This course begins by introducing the concepts of efficiency and cost of an algorithm and the basic mathematical tools to analyze them. These tools are then used to study and analyze the design and the different implementations of classic and fundamental algorithms and data structures.
Teachers
Person in charge
Albert Oliveras Llunell (
)
Others
Caroline König (
)
Fernando Gastón Codony (
)
Gabriel Valiente Feruglio (
)
Ilario Bonacina (
)
Jose Carmona Vargas (
)
Salvador Roura Ferret (
)
Santiago Marco Sola (
)
Weekly hours
Theory
2
Problems
1
Laboratory
1
Guided learning
0.4
Autonomous learning
5.6
Competences
Transversal Competences
Teamwork
G5 - To be capable to work as a team member, being just one more member or performing management tasks, with the finality of contributing to develop projects in a pragmatic way and with responsibility sense; to assume compromises taking into account the available resources.
CT3 - Ability to work as a member of an interdisciplinary team, as a normal member or performing direction tasks, in order to develop projects with pragmatism and sense of responsibility, making commitments taking into account the available resources.
CTR3 - Capacity of being able to work as a team member, either as a regular member or performing directive activities, in order to help the development of projects in a pragmatic manner and with sense of responsibility; capability to take into account the available resources.
Entrepreneurship and innovation
G1 - To know and understand the organization of a company and the sciences which govern its activity; capacity to understand the labour rules and the relation between planning, industrial and business strategies, quality and benefit. To develop creativity, entrepreneur spirit and innovation tendency.
CT1 - Know and understand the organization of a company and the sciences that govern its activity; have the ability to understand labor standards and the relationships between planning, industrial and commercial strategies, quality and profit. Being aware of and understanding the mechanisms on which scientific research is based, as well as the mechanisms and instruments for transferring results among socio-economic agents involved in research, development and innovation processes.
CTR1 - Capacity for knowing and understanding a business organization and the science that rules its activity, capability to understand the labour rules and the relationships between planning, industrial and commercial strategies, quality and profit. Capacity for developping creativity, entrepreneurship and innovation trend.
Appropiate attitude towards work
G8 - To have motivation to be professional and to face new challenges, have a width vision of the possibilities of the career in the field of informatics engineering. To feel motivated for the quality and the continuous improvement, and behave rigorously in the professional development. Capacity to adapt oneself to organizational or technological changes. Capacity to work in situations with information shortage and/or time and/or resources restrictions.
CT5 - Capability to be motivated for professional development, to meet new challenges and for continuous improvement. Capability to work in situations with lack of information.
CTR5 - Capability to be motivated by professional achievement and to face new challenges, to have a broad vision of the possibilities of a career in the field of informatics engineering. Capability to be motivated by quality and continuous improvement, and to act strictly on professional development. Capability to adapt to technological or organizational changes. Capacity for working in absence of information and/or with time and/or resources constraints.
Reasoning
G9 - Capacity of critical, logical and mathematical reasoning. Capacity to solve problems in her study area. Abstraction capacity: capacity to create and use models that reflect real situations. Capacity to design and perform simple experiments and analyse and interpret its results. Analysis, synthesis and evaluation capacity.
CT6 - Capability to evaluate and analyze on a reasoned and critical way about situations, projects, proposals, reports and scientific-technical surveys. Capability to argue the reasons that explain or justify such situations, proposals, etc..
CTR6 - Capacity for critical, logical and mathematical reasoning. Capability to solve problems in their area of study. Capacity for abstraction: the capability to create and use models that reflect real situations. Capability to design and implement simple experiments, and analyze and interpret their results. Capacity for analysis, synthesis and evaluation.
Sustainability and social commitment
G2 - To know and understand the complexity of the economic and social phenomena typical of the welfare society. To be capable of analyse and evaluate the social and environmental impact.
CT2 - Capability to know and understand the complexity of economic and social typical phenomena of the welfare society; capability to relate welfare with globalization and sustainability; capability to use technique, technology, economics and sustainability in a balanced and compatible way.
CTR2 - Capability to know and understand the complexity of the typical economic and social phenomena of the welfare society. Capacity for being able to analyze and assess the social and environmental impact.
Third language
G3 - To know the English language in a correct oral and written level, and accordingly to the needs of the graduates in Informatics Engineering. Capacity to work in a multidisciplinary group and in a multi-language environment and to communicate, orally and in a written way, knowledge, procedures, results and ideas related to the technical informatics engineer profession.
CT5 - Achieving a level of spoken and written proficiency in a foreign language, preferably English, that meets the needs of the profession and the labour market.
Effective oral and written communication
G4 - To communicate with other people knowledge, procedures, results and ideas orally and in a written way. To participate in discussions about topics related to the activity of a technical informatics engineer.
Information literacy
G6 [Avaluable] - To manage the acquisition, structuring, analysis and visualization of data and information of the field of the informatics engineering, and value in a critical way the results of this management.
G6.2
- After identifying the parts of an academic document and organizing the bibliographic references, to design and execute a good strategy to make an advanced search with specialized information resources, selecting the pertinent information taking into account relevance and quality criteria.
CT4 - Capacity for managing the acquisition, the structuring, analysis and visualization of data and information in the field of specialisation, and for critically assessing the results of this management.
CTR4 - Capability to manage the acquisition, structuring, analysis and visualization of data and information in the area of informatics engineering, and critically assess the results of this effort.
Autonomous learning
G7 - To detect deficiencies in the own knowledge and overcome them through critical reflection and choosing the best actuation to extend this knowledge. Capacity for learning new methods and technologies, and versatility to adapt oneself to new situations.
Analisis y sintesis
CT7 - Capability to analyze and solve complex technical problems.
Basic
CB6 - Ability to apply the acquired knowledge and capacity for solving problems in new or unknown environments within broader (or multidisciplinary) contexts related to their area of study.
CB7 - Ability to integrate knowledge and handle the complexity of making judgments based on information which, being incomplete or limited, includes considerations on social and ethical responsibilities linked to the application of their knowledge and judgments.
CB8 - Capability to communicate their conclusions, and the knowledge and rationale underpinning these, to both skilled and unskilled public in a clear and unambiguous way.
CB9 - Possession of the learning skills that enable the students to continue studying in a way that will be mainly self-directed or autonomous.
CB1 - That students have demonstrated to possess and understand knowledge in an area of ??study that starts from the base of general secondary education, and is usually found at a level that, although supported by advanced textbooks, also includes some aspects that imply Knowledge from the vanguard of their field of study.
CB2 - That the students know how to apply their knowledge to their work or vocation in a professional way and possess the skills that are usually demonstrated through the elaboration and defense of arguments and problem solving within their area of ??study.
CB3 - That students have the ability to gather and interpret relevant data (usually within their area of ??study) to make judgments that include a reflection on relevant social, scientific or ethical issues.
CB4 - That the students can transmit information, ideas, problems and solutions to a specialized and non-specialized public.
CB5 - That the students have developed those learning skills necessary to undertake later studies with a high degree of autonomy
CB10 - Possess and understand knowledge that provides a basis or opportunity to be original in the development and/or application of ideas, often in a research context.
Transversals
CT1 - Entrepreneurship and innovation. Know and understand the organization of a company and the sciences that govern its activity; Have the ability to understand labor standards and the relationships between planning, industrial and commercial strategies, quality and profit.
CT2 - Sustainability and Social Commitment. To know and understand the complexity of economic and social phenomena typical of the welfare society; Be able to relate well-being to globalization and sustainability; Achieve skills to use in a balanced and compatible way the technique, the technology, the economy and the sustainability.
CT3 - Efficient oral and written communication. Communicate in an oral and written way with other people about the results of learning, thinking and decision making; Participate in debates on topics of the specialty itself.
CT4 - Teamwork. Be able to work as a member of an interdisciplinary team, either as a member or conducting management tasks, with the aim of contributing to develop projects with pragmatism and a sense of responsibility, taking commitments taking into account available resources.
CT5 - Solvent use of information resources. Manage the acquisition, structuring, analysis and visualization of data and information in the field of specialty and critically evaluate the results of such management.
CT6 - Autonomous Learning. Detect deficiencies in one's own knowledge and overcome them through critical reflection and the choice of the best action to extend this knowledge.
CT7 - Third language. Know a third language, preferably English, with an adequate oral and written level and in line with the needs of graduates.
Gender perspective
CT6 - An awareness and understanding of sexual and gender inequalities in society in relation to the field of the degree, and the incorporation of different needs and preferences due to sex and gender when designing solutions and solving problems.
Technical Competences
Common technical competencies
CT1 - To demonstrate knowledge and comprehension of essential facts, concepts, principles and theories related to informatics and their disciplines of reference.
CT2 - To use properly theories, procedures and tools in the professional development of the informatics engineering in all its fields (specification, design, implementation, deployment and products evaluation) demonstrating the comprehension of the adopted compromises in the design decisions.
CT2.3
- To design, develop, select and evaluate computer applications, systems and services and, at the same time, ensure its reliability, security and quality in function of ethical principles and the current legislation and normative.
CT2.4
- To demonstrate knowledge and capacity to apply the needed tools for storage, processing and access to the information system, even if they are web-based systems.
CT3 - To demonstrate knowledge and comprehension of the organizational, economic and legal context where her work is developed (proper knowledge about the company concept, the institutional and legal framework of the company and its organization and management)
CT4 - To demonstrate knowledge and capacity to apply the basic algorithmic procedures of the computer science technologies to design solutions for problems, analysing the suitability and complexity of the algorithms.
CT4.1
- To identify the most adequate algorithmic solutions to solve medium difficulty problems.
CT4.2
- To reason about the correction and efficiency of an algorithmic solution.
CT4.3
- To demonstrate knowledge and capacity to apply the fundamental principles and the basic techniques of the intelligent systems and its practical application.
CT5 - To analyse, design, build and maintain applications in a robust, secure and efficient way, choosing the most adequate paradigm and programming languages.
CT5.1
- To choose, combine and exploit different programming paradigms, at the moment of building software, taking into account criteria like ease of development, efficiency, portability and maintainability.
CT5.2
- To know, design and use efficiently the most adequate data types and data structures to solve a problem.
CT5.3
- To design, write, test, refine, document and maintain code in an high level programming language to solve programming problems applying algorithmic schemas and using data structures.
CT5.4
- To design the programs¿ architecture using techniques of object orientation, modularization and specification and implementation of abstract data types.
CT5.5
- To use the tools of a software development environment to create and develop applications.
CT6 - To demonstrate knowledge and comprehension about the internal operation of a computer and about the operation of communications between computers.
CT7 - To evaluate and select hardware and software production platforms for executing applications and computer services.
CT8 - To plan, conceive, deploy and manage computer projects, services and systems in every field, to lead the start-up, the continuous improvement and to value the economical and social impact.
CT8.6
- To demonstrate the comprehension of the importance of the negotiation, effective working habits, leadership and communication skills in all the software development environments.
CT8.7
- To control project versions and configurations.
Technical competencies
CE1 - Skillfully use mathematical concepts and methods that underlie the problems of science and data engineering.
CE2 - To be able to program solutions to engineering problems: Design efficient algorithmic solutions to a given computational problem, implement them in the form of a robust, structured and maintainable program, and check the validity of the solution.
CE3 - Analyze complex phenomena through probability and statistics, and propose models of these types in specific situations. Formulate and solve mathematical optimization problems.
CE4 - Use current computer systems, including high performance systems, for the process of large volumes of data from the knowledge of its structure, operation and particularities.
CE5 - Design and apply techniques of signal processing, choosing between different technological tools, including those of Artificial vision, speech recognition and multimedia data processing.
CE6 - Build or use systems of processing and comprehension of written language, integrating it into other systems driven by the data. Design systems for searching textual or hypertextual information and analysis of social networks.
CE7 - Demonstrate knowledge and ability to apply the necessary tools for the storage, processing and access to data.
CE8 - Ability to choose and employ techniques of statistical modeling and data analysis, evaluating the quality of the models, validating and interpreting them.
CE9 - Ability to choose and employ a variety of automatic learning techniques and build systems that use them for decision making, even autonomously.
CE10 - Visualization of information to facilitate the exploration and analysis of data, including the choice of adequate representation of these and the use of dimensionality reduction techniques.
CE11 - Within the corporate context, understand the innovation process, be able to propose models and business plans based on data exploitation, analyze their feasibility and be able to communicate them convincingly.
CE12 - Apply the project management practices in the integral management of the data exploitation engineering project that the student must carry out in the areas of scope, time, economic and risks.
CE13 - (End-of-degree work) Plan and design and carry out projects of a professional nature in the field of data engineering, leading its implementation, continuous improvement and valuing its economic and social impact. Defend the project developed before a university court.
Especifics
CE1 - Develop efficient algorithms based on the knowledge and understanding of the computational complexity theory and considering the main data structures within the scope of data science
CE2 - Apply the fundamentals of data management and processing to a data science problem
CE3 - Apply data integration methods to solve data science problems in heterogeneous data environments
CE4 - Apply scalable storage and parallel data processing methods, including data streams, once the most appropriate methods for a data science problem have been identified
CE5 - Model, design, and implement complex data systems, including data visualization
CE6 - Design the Data Science process and apply scientific methodologies to obtain conclusions about populations and make decisions accordingly, from both structured and unstructured data and potentially stored in heterogeneous formats.
CE7 - Identify the limitations imposed by data quality in a data science problem and apply techniques to smooth their impact
CE8 - Extract information from structured and unstructured data by considering their multivariate nature.
CE9 - Apply appropriate methods for the analysis of non-traditional data formats, such as processes and graphs, within the scope of data science
CE10 - Identify machine learning and statistical modeling methods to use and apply them rigorously in order to solve a specific data science problem
CE11 - Analyze and extract knowledge from unstructured information using natural language processing techniques, text and image mining
CE12 - Apply data science in multidisciplinary projects to solve problems in new or poorly explored domains from a data science perspective that are economically viable, socially acceptable, and in accordance with current legislation
CE13 - Identify the main threats related to ethics and data privacy in a data science project (both in terms of data management and analysis) and develop and implement appropriate measures to mitigate these threats
CE14 - Execute, present and defend an original exercise carried out individually in front of an academic commission, consisting of an engineering project in the field of data science synthesizing the competences acquired in the studies
Technical Competences of each Specialization
Information systems specialization
CSI2 - To integrate solutions of Information and Communication Technologies, and business processes to satisfy the information needs of the organizations, allowing them to achieve their objectives effectively.
CSI3 - To determine the requirements of the information and communication systems of an organization, taking into account the aspects of security and compliance of the current normative and legislation.
CSI4 - To participate actively in the specification, design, implementation and maintenance of the information and communication systems.
CSI1 - To demonstrate comprehension and apply the principles and practices of the organization, in a way that they could link the technical and management communities of an organization, and participate actively in the user training.
Software engineering specialization
CES1 - To develop, maintain and evaluate software services and systems which satisfy all user requirements, which behave reliably and efficiently, with a reasonable development and maintenance and which satisfy the rules for quality applying the theories, principles, methods and practices of Software Engineering.
CES2 - To value the client needs and specify the software requirements to satisfy these needs, reconciling conflictive objectives through searching acceptable compromises, taking into account the limitations related to the cost, time, already developed systems and organizations.
CES3 - To identify and analyse problems; design, develop, implement, verify and document software solutions having an adequate knowledge about the current theories, models and techniques.
Information technology specialization
CTI1 - To define, plan and manage the installation of the ICT infrastructure of the organization.
CTI2 - To guarantee that the ICT systems of an organization operate adequately, are secure and adequately installed, documented, personalized, maintained, updated and substituted, and the people of the organization receive a correct ICT support.
CTI3 - To design solutions which integrate hardware, software and communication technologies (and capacity to develop specific solutions of systems software) for distributed systems and ubiquitous computation devices.
CTI4 - To use methodologies centred on the user and the organization to develop, evaluate and manage applications and systems based on the information technologies which ensure the accessibility, ergonomics and usability of the systems.
Computer engineering specialization
CEC1 - To design and build digital systems, including computers, systems based on microprocessors and communications systems.
CEC2 - To analyse and evaluate computer architectures including parallel and distributed platforms, and develop and optimize software for these platforms.
CEC3 - To develop and analyse hardware and software for embedded and/or very low consumption systems.
CEC4 - To design, deploy, administrate and manage computer networks, and manage the guarantee and security of computer systems.
Computer science specialization
CCO1 - To have an in-depth knowledge about the fundamental principles and computations models and be able to apply them to interpret, select, value, model and create new concepts, theories, uses and technological developments, related to informatics.
CCO2 - To develop effectively and efficiently the adequate algorithms and software to solve complex computation problems.
CCO3 - To develop computer solutions that, taking into account the execution environment and the computer architecture where they are executed, achieve the best performance.
Academic
CEA1 - Capability to understand the basic principles of the Multiagent Systems operation main techniques , and to know how to use them in the environment of an intelligent service or system.
CEA2 - Capability to understand the basic operation principles of Planning and Approximate Reasoning main techniques, and to know how to use in the environment of an intelligent system or service.
CEA3 - Capability to understand the basic operation principles of Machine Learning main techniques, and to know how to use on the environment of an intelligent system or service.
CEA4 - Capability to understand the basic operation principles of Computational Intelligence main techniques, and to know how to use in the environment of an intelligent system or service.
CEA5 - Capability to understand the basic operation principles of Natural Language Processing main techniques, and to know how to use in the environment of an intelligent system or service.
CEA6 - Capability to understand the basic operation principles of Computational Vision main techniques, and to know how to use in the environment of an intelligent system or service.
CEA7 - Capability to understand the problems, and the solutions to problems in the professional practice of Artificial Intelligence application in business and industry environment.
CEA8 - Capability to research in new techniques, methodologies, architectures, services or systems in the area of ??Artificial Intelligence.
CEA9 - Capability to understand Multiagent Systems advanced techniques, and to know how to design, implement and apply these techniques in the development of intelligent applications, services or systems.
CEA10 - Capability to understand advanced techniques of Human-Computer Interaction, and to know how to design, implement and apply these techniques in the development of intelligent applications, services or systems.
CEA11 - Capability to understand the advanced techniques of Computational Intelligence, and to know how to design, implement and apply these techniques in the development of intelligent applications, services or systems.
CEA12 - Capability to understand the advanced techniques of Knowledge Engineering, Machine Learning and Decision Support Systems, and to know how to design, implement and apply these techniques in the development of intelligent applications, services or systems.
CEA13 - Capability to understand advanced techniques of Modeling , Reasoning and Problem Solving, and to know how to design, implement and apply these techniques in the development of intelligent applications, services or systems.
CEA14 - Capability to understand the advanced techniques of Vision, Perception and Robotics, and to know how to design, implement and apply these techniques in the development of intelligent applications, services or systems.
Professional
CEP1 - Capability to solve the analysis of information needs from different organizations, identifying the uncertainty and variability sources.
CEP2 - Capability to solve the decision making problems from different organizations, integrating intelligent tools.
CEP3 - Capacity for applying Artificial Intelligence techniques in technological and industrial environments to improve quality and productivity.
CEP4 - Capability to design, write and report about computer science projects in the specific area of ??Artificial Intelligence.
CEP5 - Capability to design new tools and new techniques of Artificial Intelligence in professional practice.
CEP6 - Capability to assimilate and integrate the changing economic, social and technological environment to the objectives and procedures of informatic work in intelligent systems.
CEP7 - Capability to respect the legal rules and deontology in professional practice.
CEP8 - Capability to respect the surrounding environment and design and develop sustainable intelligent systems.
Direcció i gestió
CDG1 - Capability to integrate technologies, applications, services and systems of Informatics Engineering, in general and in broader and multicisciplinary contexts.
CDG2 - Capacity for strategic planning, development, direction, coordination, and technical and economic management in the areas of Informatics Engineering related to: systems, applications, services, networks, infrastructure or computer facilities and software development centers or factories, respecting the implementation of quality and environmental criteria in multidisciplinary working environments .
CDG3 - Capability to manage research, development and innovation projects in companies and technology centers, guaranteeing the safety of people and assets, the final quality of products and their homologation.
Especifics
CTE1 - Capability to model, design, define the architecture, implement, manage, operate, administrate and maintain applications, networks, systems, services and computer contents.
CTE2 - Capability to understand and know how to apply the operation and organization of Internet, technologies and protocols for next generation networks, component models, middleware and services.
CTE3 - Capability to secure, manage, audit and certify the quality of developments, processes, systems, services, applications and software products.
CTE4 - Capability to design, develop, manage and evaluate mechanisms of certification and safety guarantee in the management and access to information in a local or distributed processing.
CTE5 - Capability to analyze the information needs that arise in an environment and carry out all the stages in the process of building an information system.
CTE6 - Capability to design and evaluate operating systems and servers, and applications and systems based on distributed computing.
CTE7 - Capability to understand and to apply advanced knowledge of high performance computing and numerical or computational methods to engineering problems.
CTE8 - Capability to design and develop systems, applications and services in embedded and ubiquitous systems .
CTE9 - Capability to apply mathematical, statistical and artificial intelligence methods to model, design and develop applications, services, intelligent systems and knowledge-based systems.
CTE10 - Capability to use and develop methodologies, methods, techniques, special-purpose programs, rules and standards for computer graphics.
CTE11 - Capability to conceptualize, design, develop and evaluate human-computer interaction of products, systems, applications and informatic services.
CTE12 - Capability to create and exploit virtual environments, and to the create, manageme and distribute of multimedia content.
Computer graphics and virtual reality
CEE1.1 - Capability to understand and know how to apply current and future technologies for the design and evaluation of interactive graphic applications in three dimensions, either when priorizing image quality or when priorizing interactivity and speed, and to understand the associated commitments and the reasons that cause them.
CEE1.2 - Capability to understand and know how to apply current and future technologies for the evaluation, implementation and operation of virtual and / or increased reality environments, and 3D user interfaces based on devices for natural interaction.
CEE1.3 - Ability to integrate the technologies mentioned in CEE1.2 and CEE1.1 skills with other digital processing information technologies to build new applications as well as make significant contributions in multidisciplinary teams using computer graphics.
Computer networks and distributed systems
CEE2.1 - Capability to understand models, problems and algorithms related to distributed systems, and to design and evaluate algorithms and systems that process the distribution problems and provide distributed services.
CEE2.2 - Capability to understand models, problems and algorithms related to computer networks and to design and evaluate algorithms, protocols and systems that process the complexity of computer communications networks.
CEE2.3 - Capability to understand models, problems and mathematical tools to analyze, design and evaluate computer networks and distributed systems.
Advanced computing
CEE3.1 - Capability to identify computational barriers and to analyze the complexity of computational problems in different areas of science and technology as well as to represent high complexity problems in mathematical structures which can be treated effectively with algorithmic schemes.
CEE3.2 - Capability to use a wide and varied spectrum of algorithmic resources to solve high difficulty algorithmic problems.
CEE3.3 - Capability to understand the computational requirements of problems from non-informatics disciplines and to make significant contributions in multidisciplinary teams that use computing.
High performance computing
CEE4.1 - Capability to analyze, evaluate and design computers and to propose new techniques for improvement in its architecture.
CEE4.2 - Capability to analyze, evaluate, design and optimize software considering the architecture and to propose new optimization techniques.
CEE4.3 - Capability to analyze, evaluate, design and manage system software in supercomputing environments.
Service engineering
CEE5.1 - Capability to participate in improvement projects or to create service systems, providing in particular: a) innovation and research proposals based on new uses and developments of information technologies, b) application of the most appropriate software engineering and databases principles when developing information systems, c) definition, installation and management of infrastructure / platform necessary for the efficient running of service systems.
CEE5.2 - Capability to apply obtained knowledge in any kind of service systems, being familiar with some of them, and thorough knowledge of eCommerce systems and their extensions (eBusiness, eOrganization, eGovernment, etc.).
CEE5.3 - Capability to work in interdisciplinary engineering services teams and, provided the necessary domain experience, capability to work autonomously in specific service systems.
Specific
CEC1 - Ability to apply scientific methodologies in the study and analysis of phenomena and systems in any field of Information Technology as well as in the conception, design and implementation of innovative and original computing solutions.
CEC2 - Capacity for mathematical modelling, calculation and experimental design in engineering technology centres and business, particularly in research and innovation in all areas of Computer Science.
CEC3 - Ability to apply innovative solutions and make progress in the knowledge that exploit the new paradigms of Informatics, particularly in distributed environments.
Generic Technical Competences
Generic
CG1 - Identify and apply the most appropriate data management methods and processes to manage the data life cycle, considering both structured and unstructured data
CG2 - Identify and apply methods of data analysis, knowledge extraction and visualization for data collected in disparate formats
CG3 - Define, design and implement complex systems that cover all phases in data science projects
CG4 - Design and implement data science projects in specific domains and in an innovative way
CG5 - To be able to draw on fundamental knowledge and sound work methodologies acquired during the studies to adapt to the new technological scenarios of the future.
CG6 - Capacity for general management, technical management and research projects management, development and innovation in companies and technology centers in the area of Computer Science.
CG7 - Capacity for implementation, direction and management of computer manufacturing processes, with guarantee of safety for people and assets, the final quality of the products and their homologation.
CG8 - Capability to apply the acquired knowledge and to solve problems in new or unfamiliar environments inside broad and multidisciplinary contexts, being able to integrate this knowledge.
CG9 - Capacity to understand and apply ethical responsibility, law and professional deontology of the activity of the Informatics Engineering profession.
CG10 - Capacity to apply economics, human resources and projects management principles, as well as legislation, regulation and standardization of Informatics.
Objectives
Understand the definitions of the Big-O, Omega and Theta asymptotic notations and their usefulness in characterising the efficiency of algorithms in time and space.
Related competences:
CT4.2,
Calculate the efficiency of iterative algorithms using appropriate calculation rules.
Related competences:
CT4.2,
Describe the efficiency of recursive algorithms using recurrence relations and understand and apply master theorems to solve them.
Related competences:
CT4.2,
Design algorithms for solving various problems of medium difficulty with time and space constraints.
Related competences:
CT4.1,
CT4.2,
Compare the efficiency of different algorithms for solving the same problem and select the most appropriate one.
Related competences:
CT4.1,
CT4.2,
Understand, explain, design, analyse, compare and implement algorithms (such as mergesort, quicksort, Karatsuba, Strassen, etc.) using divide and conquer.
Related competences:
CT4.1,
CT4.2,
CT5.3,
Understand, explain, design, analyse, compare and implement the main data structures that can be used to implement dictionaries (tables, sorted tables, lists, sorted lists, hash tables, binary search trees, AVL trees).
Related competences:
CT4.1,
CT4.2,
CT5.2,
CT2.4,
Understand, explain, design, analyse, compare and implement the main data structures that can be used to implement priority queues (trees, heaps).
Related competences:
CT4.1,
CT4.2,
CT5.2,
CT2.4,
Understand, explain, design, analyse, compare and implement algorithms that solve classic graph problems such as traversals, topological sorts, shortest paths, etc.
Related competences:
CT4.1,
CT4.2,
CT5.2,
CT2.4,
Understand, explain, design, analyse, compare and implement exhaustive search algorithms using the backtracking technique.
Related competences:
CT4.1,
CT4.2,
CT2.4,
CT4.3,
Identify computational limits: understand the implications of the question "P = NP?", understand the statement of Cook-Levin's Theorem, and recognise and identify several classic NP-complete problems.
Related competences:
CT4.2,
Complete and modify C++ programming language implementations of several algorithms to solve medium-difficulty problems
Related competences:
CT4.2,
CT5.2,
CT5.1,
Identify and propose solutions to efficiency problems in algorithms and programs written in the C++ programming language.
Related competences:
CT4.1,
CT4.2,
CT5.2,
CT2.4,
CT2.3,
Analyse a strategy game for designing and programming an effective, efficient, collaborative and competitive player that maximises the chances of winning the game and is capable of establishing partnerships and coordinating with other players.
Related competences:
CT8.6,
CT8.7,
CT4.1,
CT4.2,
CT5.2,
CT5.4,
CT5.5,
G6.2,
CT2.4,
CT4.3,
CT5.1,
CT5.3,
CT2.3,
Apply information search strategies (for bibliographic references, scientific articles, patents, credible web resources, etc.) and, making an ethical use of the compiled information and properly citing sources, produce a well-structured document describing a well-known algorithm that solves a given problem.
Related competences:
G6.2,
Compute the cost of an algorithm in the worst, best and average cases.
Related competences:
CT4.2,
Contents
Analysis of Algorithms
Cost in time and space. Worst case, best case and average case. Asymptotic notation. Analysis of the cost of iterative and recursive algorithms.
Divide and conquer
Principles: partition into subproblems, recombination of solutions. Examples: mergesort, quicksort, Karatsuba's algorithm for multiplying large numbers, Strassen's algorithm for matrix multiplication.
Dictionaries
Operations of dictionaries and ordered dictionaries. Basic implementations: tables and lists. Advanced implementations: hash tables, binary search trees, AVL trees.
Priority Queues
Operations of priority queues. Implementations with heaps. Heapsort.
Graphs
Representations: adjacency matrices, adjacency lists and implicit representation. Depth-first search (DFS). Breadth-first search (BFS). Topological sort. Dijkstra's algorithm for shortest paths. Prim's algorithm for minimum spanning trees.
Exhaustive Search and Generation
Principles: solution space, partial solutions, pruning. Generation of subsets and permutations. Examples: knapsack, travelling salesman.
Notions of Intractability
Basic introduction to P and NP classes, Cook-Levin's Theorem, reductions and NP-completeness.
Goals corresponding to learning objective 15 will be assessed.
A statement describing a strategy game will be published. Students will have to program a player for this game (i.e. implement a strategy aimed at winning).
A competition will be carried out in which students will play against each other, from which a ranking will be obtained. To participate in the competition, the players of the students will have to pass a qualification test.
The grade corresponding to this part will be computed from the position in the ranking in a proportional way, ensuring that the winner gets a 10 and that all students with a qualified player get a minimum of 5. Those students who have not been able to qualify a player will get a 0. Objectives:14 Week:
9 (Outside class hours) Type:
assigment
Theory
0h
Problems
0h
Laboratory
0h
Guided learning
0h
Autonomous learning
8h
Game development
Learning the most appropriate strategies for the Game. Learning the solution to the most common questions about the Game. Objectives:14 Contents:
Self-learning through the BRGF library science tutorials on: intellectual property, the ethical use of information and the use of reference management software. Objectives:15
Theory
0h
Problems
0h
Laboratory
0h
Guided learning
0h
Autonomous learning
2.5h
Practical on sound use of computer resources.
Goals corresponding to learning objective 16 will be assessed.
A statement will be published consisting in the description of a computational problem and the name of an algorithm to solve it. Students will conduct research (in the library, on the web, etc.) into the problem and the algorithm and will write a brief, well-structured document that properly lists sources.
The document should be handed in on the day of the final exam.
Students' generic competences will be assessed on the basis of this document. Objectives:15 Week:
14 (Outside class hours) Type:
assigment
Theory
0h
Problems
0h
Laboratory
0h
Guided learning
0h
Autonomous learning
3h
Computer-based exam
Laboratory aspects, i.e. implementation aspects, of the topics covered up to the date will be assessed.
Students will be issued two or three problems in front of their computer. These problems will have a statement, one or more public test suites and, possibly, an already implemented code. When students are ready to submit programs for particular problems, they upload them to an automatic judge which returns a verdict on program behaviour. Students can submit up to 10 solutions for the same problem. The lecturer will correct the last solution submitted for each problem. Objectives:78910 Week:
15 (Outside class hours) Type:
lab exam
Theory
0h
Problems
0h
Laboratory
2h
Guided learning
0h
Autonomous learning
4h
Final Exam
Learning objectives for content corresponding to topics 1 to 7 will be assessed. Objectives:12354678910121311 Week:
15 (Outside class hours) Type:
theory exam
Theory
3h
Problems
0h
Laboratory
0h
Guided learning
0h
Autonomous learning
10h
Teaching methodology
Topics are explained in a practical way through the use of numerous examples.
Theory classes cover the required concepts and techniques, which are put into practice in the problem-solving and laboratory classes by means of a collection of problems and exercises from an automatic judge.
The two-hour theory class will take place once a week. The two-hour laboratory class will take place once a fortnight. The two-hour problem-solving class will take place once a fortnight.
Programming for the game integrates knowledge and skills of the entire course.
The C++ programming language is used for this course.
Evaluation methodology
NPP = written mid-semester exam grade (0 to 10)
NO = computer-based exam grade (0 to 10)
NF = final exam grade (0 to 10)
NJ = game grade (0 to 10)
MIT OpenCourseWare: és una publicació gratuïta dels materials dels cursos del Massachusets Institute of Technology (MIT) que mostra la majoria de temes que s'ensenyen en el MIT. Conté apunts, exercicis, exercicis resolts, exàmens i videos de classes.
MIT OpenCourseWare: es una publicación gratuita de los materiales de los cursos del Massachusets Institute of Technology (MIT) que muestra la mayoría de temas que se enseñan en el MIT. Contiene apuntes, ejercicios, ejercicios resueltos, exámenes y vídeos de clases.
MIT OpenCourseWare: it is a free publication of the materials of the courses of the Massachusets Institute of Technology (MIT) that shows most of the topics that are taught in MIT. Contains notes, exercises, solved exercises, exams and videos of classes. http://ocw.mit.edu/courses/#electrical-engineering-and-computer-science
Algorithms Courses on the WWW: és un llistat exhaustiu d'enllaços a portals web relacionats amb algorísmia i complexitat: cursos de diverses universitats, software, aplicacions gràfiques, pàgines personals d'investigadors coneguts, entre d'altres coses.
Algorithms Courses on the WWW: es un listado exhaustivo de enlaces a portales web relacionados con la algoritmia y complejidad: cursos de varias universidades, software, aplicaciones gráficas, páginas personales de investigadores conocidos, entre otras cosas.
Algorithms Courses on the WWW: it is an exhaustive listing of links to web sites related to algorithms and complexity: courses of several universities, software, graphic applications, personal pages of well-known researchers, among other things. http://www.cs.pitt.edu/~kirk/algorithmcourses/index.html
The Stony Brook Algorithm Repository: és un portal web amb una col·lecció d'implementacions de més de setanta algorismes fonamentals d'optimització combinatòria.
The Stony Brook Algorithm Repository: es un portal web con una colección de implementaciones de más de setenta algoritmos fundamentales de optimitzación combinatoria.
The Stony Brook Algorithm Repository: it is a web site with a collection of implementations of more than seventy fundamental algorithms of combinatorial optimitzation. http://www.cs.sunysb.edu/~algorith/