Postgraduate short courses (2018/2019 academic year)

Birkbeck, University of London offers a range of postgraduate short courses, taught part-time on our central London campus. Many of these courses are taken directly from existing master's programmes and give students the opportunity to study at a postgraduate level without committing to a full programme of study. 

Advances in Data Management (6pm-9pm, every Monday from 14 january 2019 to 25 marcH 2019)

  • Lecturer: Alex Poulovassilis
  • Assessment: a two-hour written examination and practical coursework.
  • Description: This course examines the technologies underlying modern data management systems. It studies advanced aspects of query processing, transaction management, distributed data management, and recent developments in web data, 'big data' and alternative database architectures.
  • Indicative syllabus:
    • Review of the fundamental principles of database management systems, relational databases and SQL
    • Query processing and query optimisation
    • Transaction management: ACID properties, concurrency control, recovery
    • Beyond records and objects: stored procedures and functions, triggers, semantic technologies
    • Distributed databases: data fragmentation and replication, distributed query processing, distributed transaction management
    • Heterogeneous data integration
    • XML data management
    • Linked Open Data
    • Parallel databases
    • Big data and NoSQL/NewSQL stores
  • Class dates/times:
    • Monday 14 January 2019, 6pm-9pm
    • Monday 21 January 2019, 6pm-9pm
    • Monday 28 January 2019, 6pm-9pm
    • Monday 4 February 2019, 6pm-9pm
    • Monday 11 February 2019, 6pm-9pm
    • Monday 18 February 2019, 6pm-9pm
    • Monday 25 February 2019, 6pm-9pm
    • Monday 4 March 2019, 6pm-9pm
    • Monday 11 March 2019, 6pm-9pm
    • Monday 18 March 2019, 6pm-9pm
    • Monday 25 March 2019, 6pm-9pm
  • Fees:
    • Home students: £4375
    • International students: £7425
  • Apply now

cloud computing (6pm-9pm, every friday from 18 january 2019 to 29 marcH 2019)

  • Lecturer: Dell Zhang
  • Assessment: coursework (20%) and an examination (80%).
  • Description: On this course, you will learn about the emerging area of cloud computing and how it relates to traditional models of computing, and gain competence in MapReduce as a programming model for distributed processing of big data.
  • Indicative syllabus:
    • Introduction to Cloud Computing
    • Cloud Computing Technologies and Types
    • Big Data
    • MapReduce and Hadoop
    • Running Hadoop in the Cloud (Practical Lab Class)
    • Developing MapReduce Programs
    • Data Management in the Cloud
    • Information Retrieval in the Cloud
    • Link Analysis in the Cloud
    • Beyond MapReduce
    • Selected Case Studies
    • Advanced Topics in Cloud Computing
  • Class dates/times:
    • Friday 18 January 2019, 6pm-9pm
    • Friday 25 January 2019, 6pm-9pm
    • Friday 1 February 2019, 6pm-9pm
    • Friday 8 February 2019, 6pm-9pm
    • Friday 15 February 2019, 6pm-9pm
    • Friday 22 February 2019, 6pm-9pm
    • Friday 1 March 2019, 6pm-9pm
    • Friday 8 March 2019, 6pm-9pm
    • Friday 15 March 2019, 6pm-9pm
    • Friday 22 March 2019, 6pm-9pm
    • Friday 29 March 2019, 6pm-9pm
  • Fees:
    • Home students: £4375
    • International students: £7425
  • Apply now

Data Science Techniques and Applications (6pm-9pm, every wednesday from 16 january 2019 to 27 march 2019)

  • Coordinator: Alessandro Provetti
  • Assessment: a two-hour examination (80%) and two coursework assignments (20%).
  • Description: This course will provide you with more advanced study of data analytics, building on the Python programming expertise acquired in Principles of Programming I, relational databases and SQL introduced in Programming with Data, and basic probability and statistics covered in Big Data Analytics with R. Various topics will be demonstrated by practical lab sessions. Guest lecturers from industry may present parts of certain topics.
  • Indicative syllabus:
    • Introduction
    • Definitions of data science
    • Linear algebra and probability theory concepts
    • Experiences with data science discovery in Python
    • Web data extraction
    • From data to graphs, and their relevant properties
    • Centrality measures
    • Communities
    • Rating and ranking
    • Correlation (if time allows)
  • Class dates/times:
    • Wednesday 16 January 2019, 6pm-9pm
    • Wednesday 23 January 2019, 6pm-9pm
    • Wednesday 30 January 2019, 6pm-9pm
    • Wednesday 6 February 2019, 6pm-9pm
    • Wednesday 13 February 2019, 6pm-9pm
    • Wednesday 20 February 2019, 6pm-9pm
    • Wednesday 27 February 2019, 6pm-9pm
    • Wednesday 6 March 2019, 6pm-9pm
    • Wednesday 13 March 2019, 6pm-9pm
    • Wednesday 20 March 2019, 6pm-9pm
    • Wednesday 27 March 2019, 6pm-9pm
  • Fees:
    • Home students: £4375
    • International students: £7425
  • Apply now

Data Warehousing and Data Mining (6pm-9pm, every wednesday from 16 january 2019 to 27 march 2019)

  • Lecturer: Nigel Martin
  • Assessment: a two-hour written examination (90%) and practical coursework exercise (10%)
  • Description: This course covers the organisation, analysis and mining of large data sets to support business intelligence applications. You will study the principles and commercial application of the technologies, as well as research results and emerging architectures underpinning the analysis and mining of 'big data'.
  • Indicative syllabus:
    • Data warehousing requirements
    • Database technology underpinning data warehousing and data mining
    • Data warehouse architectures. Data marts
    • Data warehouse logical design: star schemas, fact tables, dimensions, snowflake schemas, dimension hierarchies
    • OLAP architectures, OLAP operations. SQL extensions for OLAP
    • Data warehouse physical design: partitioning, parallelism, compression, indexes, materialised views, column stores
    • Data warehouse construction: data extraction, transformation, loading and refreshing. Data warehouse support in Oracle. Warehouse metadata
    • Specialised warehouse architectures. MapReduce and warehouse architectures: Hive
    • Data mining concepts, tasks and algorithms
    • Data mining technologies and implementations. Techniques for mining large databases
    • Data mining support in commercial systems. Data mining standards
    • Research trends in data warehousing and data mining
  • Class dates/times:
    • Wednesday 16 January 2019, 6pm-9pm
    • Wednesday 23 January 2019, 6pm-9pm
    • Wednesday 30 January 2019, 6pm-9pm
    • Wednesday 6 February 2019, 6pm-9pm
    • Wednesday 13 February 2019, 6pm-9pm
    • Wednesday 20 February 2019, 6pm-9pm
    • Wednesday 27 February 2019, 6pm-9pm
    • Wednesday 6 March 2019, 6pm-9pm
    • Wednesday 13 March 2019, 6pm-9pm
    • Wednesday 20 March 2019, 6pm-9pm
    • Wednesday 27 March 2019, 6pm-9pm
  • Fees:
    • Home students: £4375
    • International students: £7425
  • Apply now

Football Analytics (6pm-9pm, every Tuesday from 30 April 2019 to 9 July 2019) 

  • Coordinator and lecturerGiambattista Rossi
  • Assessment: a 20-25-minute group presentation (40%) and a two-hour examination (60%)
  • Description: The performance data industry in football has grown dramatically in recent years, to the point where all professional teams have access to some level of data and employ performance analysts to help coaches, scouts, players and executives work with the new technologies available, particularly video. However, as detailed data and analytics become integrated within club processes, it is essential that staff are equipped with the skills to not only interpret and apply this information correctly, but also to present and argue insights to decision makers. Teams also amass large databases of their own subjective information on players, but do not manage that data appropriately and clubs still have limited knowledge of how to use data to strategically plan for the future and in budgeting. It is the analysts who have the chance to improve this dramatically. At the other end of the market, some teams have become extremely advanced and actually employ data scientists to build advanced models. Whilst this progress is excellent, a new problem exists where many within the team do not know how to interpret the advanced outputs they are being shown. This short course aims to develop managers who can make decisions, based on provided models, regarding both player and team valuations.
  • Indicative syllabus
    • Statistical landscape in sport: how data is used in elite sport
    • Statistical models and their application in football
    • Collecting, databasing and analysing subjective data: integration of different datasets
    • Using data in an applied setting
    • Analytical software 
    • Data visualisation: best practice
    • Presenting advanced analysis: managing conversations; negotiating with decision-makers
    • Long-term, strategic planning using data: beyond ‘day-to-day’ work
    • Cases studies and revision 
  • Class dates/times
    • Tuesday 30 April 2019, 6pm-9pm
    • Tuesday 7 May 2019, 6pm-9pm
    • Tuesday 14 May 2019, 6pm-9pm
    • Tuesday 21 May 2019, 6pm-9pm
    • Tuesday 28 May 2019, 6pm-9pm
    • Tuesday 4 June 2019, 6pm-9pm
    • Tuesday 11 June 2019, 6pm-9pm
    • Tuesday 18 June 2019, 6pm-9pm
    • Tuesday 25 June 2019, 6pm-9pm 
    • Tuesday 2 July - no class (revision week) 
    • week commencing 8 July 2019 - exam (exact date TBC). 
  • Fees: 
    • Home students: £900 
    • International students: £1400 
  • Apply now

Information Retrieval and Organisation (6pm-9pm, every tuesday from 15 january 2019 to 26 march 2019) 

  • Lecturers: Dell Zhang and Mark Levene
  • Assessment: coursework (20%) and an examination (80%).
  • Description: Due to the explosive growth of digital information in recent years, modern information retrieval (IR) systems such as search engines have become more and more important in almost everyone's work and life (eg see the phenomenal rise of Google). IR research and development are one of the hottest research areas in academia as well as industry. This course will convey the basic principles of modern IR systems and introduce modern IR concepts and techniques, from basic text indexing to advanced text mining and Web IR. Both theoretical and practical aspects of IR systems will be presented and the most recent issues in the field of IR will be discussed. This will give you an insight into how modern search engines work and are developed.
  • Indicative syllabus
    • Boolean retrieval
    • The term vocabulary and postings lists
    • Dictionaries and tolerant retrieval
    • Index construction and compression
    • Scoring, term weighting and the vector space model
    • Computing scores in a complete search system
    • Evaluation in information retrieval, relevance feedback and query expansion
    • Probabilistic information retrieval
    • Language models for information retrieval
    • Text classification, naive bayes and vector space classification
    • Flat and hierarchical clustering
    • Advanced topics in IR
  • Class dates/times
    • Tuesday 15 January 2019, 6pm-9pm
    • Tuesday 22 January 2019, 6pm-9pm
    • Tuesday 29 January 2019, 6pm-9pm
    • Tuesday 5 February 2019, 6pm-9pm
    • Tuesday 12 February 2019, 6pm-9pm
    • Tuesday 19 February 2019, 6pm-9pm
    • Tuesday 26 February 2019, 6pm-9pm
    • Tuesday 5 March 2019, 6pm-9pm
    • Tuesday 12 March 2019, 6pm-9pm
    • Tuesday 19 March 2019, 6pm-9pm
    • Tuesday 26 March 2019, 6pm-9pm
  • Fees: 
    • Home students: £4375
    • International students: £7425
  • Apply now

Internet and Web Technologies (6pm-9pm, every tuesday from 15 january 2019 to 26 march 2019) 

  • LecturerPeter Wood
  • Assessment: a two-hour written examination (80%) and coursework exercises (20%).
  • Description: This course provides you with an understanding of how network protocols work, particularly those used on the Internet, and the ability to present and manipulate information on the World Wide Web, with an emphasis on XML.
  • Indicative syllabus
    • Introduction to the Internet and its applications
    • Web languages (eg HTML, XHTML, XML)
    • Languages for defining Web document types (eg DTDs)
    • Web query and transformation languages (eg XPath, XSLT)
    • Client-side processing (eg using Javascript, DOM)
    • Server-side processing (eg using CGI, Perl and PHP)
    • The transport layer (eg TCP, UDP)
    • The network layer (eg IP, DHCP, ICMP)
    • The link layer (eg Ethernet, ARP)
  • Class dates/times
    • Tuesday 15 January 2019, 6pm-9pm
    • Tuesday 22 January 2019, 6pm-9pm
    • Tuesday 29 January 2019, 6pm-9pm
    • Tuesday 5 February 2019, 6pm-9pm
    • Tuesday 12 February 2019, 6pm-9pm
    • Tuesday 19 February 2019, 6pm-9pm
    • Tuesday 26 February 2019, 6pm-9pm
    • Tuesday 5 March 2019, 6pm-9pm
    • Tuesday 12 March 2019, 6pm-9pm
    • Tuesday 19 March 2019, 6pm-9pm
    • Tuesday 26 March 2019, 6pm-9pm
  • Fees: 
    • Home students: £4375
    • International students: £7425
  • Apply now

machine learning (6pm-9pm, every thursday from 17 january 2019 to 28 march 2019) 

  • Lecturer: George Magoulas
  • Assessment: a two-hour written examination (100%).
  • Description: The course covers computational algorithms for intelligent information management, decision making and complex problem solving. It provides an introduction to technologies such as knowledge-based systems, artificial neural networks, fuzzy logic, evolutionary computation, hybrid systems showing how such technologies work to support the development of modern intelligent applications.
  • Indicative syllabus
    • Knowledge-based systems
    • Rule-based expert systems
    • Fuzzy systems
    • Uncertainly management
    • Neural computing
    • Genetic and evolutionary computing
    • Hybrid approaches
  • Class dates/times
    • Thursday 17 January 2019, 6pm-9pm
    • Thursday 24 January 2019, 6pm-9pm
    • Thursday 31 January 2019, 6pm-9pm
    • Thursday 7 February 2019, 6pm-9pm
    • Thursday 14 February 2019, 6pm-9pm
    • Thursday 21 February 2019, 6pm-9pm
    • Thursday 28 February 2019, 6pm-9pm
    • Thursday 7 March 2019, 6pm-9pm
    • Thursday 14 March 2019, 6pm-9pm
    • Thursday 21 March 2019, 6pm-9pm
    • Thursday 28 March 2019, 6pm-9pm
  • Fees: 
    • Home students: £4375
    • International students: £7425
  • Apply now

Software Design and Programming (1.30pm-5pm, every tuesday from 15 january 2019 to 26 march 2019 or 6pm-9pm, every thursday from 17 january 2019 to 28 march 2019) 

  • LecturersKeith Mannock and Oded Lachish
  • Assessment: a two-hour unseen written examination (80%) and coursework exercises (20%).
  • Description: The main aim of the course is to provide you with the necessary skills for developing software utlising the object-oriented and functional programming paradigms, with Java 8. This ranges from learning object-oriented concepts, designing object-oriented software using a proven methodology and tools, to learning how to program in an object-oriented and functional style. The course provides a detailed examination of software design patterns, and the emerging functional features of current-day object-oriented programming languages.
  • Indicative syllabus
    • The object model and how it is realised in various object-oriented languages (eg Java, Scala, Ruby, C++, ...)
    • Further development the ideas of inheritance and polymorphism (including a revision of parametric polymorphism)
    • Language features: inner classes, closures, higher-order functions, meta-objects, etc
    • An introduction to test driven design (TDD) and behavioural driven design (BDD)
    • The use of an integrated development environment (IDE) for software development: eg editing, debugging, compilation, etc
    • Modularity, versioning, packaging, and managing the build process
    • Design patterns and anti-patterns and their application to software design
    • The SOLID (single responsibility, open-closed, Liskov substitution, interface segregation and dependency inversion) approach to object oriented programming and design
    • Code refactoring and analysis
    • Graphical user interfaces and frameworks
    • Persistence frameworks
    • Concurrency and agents/actors
  • Class dates/times
    • Tuesday 15 January 2019, 1.30pm-5pm
    • Thursday 17 January 2019, 6pm-9pm
    • Tuesday 22 January 2019, 1.30pm-5pm
    • Thursday 24 January 2019, 6pm-9pm
    • Tuesday 29 January 2019, 1.30pm-5pm
    • Thursday 31 January 2019, 6pm-9pm
    • Tuesday 5 February 2019, 1.30pm-5pm
    • Thursday 7 February 2019, 6pm-9pm
    • Tuesday 12 February 2019, 1.30pm-5pm
    • Thursday 14 February 2019, 6pm-9pm
    • Tuesday 19 February 2019, 1.30pm-5pm
    • Thursday 21 February 2019, 6pm-9pm
    • Tuesday 26 February 2019, 1.30pm-5pm
    • Thursday 28 February 2019, 6pm-9pm
    • Tuesday 5 March 2019, 1.30pm-5pm
    • Thursday 7 March 2019, 6pm-9pm
    • Tuesday 12 March 2019, 1.30pm-5pm
    • Thursday 14 March 2019, 6pm-9pm
    • Tuesday 19 March 2019, 1.30pm-5pm
    • Thursday 21 March 2019, 6pm-9pm
    • Tuesday 26 March 2019, 1.30pm-5pm
    • Thursday 28 March 2019, 6pm-9pm
  • Fees: 
    • Home students: £4375
    • International students: £7425
  • Apply now