# DEGREE REGULATIONS & PROGRAMMES OF STUDY 2020/2021

### Information in the Degree Programme Tables may still be subject to change in response to Covid-19

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DRPS : Course Catalogue : School of Informatics : Informatics

# Undergraduate Course: Informatics 2B - Algorithms, Data Structures, Learning (INFR08009)

 School School of Informatics College College of Science and Engineering Credit level (Normal year taken) SCQF Level 8 (Year 2 Undergraduate) Availability Available to all students SCQF Credits 20 ECTS Credits 10 Summary This course presents key symbolic and numerical data structures and algorithms for manipulating them. Introductory numerical and symbolic learning methods provide a context for the algorithms and data structures. To make the presented ideas concrete, the module will extend the student's skills in Java and Matlab. Examples will be taken from all areas of Informatics. * Please note that this course has been replaced by a 10 credit course Informatics 2B - Learning (INFR08028) for 2019/20.* Course description Algorithms and Data Structures: * Asymptotic notation and algorithms * Sequential data structures * Searching - including Hashing, AVL Trees, Heaps * Sorting - including Mergesort, Heapsort, Quicksort * Web-scale algorithms * Graphs Learning: * Statistical pattern recognition and machine learning * Multidimensional data * Discrete data and naive Bayes * Modelling and describing continuous data: nearest neighbours and clustering * Gaussians and linear discriminants * Single- and multi-layer networks Relevant QAA Computing Curriculum Sections: Data Structures and Algorithms, Artificial Intelligence
 Pre-requisites Students MUST have passed: ( Informatics 1 - Computation and Logic (INFR08012) AND Informatics 1 - Functional Programming (INFR08013)) OR Informatics 1 - Introduction to Computation (INFR08025) Students MUST have passed: Informatics 1 - Object-Oriented Programming (INFR08014) AND Introduction to Linear Algebra (MATH08057) Co-requisites Prohibited Combinations Other requirements A background in calculus(differentiation of simple functions) is also required. INF1-Introduction to Computation (INFR08025) replaces INF1-Computation and Logic (INFR08012) and INF1-Functional Programming (INFR08013) from 2018/19.
 Pre-requisites None High Demand Course? Yes
 Not being delivered
 On completion of this course, the student will be able to: Demonstrate the ability to analyse the complexity of algorithms using asymptotic notation, to write programs to create and manipulate array-structured and dynamically-structured data, and to construct and analyse search tree data structuresDemonstrate knowledge of sorting and graph algorithms and their run-time complexityDemonstrate understanding of statistical pattern recognition and Bayes theorem, and the ability to manipulate and describe multidimensional data using summary statisticsDemonstrate the ability to model discrete multidimensional data using Naive Bayes, and the ability to classify multidimensional data using Gaussians and single-layer networksDemonstrate understanding of the concept of discriminant functions, and the ability to model data using nearest-neighbour and clustering approaches
 * [***] S. Russell, P. Norvig. AI: A Modern Approach. Prentice Hall, 2003. 2nd Edition * [**] T. H. Cormen, C. E. Leiserson, R. L. Rivest. Introduction to Algorithms, MIT Press, 1990. * [**] A. V. Aho, J. D. Ullman. Foundations of Computer Science with C. Computer Science Press, 1995. * [**] M. T. Goodrich and R. Tamassia. Data Structures and Algorithms in Java. John Wiley, 2003. (3rd edition) * [**] I. H. Witten and E. Frank. Data Mining. Morgan Kaufmann. 2005. (2nd edition) Programme Collective Intelligence, Toby Segaran, O'Reilly 2007
 Course URL http://course.inf.ed.ac.uk/inf2b Graduate Attributes and Skills Not entered Keywords Not entered
 Course organiser Dr Kyriakos Kalorkoti Tel: (0131 6)50 5149 Email: kk@inf.ed.ac.uk Course secretary Ms Kendal Reid Tel: (0131 6)51 3249 Email: kr@inf.ed.ac.uk
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