CS917 Foundations of Computing Skip to main content Skip to navigation Sign in Study Research Business Alumni News Engagement Search Warwick Search Department of Computer Science Admissions Undergraduate Postgraduate Taught Degree Apprenticeships Teaching Coronavirus(Restricted permissions) DCS Self Isolation Notification Student Support Appointment Booking Form Course Structures Student Handbook(Restricted permissions) Modules Taught Research Doctoral Studies Interdisciplinary Research Centres Impact and Innovation Applied Computing Artificial Intelligence and Human-Centred Computing Data Science, Systems and Security Theory and Foundations People News Events Computer Science Colloquium Outreach News Upcoming Events Past Events Projects Report(Restricted permissions) Welfare Athena SWAN Equality, Diversity and Inclusion News Vacancies Intranet(Restricted permissions) Teaching Modules Taught CS917 CS917 Foundations of Computing We will be adapting the way we teach and assess modules in line with government guidance on social distancing and other protective measures in response to Coronavirus. Teaching will vary between online and on-campus delivery through the year, and you should read the additional information linked on the right hand side of this page for details of how we anticipate this will work. The contact hours shown in the module information below are superseded by the additional information. You can find out more about the University’s overall response to Coronavirus at: https://warwick.ac.uk/coronavirus. CS917-15 Foundations of Computing Academic year 21/22 Department Computer Science Level Taught Postgraduate Level Module leader Feng Hao Credit value 15 Module duration 10 weeks Assessment 100% coursework Study location University of Warwick main campus, Coventry Download as PDF Description Study Assessment Availability Introductory description The aim of the module is to equip students with a grounding in foundations of computing, to enable students from a wider background to confidently undertake a taught masters programme in advanced computing topics. Module aims The aim of the module is to equip students with a grounding in foundations of computing, to enable students from a wider background to confidently undertake a taught masters programme in advanced computing topics. Outline syllabus This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ. -Computational Mathematics and Statistical Methods (logic, sets, probability and hypothesis testing) -Programming and Data Structures (procedural and object oriented programming, using appropriate data structures) -Algorithms and Complexity (analysis of algorithms, searching and sorting algorithms and calculation best, worst and average case complexities) Learning outcomes By the end of the module, students should be able to: Understand the foundational concepts of computing mathematics and statistical methods. Write computer programs with an understanding of type systems and control flow in both procedural and object oriented programming paradigms and have strategies for debugging. Use data structures such as arrays, lists stack, queues, hash tables and trees effectively. Understand the relationships between algorithms and complexity. Indicative reading list Huth and Ryan, Logic in Computer Science Daniel Liang Y, Introduction to Java Programming - Comprehensive (7th ed), Pearson, 2008. Goodrich MT, Tamassia R and Goldwasser MH, Data Structures and Algorithms in Java (6/e), Wiley, 2015. Kleinberg J and Tardos E, Algorithm Design, Addison Wesley, 2005. Subject specific skills Computing Mathematics and Statistical Methods Computing Mathematics: Logical analysis; Propositional Logic; Sets and Relations; Predicate Logic Statistical Methods: Probability; Distributions; Significance Tests; Confidence Intervals; Hypothesis Testing Programming and Data Structures Programming: Procedural and Object Oriented Programming; Type Systems; Control Flow; Debugging Data Structures: Arrays, Lists, Stacks and Queues; Hash Tables; Trees Algorithms and Complexity Algorithms: Basics of Algorithm Analysis; Sorting and Searching; Graph Algorithms Complexity: Best, Worst and Average Case Complexity; Applications of the Master Theorem; Problem Instances Computing Architectures Processors and Memory Hierarchies; Client Server; Models of Distributed Systems; Application Domains -Computing Grand Challenges -Big Data; Internet of Things; Privacy; Quantum Computing; New Approaches in Al; Smart Cities Transferable skills Ability to program in Python, to design and analyse efficient computing algorithms, to apply logical analysis as well as probability and statistical tools to computationally address mathematics and statistics problems. Study time Type Required Lectures 30 sessions of 1 hour (20%) Seminars 20 sessions of 1 hour (13%) Private study 100 hours (67%) Total 150 hours Private study description Private study, background reading and revision. Costs No further costs have been identified for this module. You do not need to pass all assessment components to pass the module. Students can register for this module without taking any assessment. Assessment group A2 Weighting Study time Programming assignment 34% Programming assignment. This assignment is worth more than 3 CATS and is not, therefore, eligible for self-certification. Algorithms assignment 33% Algorithms assignment. This assignment is worth more than 3 CATS and is not, therefore, eligible for self-certification. Maths and Statistics assignment. 33% Maths and Statistics assignment. This assignment is worth more than 3 CATS and is not, therefore, eligible for self-certification. Feedback on assessment Individual feedback on each assignment. Courses This module is Core for: Year 1 of TPSS-C803 Postgraduate Taught Behavioural and and Data Science TCSA-G5PD Postgraduate Taught Computer Science Year 1 of G5PD Computer Science Year 1 of G5PD Computer Science Year 1 of TCSA-G5P8 Postgraduate Taught Computer Science and Applications Year 1 of TCSA-G5PA Postgraduate Taught Data Analytics Further Information Term 1 15 CATS (7.5 ECTS) Online Material Additional Information Module Organisers: Feng Hao Long Tran-Thanh Department of Computer Science, University of Warwick, CV4 7AL E-mail: comp-sci at dcs dot warwick dot ac dot uk, Telephone: +44 (0)24 7652 3193 DCS Intranet FacebookTwitterLinkedIn Page contact: Jennifer Mills Last revised: Sat 25 Sep 2021 Powered by Sitebuilder © MMXXI Terms Privacy Cookies Accessibility Coronavirus (Covid-19): Latest updates and information Let us know you agree to cookies We use cookies to give you the best online experience. Please let us know if you agree to functional, advertising and performance cookies. You can update your cookie preferences at any time. Cookie policy Essential cookies Functional cookies Advertising cookies Performance cookies Accept all Remember my preference More information
