Undergraduate Course: Informatics 2B - Learning (INFR08028)
Course Outline
| 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 | 10 |
ECTS Credits | 5 |
| Summary | This course provides an introduction to some of the basic mathematical and computational methods for learning from data. We discuss the problems of clustering and classification, and how probabilistic and non-probabilistic methods can be applied to these.
*Please note that this course has been replaced by a 20-credit course "Informatics 2 - Foundations of Data Science" (INFR08030) from 2020/21.* |
| Course description |
Course syllabus:
* 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
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Information for Visiting Students
| Pre-requisites | Background required: at least one semester of programming; linear algebra; calculus (differentiation). |
| High Demand Course? |
Yes |
Course Delivery Information
| Not being delivered |
Learning Outcomes
On completion of this course, the student will be able to:
- Manipulate and describe multidimensional data using summary statistics.
- Define and use methods such as Naïve Bayes, Gaussians, and single-layer networks to model and classify multidimensional data.
- Describe and apply nearest-neighbour and clustering approaches and the concept of discrimi-nant functions.
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Reading List
| Course notes will be provided. |
Additional Information
| Graduate Attributes and Skills |
Problem-solving, analytical thinking, numeracy. |
| Special Arrangements |
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. |
| Keywords | Machine learning,data science |
Contacts
| Course organiser | Dr Hiroshi Shimodaira
Tel: (0131 6)51 3279
Email: h.shimodaira@ed.ac.uk |
Course secretary | Ms Kendal Reid
Tel: (0131 6)51 3249
Email: kr@inf.ed.ac.uk |
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