explanatory method to transmit the theoretical concepts that are necessary in order to understand the materials and a case study method to promote reflections (reading case studies and scientific articles before the class) along with interaction between students in the classroom.

The unit seeks to complement these two teaching methodologies with the use of the demonstrative method, in order to show students concrete examples of the use of the diverse types of information systems discussed in the classroom.

Bibliography/Literature:

  • Bradford, Marianne (2010). Modern ERP: Select, Implement & Use Today's Advanced
  • Business System lulu.com, 248 p. ISBN-13: 978-0557434077
  • Greenberg, Paul (2010). CRM at the Speed of Light, Fourth Edition: Social CRM 2.0
  • Strategies, Tools, and Techniques for Engaging Your Custom McGraw-Hill Osborne, Fourth edition, 698 p. ISBN-13: 978-0071590457
  • Laudon, C. e Laudon, J. P. (2010). Management Information Systems: Managing the Digital Firm. Pearson, Eleventh Edition, 653 p.
  • Rainer, Rex Kelly e Turban, Efraim (2008). Introduction to Information Systems: Enabling and Transforming Busines John Wiley & Sons Inc; 2 edition, 464 p.
  • Turban, Efraim; Sharda, Ramesh e Delen, Dursun (2010). Decision Support and Business Intelligence System Pearson Education; 9 edition, 780 p. ISBN-13: 978-0132453233;
  • Kenneth C. Laudon e Jane P. Laudon (2010). Management Information Systems: Managing the digital firm. Eleventh editi Pearson. ISBN-13: 978-0-13-609368-8

 

 

 

T1724   Informatics Projects Management   إدارة مشاريع المعلوماتية                                

Intended learning outcomes of the curricular unit:

The objectives of this subject are:

  • Learning of the recent techniques and methodologies in the management and execution of informatics projects, as an engineering project.
  • Elaboration of specifications and management of technical and non-technical requisites, essential to the success of an informatics project: deadlines, human resources, costs and quality and security requisites.
  • Learning of the mechanisms of informatics project managements in realistic environments with connection to the software industry.

The main outcomes acquired with this subject are:

  • To know how to manage informatics projects in real environments.
  • To know how to elaborate the specification requisites used in the negotiation of informatics projects.
  • To manage medium size teams of programmers.

Syllabus:

  1. Project management topics:
  • Clients managements
  • Teams managements
  • Leadership
  • Project lifecycle
  • Quality and negotiation
  • Project managements in 9 topics: integration, scope, schedule, cost, quality, human resources, communication, risk and acquisitio
  1. Software engineering topics:
  • Plan of the software project
  • Quality plan and security requisites
  • Identification of the functional and non-functional requisites
  • Architectures and software design
  • Detailed elaboration of the software modules
  • Test phase
  • Deployment
  • Specifications plan of an informatics project
  • Recent informatics project management platforms:
  • SCRUM
  • PMBok
  • OpenUp

Demonstration of the syllabus coherence with the curricular unit’s intended learning outcomes.

The syllabus was designed to answer to all the objectives and competencies of this subject. The correspondences between the syllabus topics and the objectives and competencies are discriminated as follows:

  • Syllabus topic 1 - Objective 2, Outcome 2
  • Syllabus topic 2 - Objective 2, Outcome 2
  • Syllabus topic 3 - Objectives 1 and 3, Outcomes 1 and 3

Teaching methodologies (including evaluation):

Classes with expositional introduction of the syllabus topics and consequent exemplification, using around a fourth of the class period. Elaboration of a global project involving the student in teams of 4 to 6 elements, aiming the conclusion of the project at the end of the period (trimester). Scheduling of the objectives and the weekly tasks toexecute autonomously with finalization at class (three fourths of the class period). Election of a team leaders (students). At the end of the trimester the student will present their projects in a public session, simulating the deliver to the client. The students will be assessed by a final exam (60%) and a that final group project (40%).

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes.

The oral presentation is essential to teach the students the syllabus topics. However, being a discipline of project, it is fundamental the elaboration of teams of realistic medium size (4 to 6 elements) to the implementation of the specifications plan in a real project environment and to manage its execution. It is still essential to stimulate the commitments of the students with the project in autonomous tasks with the class serving as the finalization of the individual tasks and as the scheduling and distribution of the new work cycle. The definition of an element as team leader is also important to the project management and to simulate the real environment, using the recent methodologies adopted to this course.

Bibliography/Literature:

  • Eric Braude e Michael Bernstein (2011). Software Engineering – Modern Approac Wiley – 2nd Edition.
  • Tim Weilkiens (2007). Systems Engineering with SysML/UM Morgan Kaufmann –Elsevier.
  • Sanford Friedenthal, Alan Moore e Rick Steiner (2009). A Practical Guide to SysML –The Systems Modeling Languag Morgan Kaufmann – Elsevier.
  • Andrew Stellman e Jennifer Greene (2005). Applied Software Project Management. O'Reilly Medi

 

 

 

T1731    Development Acquisition Information Systems    تحليل وتطوير نظم المعلومات      

Intended learning outcomes of the curricular unit:

The main Objectives of this course are

  • To understand the different (internal) development methodologies and the implementation of an information system in an organization; (O 1)
  • To understand the different alternatives to (external) acquisition and implementation of an information system in an organizati (Obj. 2) Skills:
  • To be able to analyze a situation correctly so as to decide on the implementation method and the way in which to obtain an information system to be applied; (Skill1)
  • To be able to assess the risks of options made in the implementation pl (Skill 2)

 

Syllabus:

  • Introduction to the models for obtaining new information technologies and systems
  • Methods and processes for developing information systems
    • SSM
    • SSADM
    • Scrum
  • Methods and processes for acquiring information systems
    • IEEE Recommended Practice for Software Acquisition O. CMMI® Acquisition Module (CMMI-AM)
  • The advantages and risks of the methods presented

Demonstration of the syllabus coherence with the curricular unit’s intended learning outcomes.

The program contents are specifically geared towards fulfilling the curricular unit’s objectives, as can be seen by the alignment of the curricular items to the objectives and skills to be developed by students:

  • Introduction to the models for obtaining new information technologies and systems (O 1) (Obj. 2)
  • Methods and processes for developing information systems:
    • SSM (Ob 1) (Skill 1)
    • SSADM (O 1) (Skill 1)
    • Scrum (Ob 1) (Skill 1)
  • Methods and processes for acquiring information systems:
    • IEEE Recommended Practice for Software Acquisition (Ob 2) (Comp 1)
    • CMMI® Acquisition Module (CMMI-AM) (O 2) (Skill 1)
  • The advantages and risks of the methods presented (Skill 2)

Teaching methodologies (including evaluation):

Expository classes duly complemented with practical research assignments. At a later stage, there will be case studies that will be complemented with a debate among the students, guided by the lecturer. These cases will feature the presentation of a situation in an organization (real or fiction) whereby the challenges faced by will be described.

Students must propose a solution to the problem in accordance with the subject taught and their research into it.

  • Individual research assignment on the proposed subject (60%)
  • Analysis of a case study and its exposition and discussion with the class and the lecturer (40%)

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes.

The expository part of the classes will provide an introduction to the relevant concepts to allow a proper approach to the subjects. These issues will be duly deepened with research assignments. There will also be case studies to reinforce the concepts acquired with the theoretical exposition and research. The cases will be complemented with their exposition to the class and lecturer. Debate among students will be encouraged in order to allow the confrontation of several perspectives to solve one problem

Bibliography/Literature:

  • Kenneth C. Laudon anf Jane P. Laudon (2015) Management Information Systems: Managing the Digital Firm (14th Edition). 14th Pearson. ISBN: 978-0133898163.
  • Meyers , B. Craig e Oberndorf, Patricia (2001). Managing Software Acquisition: Open Systems and COTS Products. Addison-Wesley Professional. ISBN: 9780201704549.

Hofmann, Yedlin, Mishler e Kushner (2007). CMMI® for Outsourcing: Guidelines for Software, Systems, and IT Acquisition. Addison-Wesley Professional. ISBN: 978032147717

 

 

T1733      Procurement Support Information Systems  نظم المعلومات لإدارة ودعم المشتريات                    

Intended learning outcomes of the curricular unit:

Organizations are able to create value on the basis of the effectiveness and efficiency of their activities, especially sales, production and procurement. This course has de following objectives:

  • Understand the inherent issues of the purchasing function;
  • Acquire knowledge to a successful implementation of e-procurement systems;
  • Understand the principles of eCommerce and Electronic Data Interchange.

Syllabus:

  • The Procurement Function and the Process of Acquiring Goods and Servi A Strategic Procurement Plan Preparing Specifications Fraud and Corruption
  • E-Procurement Systems Functions and Components: E-Procurement Models
  • Benefits and Disadvantages Decisive Factors to be considered while Adopting Such Models
  • Decisive Factors during Implementation Organizational Impact and Process Re-Engineering Internal Integration with ERP and CRM External Integration with Suppliers’ ERP Systems
  • Managing Electronic Catalogues Analysis of Practical Cases"
  • eCommerce and Digital Data Interchange

Demonstration of the syllabus coherence with the curricular unit’s intended learning outcomes.

Topics 1 and 2 of Syllabus are related with outcome 1 and topics 3,4 and 5 are supposed to fulfillment the outcome 2. Finally, topic 6 is related with outcome 3.

Teaching methodologies (including evaluation):

Explanatory classes complemented by case studies, analyses of scientific articles on issues discussed in the classes and demonstrations of the information systems studied in the classroom. Students will be assessed on the basis of a written test (60%) and a group project (40%).

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes.

The exhibition sessions allow the students to understand the fundamental concepts. The demonstration of e-procurement applications, analysis of case studies / papers and the preparation, presentation and discussion of group work is a form of consolidation and exploitation of matter to attaining the educational objectives and develop skills.

Bibliography/Literature:

  • Christopher, M. (2016). Logistics & Supply Chain Management (5 edition). Harlow, England : New York: FT Press.
  • DeNardis, L. (Ed.). (2011). Opening Standards: The Global Politics of Interoperability (1 edition). Cambridge, Mass: The MIT Press.
  • DeNardis, L. (2014). Protocol Politics: The Globalization of Internet Governance. Place of publication not identified: The MIT Press.
  • Frison, A. (2015). Impact of Industry 4.0 on Lean Methods: and the Business of German and Chinese Manufacturer in China. Frison Anton.
  • Laursen, G. H. N., & Thorlund, J. (2016). Business Analytics for Managers: Taking Business Intelligence Beyond Reporting. John Wiley & Sons.

 

 

T1735    Information Systems Implementation and Change    إدارة وبناء التغييرات في نظم المعلومات                      

Intended learning outcomes of the curricular unit:

This course has the following objectives:

  • Contextualizing the implementation of IS and change management within the general framework of the Information Society
  • Present and evaluate the main theories and practices of change and knowledge management
  • Present and evaluate the main theories and practices in the implementation of information systems
  • Critically define best practices for implementing IS and knowledge manageme

 

It seeks to develop the following skills and outcomes:

  • Awareness and main practical implementation of information systems and management of change in social and organizational framework;
  • Understanding of the role of knowledge and change in organizational strategies;
  • Articulate reasoned perspectives and practical solutions for knowledge management and organizational chang

Syllabus:

  • Information and communication technology in the knowledge society
  • Communication skills and change: human capital and strategies for change
  • Individuals, organizations and society: implementation of Information systems
  • Collaborative networking strategies
  • Concepts and practices of knowledge and change management
  • Innovation, adoption and implementation of information technology in the management of change
  • Interdisciplinarity and management skills
  • Good practices: conceptual analysis and case studi

Demonstration of the syllabus coherence with the curricular unit’s intended learning outcomes.

  • Contextualizing the implementation of IS and change management within the general framework of the Information Society (Objective 1)
  • Information and communication technology in the knowledge society (Outcome 1)
  • Communication skills and change: human capital and strategies for change (Outcome 2)
  • Present and evaluate the main theories and practices of change and knowledge management (Objective 2)
  • Individuals, organizations and society: implementation of Information systems (Outcome 3)
  • Collaborative networking strategies (Outcome 3)
  • Present and evaluate the main theories and practices in the implementation of information systems (O3)
  • Define critical best practices for implementing IS and knowledge management (Objective 4).

Teaching methodologies (including evaluation):

Methods will be used in nature

  • Lectures and lectures with discussions
  • Case studies (using case studies as examples)
  • Class discussion and
  • Small group discussion and brainstorming (individual work, group and relevant participation in class). Evaluation:
    • Individual work (45%)
    • Group work (25%)
    • Oral presentation of text, project, or theme (30%)

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes.

The teaching and evaluation methodologies will measure the acquisition and construction of knowledge and skills, in a manner consistent with the objectives. The individual work (project and exposition of a selected subject) will encompass the syllabus materials of individual research, complemented by group work. All research work will be presented in class, giving the students the opportunity to demonstrate their ability to relate to the syllabus with their own research and actual experience, thereby allowing them to engage critically and creatively with contemporary scholarship. Thus, we seek to strengthen an individual appropriation of the course subjects, along with the ability to innovate creatively, contributing to the creation of a solid professional identity and useful, up-to-date research skills in the course's subject area.

Bibliography/Literature:

  • Calder, A., & Watkins, S. (2015). IT Governance: An International Guide to Data Security and ISO27001/ISO27002 (6 edition). London; Philadelphia, PA: Kogan Page.
  • Cameron, Green, M. (2009), Making Sense of Change Management: A Complete Guide to the Models, Tools and Techniques of Organizational Change. Kogan Page Publishers Keen, P. G. W. (1981). Information systems and organizational change. Communications of the ACM, 24(1), 24-33. ACM.
  • Frison, A. (2015). Impact of Industry 4.0 on Lean Methods: and the Business of German and Chinese Manufacturer in China. Frison Anton.
  • Holt, A. (2013). Governance of IT: An Executive Guide to ISO/IEC 38500. Swindon: BCS, The Chartered Institute for IT.
  • PE, C., Mr Dean Fanning. (2014). Life Cycle Costing: How to calculate life cycle costs and total ownership Cost. CreateSpace Independent Publishing Platform.
  • Peppard, J., & Ward, J. (2016). The Strategic Management of Information Systems: Building a Digital Strategy. John Wiley & Sons.
  • Schwalbe, K. (2015). Information Technology Project Management (8 edition). Australia ; Brazil: Course Technology.
  • Snapp, S. (2013). Enterprise Software TCO: Calculating and Using Total Cost of Ownership for Decision Making. SCM Focus.

 

 

 

T1736    Decision Support Systems    أنظمة دعم القرارات                                                  

Intended learning outcomes of the curricular unit:

Objectives:

  • To understand the fundamental aspects relating to decision support systems (DSS), namely their characteristics and components; (Obj 1)
  • To understand the applicability of decision support systems and the risks that their use may in (Obj 2)

Skills and outcomes:

  • To be able to decide on the applicability of decision support systems according to concrete situations; (Skill 1)
  • To know how to ensure the correction and applicability of the decision support system bought, ordered or under development; (Skill 2)
  • To be able to diagnose the risks from using a specific decision support system (Skill 3)

Syllabus:

  • Decision support systems: concept, components and development; Data warehouse
  • Data Mining
  • Using decision support systems
  • Decision Support Systems, expert systems and neural networks: Obtaining knowledge;
  • The organisation of knowledge; Reliability and risks of use.
  • Types of Groupware;
  • The architecture and components of group decision support systems (GDSSs); Using GDSSs."

Demonstration of the syllabus coherence with the curricular unit’s intended learning outcomes.

The program contents are specifically geared towards fulfilling the curricular unit’s goals, as can be seen by the association of the curricular units with the objectives and the skills to be developed by students:

  • Decision support systems: concept, components & development (O 1) (Skill 2)
  • Data warehouse and Data Mining (O 1) (Skill 1)
  • Using decision support systems (Skill 1)
  • Decision support systems, expert systems and neural networks: Obtaining knowledge; (Skill 1)
  • The organization of knowledge; (Skill 1)
  • Reliability and risks of use. (O 2) (Skill 3)
  • Types of Groupware; (Skill 1)
  • The architecture and components of group decision support systems (GDSSs); (O 1) Using GDSSs. (Skill 1)

Teaching methodologies (including evaluation):

The teaching methodology includes expository sessions where the relevant aspects of the subject shall be discussed; field work by students to develop the project; and presentation of the project by the students.

  • Project and participation (40%)
  • Final test (60%) The project may consist of (alternatively):
  • Arguing cases of DSS applicability
  • Describing DSS architectures and results
  • Presenting prototypes or systems within the scope of DSS, etc.

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes.

The expository sessions enable an understanding of the concepts and the preparation, presentation and discussion of the project are a way to consolidate and exploit the subject so that the educational objectives may be met and the skills developed.

Bibliography/Literature:

Intelligence Systems, 9th Ed., Pearson, 2010

 

 

 

T1740     Thesis   الرسالة                                                                                              

Intended learning outcomes of the curricular unit:

Students must show sufficient knowledge and ability to write a dissertation of scientific nature that is original and specifically created in order to achieve the academic degree of master. The written dissertation must be of good quality, contribute to the advance of scientific knowledge in its area of study and be worthy of the approval of a specifically appointed committee, according to legal stipulations, that will evaluate the thesis and discuss it with the author.

Syllabus:

Guidelines should be given concerning the research to be carried by the author of the dissertation and also the selection of information of relevance to the theme.

Guidelines should be given concerning research methodology, which should answer the research issues selected by each student and accepted by the responsible University department.

Periodical presentations and evaluation of the students’ work and counseling about future steps.

Results’ discussion and counseling about eventual limitations in order to solve issues or to clarify them in the conclusion phase.

 

 

 

  • Elective Courses

T1714      Economics for Managers   الاقتصاد الاداري                                                               

Intended learning outcomes of the curricular unit:

Deepening of the knowledge and the capacities of pupils to its preparation for the exercise of complex and demanding activities of management and taking decision into an economic environment of uncertainty, looking for to minimize the inherent risk through of a global understanding of the macro economic reality; knowledge of the results of the macroeconomics instruments for the business ;development of abilities and capabilities of this UC that enable pupils to apply the knowledge acquired in taking decision in to a uncertainty environment with insufficient information; to obtain a articulate knowledge of different forms of economic indicators.

Syllabus:

  • Markets Organization and Structure; Monopoly, Oligopoly and Monopolist Competition; Macroeconomics
  • Concepts: Product, Income, Prices and Inflati
  • Market of the Product and Monetary Market
  • Monetary Politics and Budgetary Politics
  • Unemployment and Inflation
  • Growth and Developmen
  • What it is an Economic Monetary Union
  • From the escudo zone to the euro zone
  • Intervention of the State in the Economy and Industrial Politics
  • Economy of the Knowledge and Competitiveness of the Portuguese Economy.

Demonstration of the syllabus coherence with the curricular unit’s intended learning outcomes.

The main objectives of the program are focus in the challenges and great subjects of the economic reality in order to allow to reach an efficient understanding and apprehension of the economic environment of the decision and economic agent.

Teaching methodologies (including evaluation):

Theoretic and practices methodologic, with some exercises practical economic cases study. The split of work hours is the following: theoretic sessions 21h; Projects and other works 24h, individual study 53 h; the evaluation process is the following: a individual test 60%; a group work without presentation 20%; oral presentation and discussion of the work 20%

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes.

The used methodologies of evaluation allow to analyze if it exists an adequacy of knowledge and if the abilities acquired allowed a good understanding of the reality and economic challenges for all economic agents

Bibliography/Literature:

  • World Development Report 1997 -The State in la Changing World , Banco Mundial,1997, Banco Mundial
  • Microeconomics for Managers, David M. Kreps, 2004, W. W. Norton
  • Principles of Economics, N. Gregory Mankiw, 2004, Harcourt College Publishers, 3ª ed
  • Economia da Empresa, José Mata, 2005, Fundação Calouste Gulbenkian, 3ª ed
  • Industria e Energia - As Apostas do Fim de Século, Luís Mira Amaral, 1997, Bertrand
  • Economia do Conhecimento e Realidade Portuguesa, Luís Mira Amaral, 2005, Sociedade Portuguesa de Inovação

Economics, Paul Samuelson, 2010 Mcgraw Hill

 

 

T1732     Process Mining    تحليل وتنقيب العمليات الادارية 

Process mining is the symbiose between process modeling and data oriented analysis.

The main goal is using data patterns and data metamorphoses to construct process models and automatize workflows. The usage of BPMN 2.0 to model and describe the processes will promote the implementation in different scenarios and the simulation of the workflows.

The approach starting from data to the processes will empower the information system analyst with new methods and technologies to develop systems more synchronized with the reality of the requirements of the organizations.

Intended learning outcomes of the curricular unit:

The main outcomes are the acquisition of competencies to identify ad-hoc processes and to model workflows starting from unstructured data.

The student will also be empowered with simulation methods and techniques to develop models with more effectiveness and efficiency.

Syllabus

  1. Process Models and Process Discovery
  • Event Logs and Process Models
  • Petri Nets 
  • Transition Systems and Petri Net Properties
  1. Types of Process Models
  • Quality Criteria For Process Discovery
  • The Representational Bias of Process Mining
  • Business Process Model and Notation (BPMN)
  • Dependency Graphs and Causal Nets
  • Process Discovery Techniques and Conformance Checking
  • Two-Phase Process Discovery And Its Limitations
  • Conformance Checking: Positive and Negative Deviants
  1. Enrichment of Process Models
  • Discovering Data Aware Petri Nets
  • Holistic Process Mining: Integrating Different Perspectives
  1. Operational Support and Conclusion
  • Discussion how process mining can be applied on running processes

Teaching methodologies (including evaluation):

The teaching methodology includes expository sessions where the relevant aspects of the subject shall be discussed; field work by students to develop the project; and presentation of the project by the students.

  • Project and participation (40%)
  • Final test (60%) The project may consist of (alternatively):
  • Arguing cases of GIS applicability
  • Describing GIS architectures and results
  • Presenting prototypes or systems within the scope of GIS, etc.

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes.

The expository sessions enable an understanding of the concepts and the preparation, presentation and discussion of the project are a way to consolidate and exploit the subject so that the educational objectives may be met and the skills developed.

The labs classes will give the training and the hands-on skills to achieve the planed outcomes.

References

  • Aalst, W. M. P. van der. (2016). Process Mining: Data Science in Action (2nd ed. 2016 edition). New York, NY: Springer.

  • Aalst, W. M. P. van der, & Stahl, C. (2011). Modeling Business Processes: A Petri Net-Oriented Approach. Cambridge, Mass: The MIT Press.

  • Enterprise and Organizational Modeling and Simulation. (n.d.). Reisig, W. (2013). Understanding Petri Nets: Modeling Techniques, Analysis Methods, Case Studies (2013 ed.). New York: Springer-Verlag Berlin and Heidelberg GmbH & Co. K.

 

 

T1725     Advanced Topics in Information Technology    مواضيع متقدمة في تكنولوجيا المعلومات

Intended learning outcomes of the curricular unit:

The main outcomes of this course are training

  • The value of the view
  • Data and image models (norms and standards of graphic representations)
  • Standards and technologies for application development with graphical environment
  • Concepts of Geographic Information Systems (GIS)
  • Information Integration with GIS Systems

Syllabus:

  • Graphics representations. Bitmap e SVG.
  • Norms of CGM, history and evolution. OpenGL and WebGL, concept and methods.
  • Graphic Software developement. WebGL and javascript.
  • Geographic Information Systems.
  • Raster and Vectorial Models,
  • R packages for GIS.

Demonstration of the syllabus coherence with the curricular unit’s intended learning outcomes.

The correlation between the points of the program and the proposed objectives is as follows:

  • The value of the visualization is achieved with point I of the program;
  • Data and image models (norms and standards of graphic representations) is achieved with point 2 of the program;
  • Standards and technologies for the development of applications with graphic environment is achieved with point 3 of the program;
  • Concepts of Geographic Information Systems (GIS) is achieved under item 4 and 5 of the program;
  • Integration of Information with GIS systems is achieved by means of point 6 of the program.

Teaching methodologies (including evaluation):

The course will include lectures taught by teachers with expertise and proven experience in the area and complimented with mentoring meetings between students and the teacher, whose main objective will be to provide guidance to practical work to be developed by students. All material used by the teachers to support classes (slides, videos, notes, etc..) will be available to students on the website of the course.

The pedagogical methods include theoretical presentations and a project according with “Project Based Learning” methodologies.

The students will be motivated to write a report on a particular theme associated with their project. It is expected that the student perform also a serious and detailed research in this context using internationally recognized material for this purpose (books, articles, magazines, etc.).The students will be assessed by a final exam (60%) and a that final group project (40%).

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes

The development and implementation of small projects at the end of each of the course component will allow the concrete and practical application of the knowledge acquired, providing a better sedimentation of it by the students and to acquire skills in the area.

The preparation of a report (monograph) besides the reading of relevant articles of the area will consolidate the theoretical knowledge of the CG field, contributing also to the acquisition of skills.

For this reason, this course will adopt, in terms of organization and methodology, the principle of diversity using different types of explicit teaching methods (Lectures, group work and evaluation through several small projects/works)."

Bibliography/Literature:

  • Tony Parisi (2012). WebGL: Up and Running. O’Reilly Media, Inc. ISBN: 978-1-449-32357-8
  • Robert I. Kabakoff (2015). R in Action. Manning Publications (2nd. Ed.),ISBN-13: 978-1617291388
  • Jos Dirksen (2013). Learning Three.js: The JavaScript 3D Library for WebGL. Packt Publishing. ISBN 978-1-78216-628-3.
  • David Eisenberg et al. (2014). SVG Essentials. O’Reilly Media, Inc. ISBN:978-1-4493-7435-8
  • Michael Dorman (2014). Learning R for Geospatial Packt Publishing. ISBN 978-1-78398-436-7

 

 

T1734     Information Mining in Social Web   تحليل وتنقيب المعلومات في الشبكات الاجتماعية    

Intended learning outcomes of the curricular unit:

The main objective of this course is to enable students to understand how the different techniques of mining information on the Social Web can provide competitive advantage to companies from diverse business areas. This goal is reached from the following specific goals:

  1. To present the concepts related to mining information on the Social Web, including social networks, microblogging sites, and evaluation of products and services;
  2. To analyze techniques for named entity extraction and opinion mining;
  3. To present and use applications that make information mining on the Social We The skills to be acquired with this UC are:
  4. To enable the student to develop techniques for information mining on the Social Web, according to the needs of corporate information systems;
  5. To enable the student to evaluate and extract knowledge from the content generated by users of the Social Web.

Syllabus:

  1. Text Preprocessing
    1. Removal of top-words
    2. Duplicate detection
  2. Text named entity extraction (NE)
    1. Identification and classification of NE (e. people, places and organizations)
    2. Recognition of relationships between NE
  3. Opinion Mining
    1. Sentiment Analysis
    2. Polarity of the sentiments and degrees of positivity
    3. Opinion Mining based on features
    4. Applications
  4. Social Network Analysis
    1. Centralization
    2. Prestige
  5. Information mining in blogosphere and folksonomies
  6. Applications for information mining on the Social Web

Demonstration of the syllabus coherence with the curricular unit’s intended learning outcomes.

The first objective is achieved with the study of the syllabus from 1 to 5.

The second objective is achieved through the study of the syllabus of 1, 2, 3 and 5.

The third objective is achieved with the study of the syllabus of 3d and 6.

Teaching methodologies (including evaluation):

  1. Lectures on the topics listed in the syllabus;
  2. Analysis of scientific articles on the topics of the syllabus;
  3. The students will be invited to develop a project and to make an oral presentation.;
  4. Open discussion classes;
  5. Labs and practical exerci

Evaluation: Test (60%), project (20%) and practical work group (20%)"

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes.

  • Teaching methods 1 and 2 are consistent with the objectives 1 and 2;
  • Teaching methods 2, 3 and 4 are consistent with the objectives 2 and 3;
  • The teaching method 5 is consistent with the objective 2.

Bibliography/Literature:

  • Artificial Intelligence in Medicine: 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, June 21-24, 2017, Proceedings (Lecture Notes in Computer Science).
  • Chang, W. (2013). R Graphics Cookbook: Practical Recipes for Visualizing Data (1 edition). Beijing Cambridge Farnham Köln Sebastopol Tokyo: O’Reilly Media.
  • Gómez-Pérez, A., Fernandez-Lopez, M., & Corcho, O. (2004). Ontological Engineering: With Examples from the Areas of Knowledge Management, E-Commerce and the Semantic Web (1st ed. 2004. Corr. 2nd printing 2004 edition). London ; New York: Springer.
  • Liu, B. (2011). Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (2nd ed. 2011 edition). Heidelberg ; New York: Springer.
  • Maynard, D., Gangemi, A., Hoekstra, R., Hitzler, P., & Hartig, O. (2017). The Semantic Web: 14th International Conference, ESWC 2017, Portoroz, Slovenia, May 28 - June 1, 2017, Proceedings, Part II. (E. Blomqvist, Ed.) (1st ed. 2017 edition). Cham: Springer.
  • Pang, B., & Lee, L. (2008). Opinion Mining and Sentiment Analysis. Boston, Mass.: Now Publishers Inc.
  • Shmueli, G., Patel, N. R., & Bruce, P. C. (2016). Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner. John Wiley & Sons.
  • Wickham, H., & Grolemund, G. (2017). R for Data Science: Import, Tidy, Transform, visualize, and Model Data (1 edition). s.l: O’Reilly Media.
  • Zamir, A. R., Hakeem, A., Gool, L. V., Shah, M., & Szeliski, R. (Eds.). (2016). Large-Scale Visual Geo-Localization (1st ed. 2016 edition). New York, NY: Springer.

 

 

 

T1723     Methods of Negotiation    طرق التفاوض 

Intended learning outcomes of the curricular unit:

Provide students with the concepts and models of negotiation and reveal its importance for the management of organizations are presented models and methods that can be used in general management, departmental   and   product, negotiation processes.

In the end, students should understand what is negotiation, as can be applied, specifically, in organizations and how information and communication technologies can contribute to a more effective negotiation. Also, should know main important research options in this area of knowledge.

Demonstration of the syllabus coherence with the curricular unit’s intended learning outcomes.

Negotiation is key for organizations sustainability. To date, many authors have developed this subject and applied their knowledge to organizations. It has been scientifically proven that companies with the major negotiation capability perform better. New technology and the internet facilitate to obtain, analyze and share information.

Accordingly, they allow greater acquisition and dissemination of knowledge in negotiation processes. In this unit we will provide knowledge on negotiation concepts and models and how ICT can facilitate its implementation. By the end, students will have the required knowledge and capacity to assess and implement negotiation processes and now how ICT can facilitate. New knowledge obtained by students can be applied in new investigations in this subject or in organizations.

Teaching methodologies (including evaluation):

The methods used structure each session in the following way: the session will begin with an explanation of the objective to be reached and a brief introduction to the subject is given; next, there will be a simulated exercise where students will interact with one another; there will follow a broad discussion to define and clarify the underlying principles; lastly, a synthesis of the session’s key-points will be made. The assessment will be based on a test or final coursework (60%) and group work in the classroom (40%).

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes.

The behavioral fields require the active involvement of students, the reason for which a mixed methodology was chosen. The practice-debate-theoretical framing sequence has proven to be adequate and facilitates learning among young adults. The topic of this curricular unit requires a good balance between practice and exposition, so as to reach the desired objectives.

Bibliography/Literature:

  • Berry, J. (2014). Negotiating Skills: How to Negotiate Anything to Your Advantage. CreateSpace Independent Publishing Platform. ISBN-13: 978-1505559873.
  • Hay, S., McCarthy, A., & RDC, J. H. A. for. (2015). Advanced Negotiation Techniques (1st ed. edition). Apress. ISBN-13: 978-1484208519.
  • Moore, C. W. (2014). The Mediation Process: Practical Strategies for Resolving Conflict (4 edition). San Francisco: Jossey-Bass. ISBN: 978-1-118-30430-3.
  • Sood S., Pattinson H. (2011) Patterns of Negotiation. In: Minai A.A., Braha D., Bar-Yam Y. (eds) Unifying Themes in Complex Systems. Springer, Berlin, Heidelberg.

 

 

T1726      Data Analytics for Business   تحليل البيانات الادارية 

Intended learning outcomes of the curricular unit:

The main goals of this course are the normalization and conceptualization of knowledge repositories susceptible to be used by analytics models to present patterns, tendencies and predictive forecasts.

The main outcomes of this course is:

  • To acquire knowledge of concepts and models of data-driven management and techniques to manage the data life cycle and its quality;
  • To understand and get training on health data analytics based on clustering and data patterns tools;
  • To understand and get skills to use statistics and predictive business models;
  • To know how to use business data visualization tools.

Syllabus

  1. Strategic Importance of fostering a data-driven culture in a business organization
  • Business value of data to an organization
  • From Data to Knowledge to healthcare improvement
  • Types of data analytics techniques and their strengths and weaknesses
  • Data governance and what it means to the organization
  • Importance of fostering a data-driven culture in an organization
  1. Data processing and reporting techniques
  • The Data Life Cycle
  • Data sources and data structures
  • Defining and Developing Key Performance Indicators
  • Dashboards – uses and design pitfalls
  • Data summary and visualization techniques
  • Techniques for Statistical Inference – the 95% Confidence Interval
  • General principles involving test of statistical significance – Null Hypothesis, p-value and interpreting test outcomes
  • Basic statistical tests involving measurement outcome variables
  • Basic statistical tests involving non-measurement outcome variables
  • Misuses of statistical tests of significance 
  1. Predictive Analytics and models
  • Principles of predictive analytics
  • Machine Learning concepts and techniques with business data

Teaching methodologies (including evaluation):

The teaching methodology includes expository sessions where the relevant aspects of the subject shall be discussed; field work by students to develop the project; and presentation of the project by the students.

  • Project and participation (40%)
  • Final test (60%) The project may consist of (alternatively):
  • Arguing cases of GIS applicability
  • Describing GIS architectures and results
  • Presenting prototypes or systems within the scope of GIS, etc.

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes.

The expository sessions enable an understanding of the concepts and the preparation, presentation and discussion of the project are a way to consolidate and exploit the subject so that the educational objectives may be met and the skills developed.

The labs classes will give the training and the hands-on skills to achieve the planed outcomes.

References

  • Chang, W. (2013). R Graphics Cookbook: Practical Recipes for Visualizing Data (1 edition). Beijing Cambridge Farnham Köln Sebastopol Tokyo: O’Reilly Media.
  • Gómez-Pérez, A., Fernandez-Lopez, M., & Corcho, O. (2004). Ontological Engineering: With Examples from the Areas of Knowledge Management, E-Commerce and the Semantic Web (1st ed. 2004. Corr. 2nd printing 2004 edition). London ; New York: Springer.
  • Madsen, L. B. (2012). Healthcare Business Intelligence, + Website: A Guide to Empowering Successful Data Reporting and Analytics (1 edition). Hoboken, New Jersey: Wiley.
  • Wickham, H., & Grolemund, G. (2017). R for Data Science: Import, Tidy, Transform, Visualize, and Model Data (1 edition). s.l: O’Reilly Media.

Yang, H., & Lee, E. K. (Eds.). (2016). Healthcare Analytics: From Data to Knowledge to Healthcare Improvement (1 edition). Hoboken, New Jersey: Wiley

 

 

T1727     Geographic Information Systems Technology for Business Applications    نظم المعلومات الجغرافية لتطبيقات الأعمال                                

The geographic information systems are a set of concepts and techniques transversal to almost all information system. Nowadays every event or physical quantum of data can be geo-referenced and the distribution of values in a spatial perspective is a very important issue to the knowledge construction.

The merging of spatial data with non-spatial data and the relational data bases capable to store all the data and manage it according with a normalized query language like SQL is a very huge step toward the integration of all information systems and Big Data.

Intended learning outcomes of the curricular unit:

The main goals of this course are the acquisition of skills to understand, define and develop information systems that use geo-referencing information.

Complementary the course explores the data visualization and data analytics in conjunction with spatial data.

The main outcomes are:

  • To understand the concepts of spatial data and reference systems;
  • To have skills to merge spatial data with common data;
  • To have skills to develop spatial relational database repositories;
  • To be able to develop data analytical models with spatial data.

Syllabus

  1. Data Acquisition and Data Integration
  • Spatial reference Systems and transformations
  • Spatial models: raster and vectorial
  • Data acquisition systems: satellite, Shuttle Radar Topography Mission, aerial photogrammetry and GPS.
  1. Relational Databases
  • Relational data models to store spatial data
  • SQL extensions to manipulate spatial data
  • Raster Data Management, Queries, and Applications
  • Geometry: Building Applications
  • Performance and tuning.
  • Merging spatial with non-spatial data
  • Data analytics
  • R packages to analyze spatial data
  • Classes for Spatial Data in R
  • Visualizing spatial data
  • Interpolation and Geo-statistics

Teaching methodologies (including evaluation):

The teaching methodology includes expository sessions where the relevant aspects of the subject shall be discussed; field work by students to develop the project; and presentation of the project by the students.

  • Project and participation (40%)
  • Final test (60%) The project may consist of (alternatively):
  • Arguing cases of GIS applicability
  • Describing GIS architectures and results
  • Presenting prototypes or systems within the scope of GIS, etc.

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes.

The expository sessions enable an understanding of the concepts and the preparation, presentation and discussion of the project are a way to consolidate and exploit the subject so that the educational objectives may be met and the skills developed.

The labs classes will give the training and the hands-on skills to achieve the planed outcomes.

References

  • Chang, W. (2013). R Graphics Cookbook: Practical Recipes for Visualizing Data (1 edition). Beijing Cambridge Farnham Köln Sebastopol Tokyo: O’Reilly Media.
  • Eisenberg, J. D. (n.d.). SVG Essentials. Retrieved from http://shop.oreilly.com/product/9780596002237.do
  • Graph Analysis and Visualization: Discovering Business Opportunity in Linked Data - PDF Free Download. (2015, April 2). Retrieved July 30, 2017, from http://www.foxebook.net/graph-analysis-and-visualization-discovering-business-opportunity-in-linked-data/
  • Heywood, I., Cornelius, S., & Carver, S. (2012). An Introduction to Geographical Information Systems (4 edition). Harlow, England ; Toronto: Pearson.
  • Learning R for Geospatial Analysis - PDF Free Download. (2015, February 13). Retrieved July 30, 2017, from http://www.foxebook.net/learning-r-for-geospatial-analysis/Parisi, T. (n.d.). WebGL: Up and Running. Retrieved from http://shop.oreilly.com/product/0636920024729.
  • DoR in Action: Robert Kabacoff: 9781935182399: Amazon.com: Books. (n.d.). Retrieved July 15, 2017, from https://www.amazon.com/R-Action-Robert-Kabacoff/dp/1935182390
  • Weske, M. (2012). Business Process Management: Concepts, Languages, Architectures (2nd ed. 2012 edition). Heidelberg; New York: Springer.
  • Wickham, H., & Grolemund, G. (2017). R for Data Science: Import, Tidy, Transform, Visualize, and Model Data (1 edition). s.l: O’Reilly Media.

 

 

 

T1728  Semantic Intelligence technologies: The future of organizations interoperability تقنيات الذكاء الدلالي: مستقبل قابلية تبادل المعلومات بين المؤسسات                                                                                        

The semantic intelligence techniques are used to extract information from non-structured data, including natural language.

The areas of application are many including big data analysis, web crawling and processes automation across different organizations.

Intended learning outcomes of the curricular unit:

The main goals are the acquisition of knowledge and train on tools to design semantic web platforms and to develop interoperable interfaces capable to extract and process information written in natural language.

The outcomes are:

  • To acquire knowledge to design semantic web platforms;
  • To get skills to use and develop scripts to extract information from natural language;
  • To know how to use machine learning tools to process information in natural language.

Syllabus

  1. Introduction to Knowledge representation and reasoning (KR)
  • Concept of knowledge representation
  • Ontologies and interoperability
  1. Declarative Programming and semantic Web
  • Concept of declarative programming
  • The Semantic Web Activity of W3C: Overview of techniques and standards
  • Transformation/Inference rules in XSLT, RuleML and RIF
  • Metadata with RDF (Resource Description Framework)
  • Natural Language Processing (NLP)
  • Information extraction, question answering, recognizing textual entailment, and machine translation
  • Syntactic Parsing and Lexical Semantics
  • Machine learning techniques to extract information from web.

Teaching methodologies (including evaluation):

The teaching methodology includes expository sessions where the relevant aspects of the subject shall be discussed; field work by students to develop the project; and presentation of the project by the students.

  • Project and participation (40%)
  • Final test (60%) The project may consist of (alternatively):
  • Arguing cases of GIS applicability
  • Describing GIS architectures and results
  • Presenting prototypes or systems within the scope of GIS, etc.

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes.

The expository sessions enable an understanding of the concepts and the preparation, presentation and discussion of the project are a way to consolidate and exploit the subject so that the educational objectives may be met and the skills developed.

The labs classes will give the training and the hands-on skills to achieve the planed outcomes.

References

  • Badr, Y., Chbeir, R., & Abraham, A. (Eds.). (2010). Emergent Web Intelligence: Advanced Semantic Technologies (2010 edition). London; New York: Springer.
  • Barrière, Caroline (2016). Natural Language Understanding in a Semantic Web Context.Springer International Publishing, ISDN:978-3-319-41337-2.
  • Liu, Bing (2010). Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data. Springer, 2nd printing edition 532 p. ISBN-13: 978-3642072376
  • Maynard, D., Gangemi, A., Hoekstra, R., Hitzler, P., & Hartig, O. (2017). The Semantic Web: 14th International Conference, ESWC 2017, Portoroz, Slovenia, May 28 - June 1, 2017, Proceedings, Part II. (E. Blomqvist, Ed.) (1st ed. 2017 edition). Cham: Springer.
  • Maynard, D., Kalina Bontcheva, Isabelle Augenstein (2016). Natural Language Processing for the Semantic Web (Synthesis Lectures on the Semantic Web: Theory and Technology). Morgan Claypol Publishers.
  • Pang, Bo e Lee, Lillian (2008). Opinion Mining and Sentiment Analysis. Now Publishers Inc. 148 p. ISBN-13: 978-1601981509
  • Paul H. Sra (2012) Optimization for Machine Learning (Neural Information Processing Series). Massachusetts Institute of Technology.
  • Watson, M. (2010). Scripting Intelligence: Web 3.0 Information Gathering and Processing (1st ed. edition). Berkeley, Calif: Apress.


                                                                                                                       

Entrepreneurship    الريادية         

Intended learning outcomes of the curricular unit:

This curricular unit has as main goals the following:

  1. To develop entrepreneurial skill
  2. To provide knowledge on the elaboration of business plan
  3. To provide knowledge on the legal aspects of new venture creati
  4. To improve communication techniques
  5. To develop management decision capabilities in what concerns business plan implementation and financi

Syllabus:

Business creation process

  1. Identification of business opportunities
  2. Market analysis and marketing Business plans and financing
  3. Elaboration of Business Plans
  4. Risk analysis Implementation of the new business creation
  5. Financing
  6. Taxes and another legal aspects Business exit
  7. Exit options

Demonstration of the syllabus coherence with the curricular unit’s intended learning outcomes.

The selected syllabus will complement and explore the knowledge gained in the first cycle and will focus on the writing of business plans adapted to the type of company and to the presentation to investors. The syllabus are coherent with the curricular unit's objectives since they contain a thorough approach to each theme, including the several aspects of new venture creation such as Business Plan elaboration, detailed risk analysis and the preparation of financial statements using real options. In addition, several specific aspects associated to new venture creation will also be addressed including the legal issues related to the establishment of the company and intellectual property. Finally, the final assignment will consist on the elaboration of a Business Plan which will contribute to provide the student with an opportunity to develop research and communication skills.

Teaching methodologies (including evaluation):

Classes are taught based on the theory presentation supported by the presentation of case-studies to ensure better understanding of the concepts.

The evaluation is composed of:

  1. group assignment on a relevant theme for new venture creation or a case-study with oral presentation/discussion (40% weight on the final mark)
  2. a final written assignment consisting in a Business Plan for the creation of a new company (60% weight).

Demonstration of the teaching methodologies coherence with the curricular unit’s intended learning outcomes.

The theoretic presentations in class are complemented with the presentation and discussion of group assignments.  This methodology is coherent with the curricular unit's objectives since it provides knowledge on entrepreneurship, including Business Plan elaboration adapted to the specific characteristics of each company and develops the necessary skills for implementation and financing of new ventures in a competitive environment.

Bibliography/Literature:

  1. Bygrave, William D., Zacharakis, Andrew, Portable MBA in Entrepreneurship, Wiley, 4th Ed., 2009
  2. Brännback, M., & Carsrud, A. (2017). Cognitive Maps in Entrepreneurship: Understanding Contexts. In Revisiting the Entrepreneurial Mind (pp. 123–129). Springer, Cham.
  3. Cobb, Barry R., Charnes, John , Real Options valuations, in Proceedings of the 2007 Winter Simulation Conference (S. G. Henderson, B. Biller, M.-H. Hsieh, J. Shortle, J. D. Tew, and R. R. Barton, eds.), 2007.
  4. Palumbo, M. J. (2016). Calculated Risk: The Modern Entrepreneur’s Handbook. MJP Publications, LLC.
  5. Schenk, W. (2017). The Absence of Entrepreneurial Foresight as a Reason of Entrepreneurial Failure. In Development, Growth and Finance of Organizations from an Eastern European Context (pp. 127–132). Springer, Cham.

 

جميع الحقوق محفوظة © 2018 جامعة الخليل

Search