Negotiation and Sales Techniques

Category: Discipline
  • Não
  • The curriculum unit on negotiation and sales techniques falls within the Commercial Management and Sales course. It aims to equip students with knowledge of how negotiation and sales are pivotal factors in managing businesses and commercial operations. This curriculum unit also addresses concepts and techniques of negotiation essential in the commercial field. Alongside these principles of negotiation and sales, the team also seeks to stimulate reflective capacity and critical thinking in this domain.
  • Semestral

  • Descrição

    Data limite

    Ponderação

    Teste de avaliação individual

    17-11-2025

    40%

    Relatório trabalho de grupo
    (role-playing) + apresentação oral

    Entrega relatório: 15-12-2025


    Apresentações orais:
    05-01-2026 e 12-01-2026

    Relatório trabalho de grupo 30% + 30% apresentação individual

    Presença e participação nas aulas

    -

    Avaliação qualitativa
  • Communication The communication process Communication techniques Web communication supports Negotiation The negotiation process Team leadership Negotiation and organizational culture Negotiation styles and attitudes to adopt towards them Sales Techniques Identifying motivations and needs Analysis and evaluation of possible solutions Demonstrating the solution Finalisation Post-sale communication and support Conflict Management Case Studies
  • Introduce and outline communication techniques. Characterise the negotiation process. Present team leadership techniques. Identify the needs and motivations of the customer. Describe the communication process in sales. Apply negotiation techniques. Identify the stages of a sale's life cycle.
  • Mandatory
  • The students will be working on projects related to real-life negotiation and sales situations, offering them a deeper and contextualised learning experience. Group work involves simulation/role-playing: allowing students to experience real negotiation scenarios, and helping them understand the dynamics and strategies involved. Peer-to-peer learning: fostering discussions and tasks where students can learn from each other, sharing experiences and different perspectives. Reflection sessions: After simulations and role-playing activities, there are moments of reflection where students can discuss what worked, what didn't, and how they can improve. Problem-based learning: challenging students with real-world sales negotiation issues, encouraging them to propose solutions using theories and techniques taught in the curriculum unit.
  • Português
  • Cialdini, R. B. (2021). Influence, new and expanded: The psychology of persuasion. Harper Business. Blount, J. (2021). Sales EQ: How ultra high performers leverage sales-specific emotional intelligence to close the complex deal. Wiley. Thompson, L. L. (2021). The truth about negotiations (3rd ed.). Pearson Education. Voss, C., & Raz, T. (2021). Never Split the Difference: Negotiating as if your life depended on it. Harper Business
  • 4
  • 0
  • 5
  • 2
  • IPLUSO6148-15491
  • Negotiation and Sales Techniques
  • 15491
  • 6148
  • Commercial and Sales Management

Sales Force Management

Category: Discipline
  • Não
  • The Sales Force Management course is part of the commercial and marketing field, focusing on the organisation, leadership, and motivation of sales teams. Aimed at students of the Higher Professional Technical Courses (CTeSP) in Marketing Management and Commercial and Sales Management, it covers methods and strategies to plan, monitor, and optimise commercial activity, aligning it with the company’s objectives. With its practical and applied nature, this course prepares professionals for leadership and coordination roles in sales teams, meeting the competitive demands of today’s market.
  • Semestral

  • A avaliação privilegia a participação ativa, a aplicação prática dos conhecimentos e a capacidade crítica dos estudantes. Está organizada em componentes contínuas e uma prova individual:

    Participação e desempenho em aula – 15%

    • Assiduidade, envolvimento em debates, simulações e role-play.

    • Contributo individual para trabalhos de grupo e atividades práticas.

    Trabalho de Grupo Intermédio – 20%

    • Elaboração de um mini-plano de vendas (Aula 5).

    • Foco na definição de objetivos, estratégias e recursos.

    • Apresentação curta em aula e entrega em Moodle.

    Trabalho Final de Grupo – 35%

    • Desenvolvimento de um Plano de Gestão da Força de Vendas para um caso real ou simulado.

    • Inclui análise de estrutura da equipa, planeamento, motivação, controlo de desempenho e tecnologias de apoio.

    • Apresentação oral (Aula 14) com discussão crítica.

    Teste Individual Final – 30%

    • Realizado na Aula 15.

    • Avaliação dos conhecimentos teóricos e práticos adquiridos ao longo do semestre.

    • Questões de escolha múltipla, de desenvolvimento e aplicação prática.

    Notas Complementares

    • A avaliação contínua requer presença mínima em 75% das aulas.

    • A não entrega de trabalhos implica a perda da respetiva componente.

    • Os estudantes podem ser chamados individualmente a defender oralmente o seu contributo nos trabalhos de grupo.

    • Nota mínima de 9,5 valores nas várias componentes da avaliação contínua.

    • Em época de recurso ou especial, será realizado um Teste Individual que abrange todos os conteúdos lecionados ao longo do semestre.
  • Introduction to sales force management: concepts, objectives, and strategic importance. Sales team structure and organisation: models, roles, territories, and customer portfolios. Sales planning and strategy: goal setting, forecasting, resources, and integration with marketing. Motivation and leadership: applied theories, management styles, coaching, and talent retention. Performance control and evaluation: KPIs, incentives, rewards, and continuous improvement. Sales support technologies: CRM, sales force automation, reporting, and the impact of digital transformation. Ethics, sustainability, and customer focus: social responsibility, loyalty, win-win negotiation, and value creation. Case studies and practice: analysis of national and international examples, development of sales plans, simulations, and role-play.
  • By the end of the course, students should understand the fundamental concepts of sales force management, recognising its strategic role within organisations and its integration with marketing. They should be familiar with commercial organisation models, sales planning methods and goal setting, motivation and leadership techniques, and the use of digital tools (CRM and SFA). In terms of skills, students will be able to design sales plans, apply performance indicators, use sales support technologies, and adapt strategies to different customer profiles and market contexts. At the competence level, they should demonstrate the ability to lead and coordinate teams, make informed decisions, integrate ethical and customer-oriented practices, and communicate effectively in commercial settings, preparing for leadership and coordination roles in competitive environments.
  • Mandatory
  • The course adopts active, student-centred methodologies, combining theory and practice in contexts close to business reality. Project-based learning is used through the development of sales force management plans applied to real or simulated cases; role-play and simulations are applied to practise negotiation, leadership, and decision-making; and national and international case studies are analysed critically. Practical exercises integrate digital tools and CRM systems, enhancing technical and analytical competences. Gamified activities, guided debates, and collaborative work foster critical thinking, communication, and teamwork. Continuous feedback, including self-assessment and reflection, ensures performance improvement and consolidation of learning outcomes.
  • Português
  • Rich, G. A., & Epler, R. (2023). Sales Force Management (1ª ed.). SAGE Publications. Larreche, J.-C. (2023). Value Capture Selling: How to Win the 3rd Sales Transformation. Wiley.  Miller, A. B. (2024). HubSpot vs Salesforce: A Comprehensive Guide to Navigating CRM Systems. Independently published. 
  • 4
  • 0
  • 5
  • 2
  • IPLUSO6148-15489
  • Sales Force Management
  • 15489
  • 6148
  • Commercial and Sales Management

Data Communications and Computer Networks

Category: Discipline
  • Não
  • This UC addresses the basic concepts related to data communication networks, from their single-use to the planning, design, and management of networks, in the double aspect of resources and security, allowing a better understanding of the emerging potentialities
  • Semestral

  • Descrição dos instrumentos de avaliação (individuais e de grupo) ¿ testes, trabalhos práticos, relatórios, projetos... respetivas datas de entrega/apresentação... e ponderação na nota final.

    Exemplo:

    Descrição

    Data limite

    Ponderação

    Projecto de redes estruturada

    Teste de Avaliação Global (TAG)

    Entregar até uma semana antes fim semestre

    Fim do Semetre

    30%

    70%

     

     

     
  • Data representation (Numbering systems) Exploring the network Setting up a network operating system Network protocols and communications Network access Ethernet Network layer IP addressing Division of IP networks into subnets Transport layer Creating a Network
  • Provide solid training in the areas of data communication, LAN, WAN, and Wireless. Architectures, Topologies, and Communication Protocols. Design and structured network design. Competences: Know the main network models; Knowledge the potential of data media for the performance of organizations; Identify the various types of networks; Planning projects of data communication networks; Identify protocols and network architectures; Create local and long-distance data networks; Identify and apply the various network devices; Know in detail the IP address (Internet Protocol v4 and v6) as well as the mechanics of dividing IP addresses into subnets; Configuration of routers and switches; Analyze the quality of data communication networks.
  • Mandatory
  • Innovative methodologies at the UC include active learning through problem-solving and case studies, collaboration on group projects, use of interactive digital resources, regular formative assessments, and practical application of knowledge in real-world projects.
  • Português
  • GOUVEIA, José, Redes de Computadores - Locais e Wireless - Curso Completo, FCA, 2005 MONTEIRO, Edmundo e Fernando Boavida: Engenharia de Redes Informáticas", FCA, 2011 VÉSTIAS, Mário P. , Redes Cisco Para Profissionais, FCA, 2012 Martins, José Legatheaux - Fundamentos de Redes de Computadores Ilustrados com Base naInternet e nos Protocolos TCP/IP. 1a Edição Digital. Nova.FCT Editorial, 2018. https://legatheaux.eu/book/cnfbook-pub.pdf Kozierok, Charles M. - The TCP/IP Guide. http://www.tcpipguide.com/free/t_toc.htm  
  • 4
  • 0
  • 6
  • 1
  • IPLUSO6382-1282
  • Data Communications and Computer Networks
  • 1282
  • 6382
  • Computer Applications for Data Science

Object-Oriented Programming

Category: Discipline
  • Não
  • The Course Unit of Object-Oriented Programming (OOP) aims to provide students with solid knowledge of the programming paradigm that underpins most current programming languages and software development technologies. Its scope lies in introducing and deepening the fundamental concepts of object orientation, fostering the ability to apply these principles in the development of robust, scalable, and reusable applications. The unit also seeks to stimulate logical and abstract reasoning skills, preparing students to solve complex problems in diverse contexts through the practical application of modeling and implementation techniques in Java. The relevance of this unit stems from the fact that OOP constitutes the essential conceptual and practical foundation for progression into more advanced areas of software engineering and development.
  • Semestral

  • Descrição

    Data limite

    Ponderação

    Entrega, Apresentação e Defesa do Projeto

    20-01-2026

    65%

    Entrega do Portefólio Individual

    20-01-2026

    35%

    Exame de Recurso

    -

    100%

    A avaliação contínua inclui a realização, individualmente ou em pequenos grupos, de um projeto que materializa a aplicação dos conceitos da POO, representando 65% da nota final, e a elaboração de um portefólio individual, no qual cada estudante reflete de forma crítica sobre as aprendizagens realizadas, documenta exercícios desenvolvidos e avalia a sua evolução ao longo do semestre, correspondendo a 35% da nota final. Esta distribuição assegura um equilíbrio entre o desempenho técnico e a capacidade reflexiva, garantindo uma avaliação integral e formativa do processo de aprendizagem. Em alternativa à avaliação contínua, os estudantes que não obtenham aprovação podem realizar um exame escrito de recurso, com um peso de 100% da nota final.
  • Introduction to the Object-Oriented Programming (OOP) paradigm What is OOP and Benefits of OOP Concepts used in OOP (methods, fields, classes, objects, etc.); connection with algorithmics may be addressed again. Objects and classes in OOP; Definition of classes Creation of objects; Constructors Inheritance What inheritance is in OOP Extension of classes Method overriding through the superclass Polymorphism; Method overloading Dynamic methods in OOP Encapsulation Access modifiers Getters and setters in OOP Abstraction Abstract classes; Interfaces Relevant topics in OOP Exceptions and their handling File systems (I/O) Inner classes and static members Structures and code organization Organization and structure of code and their importance
  • At the end of the course unit, the student should be able to: Understand the fundamental principles of Object-Oriented Programming. Define classes, objects, and methods in Java, correctly applying constructors. Apply the concepts of encapsulation, inheritance, polymorphism, and abstraction to concrete problems. Develop solutions using interfaces, abstract classes, and method overloading and overriding mechanisms. Implement exception handling, input/output operations, and modular code organization. Work collaboratively in a team in the development of software solutions. Present and defend developed solutions, providing well-founded arguments. Critically reflect on the process of learning and software development, producing appropriate technical documentation.
  • Mandatory
  • The course unit adopts active teaching and learning methodologies, privileging the articulation between theory and practice. Project-Based Learning (PBL) constitutes the structuring axis of the process, promoting autonomy and the resolution of real problems, which ensures greater motivation and engagement. In addition, the completion of practical exercises and the resolution of cases in class, individually and/or collaboratively, allows for the immediate application of the concepts presented. Collaborative work and peer assessment foster discussion, critical reflection, and the sharing of different perspectives, developing social and communication skills that are fundamental in professional contexts. Throughout the entire process, formative assessment, with continuous feedback from the lecturer, ensures that students can identify and overcome difficulties, progressively consolidating their knowledge and competences.
  • Português
  • Schildt, H. (2022). Java: The Complete Reference. McGraw-Hill Education Coelho, P. (2016). Programação em Java - Curso Completo. 5a Edição Atualizada. FCA.ISBN 9789727228409  
  • 4
  • 0
  • 4
  • 1
  • IPLUSO6382-11144
  • Object-Oriented Programming
  • 11144
  • 6382
  • Computer Applications for Data Science

Algorithms and Data Structures

Category: Discipline
  • Não
  • Many programming projects involve solving complex computational problems, for which simplistic or naive solutions may not be efficient enough. The focus of this course is on how to design good algorithms, and how to analyze their correctness and efficiency. This is among the most basic aspects of good programming which has progressively become a major concern. This is therefore a particularly relevant CU for the the studies’ cycle.
  • Semestral
  • Descrição Data Ponderação
    Teste de avaliação (A definir com os alunos) 40%
    Trabalhos práticos

    (A definir com os alunos)

    		 60%

     

     

    A avaliação final baseia-se numa componente prática, baseada em trabalhos práticos, e, e numa componente teórica baseada num teste escrito sobre os diferentes tópicos abordados. A componente prática terá um peso de 60% e a componente teórica terá um peso de 40%, na nota final. A nota mínima de ambas as componentes será de 8 valores.

     

     

     

    Os alunos poderão ainda ser avaliados por exame de recurso, este valerá 100% da nota final.

     
  • CP1: Complexity, classes, typical functions and algorithm analisys; CP2: Complexity and recursivity (set of recursive problems); CP3: Sorting and selection algorithms; CP4: Sorting algorithms: Insertion Sort, Selection Sort, Merge Sort and Quicksort; CP5: Compare the complexity of sorting algorithms (Quicksort programming); CP6: Abstract data types: Stack and Queue; CP7: Circular arrays, simple lists and linked lists; CP8: Implementing Queue and List (programming using arrays and lists); CP9: Using Dictionaries and Sets; CP10: Binary Trees; CP11: Progrmming binary trees; CP12: Basic notions of graphs.
  • The students that successfully finish this curricular unit will be able to: OA1. Know, understand and use fundamental algorithms and data structures; OA2: Analyze e design recursive algorithms; OA3. Analyze the correctness, complexity and performance of simple algorithms; OA4. Make a reasoned choice of the best suited data structures to each problem and apply them to its resolution; OA5. Design linked data structures and algorithms for it's manipulation  
  • Mandatory
  • Use of ecercise-based learning methodology through which students are encouraged to autonomously develop solutions for problems that are posed to them, and that address most of the topics taught.  
  • Português
  • Cormen, Thomas H. - Algorithms Unlocked. Cambridge, Massachusetts: MIT Press, 2013. Tamassia, Roberto, Goldwasser, Michael H., Goodrich, Michael  T. - Data Structures and Algorithms in Python. First Edition. USA: Wiley, 2013  
  • 4
  • 0
  • 5
  • 1
  • IPLUSO6382-18752
  • Algorithms and Data Structures
  • 18752
  • 6382
  • Computer Applications for Data Science
  1. Data Science Foundations
  2. English
  3. Introduction to Operating Systems
  4. Probabilities and Statistics

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