THE UNIVERSITY of EDINBURGH

DEGREE REGULATIONS & PROGRAMMES OF STUDY 2020/2021

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

University Homepage
DRPS Homepage
DRPS Search
DRPS Contact
DRPS : Course Catalogue : School of Biological Sciences : Postgraduate

Postgraduate Course: Introduction to Python Programming (PGBI11119)

Course Outline
SchoolSchool of Biological Sciences CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate)
Course typeOnline Distance Learning AvailabilityNot available to visiting students
SCQF Credits10 ECTS Credits5
SummaryThe course will consist of introductory programming learning material presented in the Python language. All material and teaching will be available online through Learn and Collaborate,
Course description This course is aimed at Data Science Technology and Innovation students with no prior experience of programming. Therefore, the course will consist of introductory programming learning material presented in the Python language. All material and teaching will be available online through Learn and Collaborate, and will consist of:
- Exercises to demonstrate the main principles of computer programming through hands-on activities related to data science
- Video lectures to explain and expand on more difficult points
- Collaborate flipped classrooms to provide face-to-face contact time with lecturers
- Group online discussion forum to allow communication between students, and students and lecturer
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Not being delivered
Learning Outcomes
On completion of this course, the student will be able to:
  1. Describe the growing importance of programming, and its relevance to data science, and science in general.
  2. Give examples of coding that made the impossible possible.
  3. Use coding basics: simple variables, string operators, arithmetic operators.
  4. Utilise program navigation in code: flow control, Boolean logic, input/output.
  5. Solve example data science problems via writing functional code: functions, complex variables (arrays), large datasets.
Reading List
None
Additional Information
Graduate Attributes and Skills Enquiry - students will be confident in their ability to successfully search for and identify programming knowledge resources.
Personal and intellectual autonomy - Students will become accustomed to solving programming problems autonomously.
Communication - Students will be familiar with online communication, collaboration and knowledge transfer.
Personal effectiveness - Flexibility; many students have limited exposure to maths/computation in which there is more than one 'right' answer, but in programming, there is always more than one way to do it.
Application of numeracy and information technology - Students will advance beyond traditional IT Skills learning (which usually consists of learning how to use software packages such as Word) and will understand what makes such programs work 'under the bonnet'.
KeywordsNot entered
Contacts
Course organiserDr Douglas Houston
Tel: (0131 6)50 7358
Email: DouglasR.Houston@ed.ac.uk
Course secretaryMrs Claire Black
Tel: (0131 6)50 8637
Email: Claire.Black@ed.ac.uk
Navigation
Help & Information
Home
Introduction
Glossary
Search DPTs and Courses
Regulations
Regulations
Degree Programmes
Introduction
Browse DPTs
Courses
Introduction
Humanities and Social Science
Science and Engineering
Medicine and Veterinary Medicine
Other Information
Combined Course Timetable
Prospectuses
Important Information