winter... · web viewbrownian motion and stochastic calculus, springer-verlag, berlin 1988. course...
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Winter semester 2018/19Courses offer at Faculty of Physics, Mathematics and Computer Science:
1. Abstract Algebra2. Applied Statistics for Engineers3. Cryptography4. Data Mining with R5. Differential Geometry6. Elements of Artificial Intelligence7. Engineering Ethics8. Graph theory9. Introduction to Databases10. Number Theory11. LTE/LTE-A Basics12. Mathematical Finance13. Neural Networks14. Object - Oriented programming15. Operations and production process management for engineers16. Parallel and Distributed Programming17. Software Engineering18. Stochastic Modelling
Please, note that the minimum number of students in a group required to open a course is 7. For more information regarding courses please contact Exchange Coordinator at FPMCS - Ms Margareta Wiciak, PhD, contact: [email protected]
Courses description:19.
Course title: Abstract Algebra Institute/Division: Institute of Mathematics, Faculty of Physics, Mathematics and
Computer Science Course code: F2-AErasmus subject code: 11.1 Mathematics Number of contact hours: 45 hours Course duration: 1 semester ECTS credits: 6 Course description: Groups, Rings and Fields. Substructures and products. Quotient
structures. Normal subgroups, ideals. Isomorphism theorems. Selected topics in group theory: Sylow subgroups, solvability, nilpotency. Integral domains, factorisation. Fundamental Theorem of Algebra.
Literature: T. Hungerford, Abstract Algebra, Saunders College Publishing, many edition D. Dummit, R. Foote, Abstract Algebra, Prentice Hall
Course type: lectures (30 hours), problem sessions (30 hours) in small group Assessment method: two tests during the semester, final exam Prerequisites: Linear Algebra Primary target group: Mathematics majors; at the sophomore or junior level. Available also to
CSc, Physics and Engineering majors. Lecturer: Members of the faculty of the Mathematics Institute Contact person: Katarzyna Pałasińska, e-mail: [email protected] Deadline for application: 15th of September Remarks:
Course title: Applied Statistics for EngineersInstitute/Division: Institute of Mathematics, Faculty of Physics,
Mathematics and Computer ScienceCourse code: F5-ASErasmus subject code: 11.2 StatisticsNumber of contact hours: 45 hoursCourse duration: 1 semesterECTS credits: 6Course description: This course planned for 45 hrs is designed for engineers
and is based on more than 10 years teacher's experience of providing such class for engineers at University of California. The topics include: regression modelling, reliability, analysis of variance. One of the bestEnglish textbook in the world for such class is of Mendenhall "Probability and Statistics for Engineers". The focus of the class will be on applications, problem-related concepts and computer driven data analysis. The level is intermediate and elementary probability and statistics course is a prerequisite.
Literature: Mendenhall, "Probability and Statistics for Engineers"Course type: Lectures, classesAssessment method: Two tests during the semester, final examPrerequisites: elementary probability and statisticsPrimary target group: Computer Science, Engineering Sciences, I levelLecturer: Jacek Leśkow, PhDContact person: Jacek Leśkow , e-mail: [email protected] for application: 15th of SeptemberRemarks:
Course title: Cryptography Institute/Division: F-3, Institute of Computer Modelling Course code: F31-C Erasmus subject code: Informatics, Computer Science Number of contact hours: 45 hours Course duration: 1 semester ECTS credits: 6 Course description: Integers. Divisibility of integers. Prime numbers. Euclidean
algorithm. Factoring into primes. Congruences. Operations modulo. Fermat’s Little Theorem. The Chinese Remainder Theorem. Euler function. Fast exponentiation. Finite groups and fields. Element orders. Encryption schemes. Symmetric cryptosystems: substitution ciphers, block ciphers, permutation ciphers. System DES. Public – Key systems: RSA, discrete logarithm. Hash functions. Digital signatures.
Literature: J.A.Buchmann, Introduction to cryptography, Springer, New York 2000. N.Ferguson, B.Schneier, Practical cryptography, Wiley & Sons, New York 2003. N.Koblitz, A course in number theory and cryptography, Springer, Berlin 1998.
Course type: Lectures and exercises Assessment method: Attendance, ability of solving of simple exercises, exam Prerequisites: General algebra Primary target group: 3-rd – 4-th year computer science students Lecturer: Agnieszka Jakóbik, PhD Contact person: Agnieszka Jakóbik, PhD, [email protected] for application: 15th of September Remarks:
Course title: Data Mining with R Institute/Division: F-3, Institute of Computer Science Course code: F3-R Erasmus subject code: Informatics, Computer ScienceNumber of contact hours: 45 hours Course duration: 1 semester ECTS credits: 6Course description: The students will learn the most current techniques to process large
datasets using the very popular and very simple R language, which will be used to extract valuable knowledge from data, to classify and to cluster it within datasets and to perform analytical predictions, based on the available datasets.
Literature: 1. Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani, An Introduction to Statistical Learning with Applications in R, Springer, Sixth edition, Springer, 2015, available on the Internet: http://www-bcf.usc.edu/~gareth/ISL/ISLR Sixth Printing.pdf2. Yanchang Zhao, R and Data Mining: Examples and Case Studies, Elsevier, 2012-2014, available on the Internet together with source codes of all examples: http://www.RDataMining.com3. Many additional materials and links will be given to all students during the lectures.
Course type: Lectures and exercisesAssessment method: There will be few homeworks. Each one should be returned to the
teacher up to 2 weeks after distribution). Prerequisites: None Primary target group: computer science students of the 3rd or 4th yearLecturer: Barbara Borowik, PhD Contact person: Barbara Borowik, PhD; [email protected] for application: 15th of SeptemberRemarks:
Course title: Differential GeometryInstitute/Division: Institute of MathematicsCourse code: F2-DGErasmus subject code: 11.1 MathematicsNumber of contact hours: 45 hoursCourse duration: 1 semester ECTS credits: 6Course description:1. Manifolds, charts, atlas, sub-manifolds, smooth maps, submersion and immersion.2. Vector bundles, tangent and cotangent bundle , vector and tensor fields, one-parameter group of a vector field, differential forms, the exterior differentiation d, the Lie differentiation.3. The linear connection on a vector bundle, curvature tensor, torsion tensor, geodesics, normal coordinates, Bianchi identities. 4. Riemannian geometry, Riemannian space, the Levi-Civita connection, sectional curvature, manifolds of constant sectional curvature, metric In a Riemannian space, the Hopf-Rinov theorem.Literature: K. Nomizu, S. Kobayashi Foundations of differential geometry
Course type: Lectures and exercises Assessment method: Attendance , final examPrerequisites:Primary target group: Students of mathematics and physicsLecturer: dr hab. Włodzimierz JelonekContact person: dr hab. Włodzimierz Jelonek, [email protected] for application: 15th of SeptemberRemarks:
Course title: Elements of Artificial Intelligence Institute/Division: F-3, Institute of Computer Science Course code: F32-EAI Erasmus subject code: Informatics, Computer Science Number of contact hours: 45 hours Course duration: 1 semester ECTS credits: 6 Course description: The module introduces AI techniques for optimization, search,
reasoning about actions, representing and reasoning with uncertainty and AI planning. The search techniques are applicable to problems in AI and optimisation and include: heuristic search, hill climbing, genetic algorithms, simulated annealing, tabu search, local beam search and SAT. The planning techniques are applicable to complex task planning and planning for mobile robots. Topics covered include: approaches to reasoning about actions and searching for plans efficiently, design and fine-tunning of heuristics.
Literature: Basic literature on the subject of artificial intelligence Course type: Lectures and laboratories Assessment method: Attendance, evaluation of small projects, exam Prerequisites: programming languages Primary target group: 3-rd – 4-th year computer science students Lecturer: Prof. Andrzej Bargieła Contact person: Prof. Andrzej Bargieła Deadline for application: 15th of September Remarks:
Course title: Engineering EthicsInstitute/Division: F-4, Institute of Economics Sociology and Philosophy /Faculty
of Physics, Mathematics and Computer Science/Course code: F4-EEErasmus subject code: 08.1Number of contact hours: 15Course duration: 1 semesterECTS credits: 2Course description: This course introduces the students into the moral aspects of
engineering profession and practices. An introductionto morality and ethics. Moral subject, action, freedom and responsibility. Ethical theories: deontological ethics, utilitarianism and ethics of virtue. Engineer’s responsibility for public safety and health. Responsibilities to employers and clients. Professional development and virtues. Rights of engineers. Conflicts of interest and whistle-blowing. Engineers as managers; ethical problems at work place. Engineers as experts. Ethical codes and case studies
Literature: M. Martin, R. Schinzinger, 1996, Ethics in Engineering, The McGraw-Hill Companies, Inc.Ch. Harris, Jr., M. Pritchard, M. Rabins, 2005, Engineering Ethics: Concepts and Cases, Wadsworth
Course type: Lectures and seminarsAssessment method: Attendance and final examPrerequisites: NonePrimary target group: 2nd and 3rd year studentsLecturer: Marek Pyka, PhDContact person: Marek Pyka, PhD, phone (+48 12) 628 24 80; e-mail:
[email protected] for application: 15 September
Course title: Graph TheoryInstitute/Division: Institute of Mathematics, Faculty of Physics, Mathematics and
Computer ScienceCourse code: F2-GThErasmus subject code: 11.1 MathematicsNumber of contact hours: 45 hoursCourse duration: 1 semesterECTS credits: 6Course description: This is an elementary graph theory course for students majoring
in Mathematics, Computer Science, Physics or Engineering. Can be offered as an elective to both foreign and native Polish students. The emphasis is on showing how various problems originating in science, engineering and in real life are (often unexpectidely) amenable to graph theory methods. We cover: basic notions and theorems of the theory; routing problems (Euler and Hamiltonian circuits, Chinese Postman problem, Minimum Network Problem, TSP), optimization problems (like scheduling problems ), graph coloring, matching in bipartite graphs and flows in networks. Well known algorithms, such as Dijkstra’s, Floyd-Warshall’s, Fleury’s, Kruskal’s, Prim’s, Ford-Fulkerson’s and someapproximate algorithms for TSP are learned and practiced. The algorithm complexity is defined and computed for some of the above algorithms. The NP-completeness of HAM-CYCLE and TSP is explained at the level adapted to the level of the course participants.
Literature: E. Goodaire, M. Parmenter, Discrete Mathematics with Graph Theory, Prentice Hall, many editionsR. Wilson, Introduction to Graph Theory
Course type: lectures (30 hours), problem sessions (15 hours)Assessment method: two tests during the semester, final examPrerequisites: Linear AlgebraPrimary target group: Computer Science, Engineering Sciences, Mathematics and
Physics majors; preferably sophomore or junior; students of other levels are also welcome
Lecturer: Katarzyna Pałasińska, PhDContact person: Katarzyna Pałasińska, e-mail: [email protected] for application: 15th of September Remarks:
Course title: Introduction to DatabasesInstitute/Division: F-3, Institute of Computer ScienceCourse code: 0612-DBErasmus subject code: Information and Communication Technologies (ICTs)
Informatics, Computer ScienceNumber of contact hours: 45 hoursCourse duration: 1 semester ECTS credits: 6Course description: Using base management tools for the administrator and user, Making
up base and tables by means of graphical tools, Making up base and tables by means of SQL instruction from the console, Making up base and tables by means of SQL instruction from the console, Normalization of the base for the given input project. ERD diagrams, Making up SQL statements based on queries, Making up views by means of SQL creators and queries, Designing and making up referential integrity in tables and columns, Indices, Designing transactions and making use of them, Cooperation with external client applications and interface configuration, User management and access rights management, Topic up to the teacher dependent on course of the previous laboratory lessons
Literature: 1. Connolly, T. C. Begg: Database Systems: A Practical Approach to Design, Implementation and Management. Addison-Wesley Longman, 1998.
2. Date, C.J. and H. Darwen: A Guide to SQL Standard. Addison-Wesley, 1994.
Course type: Lectures and laboratoriesAssessment method: Attendance, evaluation of small projects, examPrerequisites: Database, SQL languagePrimary target group: computer science students of the 2-nd or 3-rd yearLecturer: Anna Plichta, DScContact person: Anna Plichta, DSc , [email protected] for application: 15th of SeptemberRemarks:
Course title: Number TheoryInstitute/Division: Institute of Mathematics, Faculty of Physics,
Mathematics and Computer ScienceCourse code: F2-NThErasmus subject code: 11.1 MathematicsNumber of contact hours: 45 hoursCourse duration: 1 semester ECTS credits: 6Course description:
This course is an elementary introduction to number theory for undergraduate students in Mathematics, Computer Science, Physics or Engineering with no previous knowledge of the subject.Topics covered include: common number sets, the principle of mathematical induction, minimum principle, primes, division algorithm, the Euclidean algorithm and continued fractions, greatest common divisors, the m-adic representations of integers, the binomial coefficient, the lexicographic order, examples of abelian groups, congruence’s, the ring of congruence classes, Fundamental theorem of arithmetic, the p-adic value, the radical, Sieve of Eratosthenes, Bertrand’s postulate, diophantine equations, the Euler Phi function, The Chinese remainder theorem, Wilson theorem, Euler’s theorem and Fermat’s Little theorem, pseudoprimes and Carmichael numbers, reduced residue system, primitive roots, the index with respect to primitive root, the discrete logarithm, power residues, quadratic reciprocity.
Literature:W. Narkiewicz, Number Theory, World Scientific, Singapore, 1983.W. Sierpiński, Elementary theory of numbers, Warszawa-Amsterdam-New York-Oxford, 1987.Z.I.Borevich, I.R.Shafarevich, Number Theory, Academic Press,1966.H.Davenport, The Higher Arithmetic, Cambridge University Press, 2008.G. H. Hardy and E. M. Wright, An Introduction to the Theory of Numbers, Oxford University Press,1979.
Course type: lectures (30 hours), problem sessions (15 hours)Assessment method: two tests during the semester, final examPrerequisites: at least one college level math coursePrimary target group: Majors in Computer Science, Mathematics, Physics or
EngineeringLecturer: Maciej Zakarczemny, PhDContact person: Maciej Zakarczemny, e-mail: [email protected] for application: 15th of SeptemberRemarks:
Course title: LTE/LTE-A BasicsInstitute/Division: F-5, Institute of Teleinformatics Course code: F50-02 Erasmus subject code: Telecomunication, Computer Science Number of contact hours: 45 hours Course duration: 1 semester ECTS credits: 6 Course description:
Introduction to LTE, History, What is LTE/LTE-Advanced, Network Architecture, Microwaves an radio propagation, Modulation basics, Orthogonal Frequency Multiple Access (OFDMA), Single Carrier Frequency Division Multiple Access (SC-FDMA), Introduction to air interface, RF Basics, LTE Measurements, Air interface layer 1 and 2 protocols, Control plane and user plane, Basic operations, Attach and handover (soft vs hard), Quality of Service (QoS) Literature: Course type: Lectures and seminars Assessment method: Attendance, ability of solving of simple exercises, exam Prerequisites: Basics of Computer Networks Primary target group: 3-rd – 4-th year computer science students Lecturer: Jerzy R. Jaworowski, PhD Contact person: Jerzy R. Jaworowski, PhD, [email protected] Deadline for application: 15th of September Remarks:
Course title: Mathematical FinanceInstitute/Division: Institute of Mathematics, Faculty of Physics, Mathematics and
Computer ScienceCourse code: F2-MFErasmus subject code: 11.0 MathematicsNumber of contact hours: 45 hoursCourse duration: 1 semesterECTS credits: 6Course description: The course provides an elementary introduction to concepts of
price and hedge derivative securities (European and American options). Topics include elements of stochastic analysis: filtrations, martingales, stochastic processes, Brownian motion, Ito formula, stopping times, Snell envelope, Girsanov theorem. The following concepts will be studied in both discrete and continuous time: the change-of-measure technique, hedging,pricing, absence of arbitrage opportunities and the Fundamental Theorem of Asset Pricing. Black – Scholes model will be discussed.
Literature: H. Bingham, R. Kiesel, Risk-Neutral Valuation, Springer-Verlag, London 1998. J. Karatzas, S. E. Shreve,Brownian Motion and Stochastic Calculus, Springer-Verlag, Berlin 1988.
Course type: Lectures, problem sessionsAssessment method: Two tests during the semester, final examPrerequisites: Stochastic processesPrimary target group: Majors in Mathematics, II or I levelLecturer: Margareta Wiciak, PhDContact person: Margareta Wiciak, e-mail: [email protected] for application: 15th of SeptemberRemarks:
Course title: Neural Networks Institute/Division: F-3, Institute of Computer Science Course code: F3-NNErasmus subject code: Informatics, Computer ScienceNumber of contact hours: 45 hoursCourse duration: 1 semester ECTS credits: 6Course description: General description of the neural networks. Relations between
classical algorithms and neural methods in problem solving. Artificial neural network and human brain. Structure and functionality of a single artificial neuron. Architectures of neural networks and dependence between complexity of the solved problem and structural complexity of the network. Methods of neural network learning and training. Back propagation and other methods of learning. Self learning of the networks and problem of self-organization. Networks with feedback. Deep learning networks. Possibilities and limitations of many types of neural networks.
Literature: 1. Basic literature on the subject2. Many additional materials and links will be given to all students during the lectures.
Course type: Lectures and exercisesAssessment method: There will be few homeworks. Each one should be returned to
the teacher up to 2 weeks after distribution). Prerequisites: NonePrimary target group: computer science students of the 3rd or 4th yearLecturer: Barbara Borowik, PhDContact person: Barbara Borowik, PhD; [email protected] for application: 15th of SeptemberRemarks:
Course title: Object Oriented Programming Institute/Division: F-3, Institute of Computer Science Course code: F3-OOP Erasmus subject code: Informatics, Computer Science Number of contact hours: 45 hours Course duration: 1 semester ECTS credits: 6 Course description: basics of object oriented techniques: classes, interfaces, abstract
classes, inheritance, encapsulation, implementation hiding; design patterns – definitions and example projects; C# realization of object oriented features; elements of test driven development (TDD) approach to software development
Literature: 1. "Programming C#. Building .NET Applications with C#", Jesse Liberty 2. "Microsoft Visual C# 2010 Step by Step", John Sharp 3. "Head First Design Patterns", Elisabeth Freeman, Eric Freeman, Bert Bates, Kathy Sierra, Elisabeth Robson 4. "Design Patterns in C#", Steven John Metsker 5. "The Object-Oriented Thought Process (3rd Edition)", Matt Weisfeld
Course type: Lectures and laboratories Assessment method: Attendance, evaluation of small projects, exam Prerequisites: basics of programming languages (procedural programming,
loops, conditional statements etc., other object oriented languages appreciated but not necessary)
Primary target group: 2-nd – 4-th year computer science students Lecturer: Michał Bereta, PhD, Eng. Contact person: Michał Bereta, PhD, Eng. [email protected] Deadline for application: 15th of September Remarks:
Course title: Operations and production process management for engineers
Institute/Division: Institute of Mathematics, Faculty of Physics, Mathematics and Computer Science
Course code: F5-OPMErasmus subject code: 11.2 StatisticsNumber of contact hours: 45 hoursCourse duration: 1 semesterECTS credits: 6Course description: This class is offered to graduate level engineers (MSc programs)
that need to learn more advanced statistical and math model while working on operations management and production management. The math profile will be low and lots of math or stat related problems will be solved using the relevant computer packages. Main topics include PERT-CPM model, scheduling algorithms, production process management and management of services. Special attention will be given to business process reengineering. The textbook will be of Aquilano, Jacobs "Operations and Production Management". Students will be asked to work on practice-related problems using the models learned in class. The curriculum of this class was checked for around 10 years of providing such class within the University of California format and within the National Louis University of Chicago program.
Literature: Aquilano, Jacobs, Operations and Production ManagementCourse type: lectures, classesAssessment method: project on practice-related problemsPrerequisites: elementary probability and statisticsPrimary target group: graduate level engineers (MSc programs)Lecturer: Jacek Leśkow, PhDContact person: Jacek Leśkow , e-mail: [email protected] for application: 15th of September Remarks:
Course title: Parallel and Distributed ProgrammingInstitute/Division: F-3, Institute of Computer ScienceCourse code: F34-PDPErasmus subject code: Informatics, Computer ScienceNumber of contact hours: 45 hoursCourse duration: 1 semester ECTS credits: 6Course description: History of parallel and distributed computing. Operating
system's foundations: processes, threads. POSIX Threads in C language. Concurrency and parallel programming models. Programming shared memory systems: data dependencies and OpenMP specification. Vectorization and basic assemby code. Programming of distributed memory systems: message passing paradigm, MPI specification, group communication. Accelerators programming - CUDA/OpenCL.
Literature: G. Coulouris et al., “Distributed Systems. Concepts and Design” (4th ed.), Addison Wesley, 2005A. S. Tanenbaum, “Distributed Systems. Principles and Paradigms” (2nd ed.), Prentice Hall 2002Grama A. et al., „Introduction to Parallel Computing” (2nd
ed.), Addison-Wesley, 2003Course type: Lectures and laboratoriesAssessment method: Attendance, evaluation of small projects, examPrerequisites: Advanced C or C++ programming language, Basic knowledge
of Linux operating system.Primary target group: 3-rd – 4-th year computer science studentsLecturer: Filip Krużel, MScContact person: Filip Krużel, MSc, [email protected] for application: 15th of SeptemberRemarks:
Course title: Software Engineering Institute/Division: F-3, Institute of Computer Science Course code: F33-SE Erasmus subject code: Informatics, Computer Science Number of contact hours: 45 hours Course duration: 1 semester ECTS credits: 6 Course description: All aspects of software production process thorough treatment of
the development lifecycle, modeling languages (UML), engineering tools, project planning and process management. The course emphasizes object-oriented modeling and programming, explains the use of components and business object and highlights application of architectural design and refactoring.
Literature: D.Hamlet, J.Maybee, The Engineering of Software– Technical Foundations for the Individual, Addison Wesley Longman Inc. 2001, L.Maciaszek, B.Lee Liong, Practical Software Engineering, A Case Study Approach, Pearson Education Limited 2005
Course type: Lectures and laboratories Assessment method: A few tests (each one will be announced two weeks in advance),
ability of solving of simple exercises, exam. Prerequisites: Programming languages, algorithms and data structures, data
bases. Primary target group: 3-rd – 4-th year computer science students Lecturer: Marek Stanuszek, PhD, DSc. Contact person: Marek Stanuszek, PhD, DSc. [email protected] Deadline for application: 15th of September Remarks:
Course title: Stochastic ModellingInstitute/Division: Institute of Mathematics, Faculty of Physics, Mathematics and
Computer ScienceCourse code: F5-SMErasmus subject code: 11.1 MathematicsNumber of contact hours: 45 hoursCourse duration: 1 semesterECTS credits: 6Course description: The objective of this course is to introduce graduate-level math
students to the intricacies of stochastic processes, point processes and time series. Main modelling issues will be: Brownian Motion, Poisson Process, Cox regression model, ARMA(p,q) model. This class requires familiarity with basic concepts of probability and statistics as taught for math students. The class will be focused on solving real problems, stemming from finance, signal processing, climatology and biology. Therefore, students will get acquainted not only with the theoretical models but also with software.
Literature:Course type: Lectures, classesAssessment method: Two tests during the semester, final examPrerequisites: basic concepts of probability and statistics as taught for math
studentsPrimary target group: Mathematics, II levelLecturer: Jacek Leśkow, PhDContact person: Jacek Leśkow , e-mail: [email protected] for application: 15th of September Remarks