Undergraduate Course: Informatics 1 - Data and Analysis (INFR08015)
Course Outline
| School | School of Informatics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 8 (Year 1 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | An introduction to collecting, representing and interpreting data across the range of informatics. Students will learn the different perspectives from which data is used, the different terminology used when referring to them and a number of representation and manipulation methods. The course will present a small number of running, illustrative examples from the perspectives of hypothesis testing and query formation and answering. |
| Course description |
Structured data and relational databases. Semistructured data and XML. Text corpora. Unstructured data and its analysis.
Relevant QAA Computing Curriculum Sections: to be confirmed
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Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2015/16, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 19,
Seminar/Tutorial Hours 8,
Feedback/Feedforward Hours 1,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
68 )
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| Assessment (Further Info) |
Written Exam
100 %,
Coursework
0 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Formative assessment will be used to provide feedback and guidance to students and will take the form of quizzes, exercise sheets, practical exercises and coursework assignments, covering areas from across the syllabus.
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| Feedback |
Not entered |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S2 (April/May) | | 2:00 | | | Resit Exam Diet (August) | | 2:00 | |
Learning Outcomes
1 - Demonstrate knowledge of the terminology and paradigms used in different areas of informatics for collecting, representing and interpreting data, by being able to apply them to sample problems.
2 - Demonstrate understanding of different types of data (for example, structured/semistructured/unstructured, quantitative/qualitative).
3 - Demonstrate proficiency of the entity/relationship model by being able to specify appropriate representations and queries for simple examples.
4 - Show awareness of the importance of logic for the representation of data by being able to design simple logical representation of a given data set.
5 - Present data in a variety of forms (textual, graphical, quantitative), across a range of data types.
6 - Show awareness of the distinction between object data and meta-data, by being able to apply it to a number of applications across informatics (e.g., databases, corpora).
7 - Demonstrate knowledge of the basic algorithms for interpreting and processing data, by being able to demonstrate how these algorithms work for simple data sets.
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Reading List
* Database Management Systems Raghu Ramakrishnan, Johannes Gehrke McGraw-Hill, Third edition, 2002
* Corpus Linguistics: An Introduction Tony McEnery, Andrew Wilson Edinburgh University Press, Second edition, 2001
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Contacts
| Course organiser | Dr Ian Stark
Tel: (0131 6)50 5143
Email: |
Course secretary | Mr Gregor Hall
Tel: (0131 6)50 5194
Email: |
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