Key Information
Tutor: Dr Christopher Cooling
Course Level: Level 2
Course Credit: 1 credit
Prerequisites: See below
Course Duration: 2 x 2 hour sessions
Format: Live online or live face to face with hands on practice
Prerequisites
Basic knowledge of Python is essential. Ideally an attendee will have used Python intensively for at least three months prior to attending this course. Python users who are already familiar with NumPy and/or SciPy will gain less from this course as it is primarily aimed at those learning about these features for the first time. Knowledge of the following areas of maths is required:
- Vectors
- Matrices
- Differentiation of simple functions
- Integration of simple functions
- Ordinary differential equation (useful, not required)
If you are unfamiliar with of some of these areas, or would like a refresher, consider taking the Maths and Stats Online Catch Up course before you attend this course. This course can be completed at your own pace.
Course Resources
Python has many great advantages that leads to it being the programming language of choice for a large range of audiences. However, it is an inherently inefficient language and performing extensive numerical calculations in pure Python can be very slow. Fortunately, the NumPy and SciPy modules are a popular and effective way to greatly improve the performance of Python for numerical computing.
This course aims to introduce the basic features of the NumPy and SciPy packages and give attendees the experience required to begin using these packages in their own work. This will be achieved through a series of demonstrations, followed by hands-on practicals, which challenge attendees to apply the tools demonstrated to sample problems of increasing complexity.
Syllabus
- What are NumPy and SciPy?
- Creating and manipulating NumPy arrays
- Operations using NumPy arrays
- Performance comparison of NumPy arrays with standard Python
- Using SciPy to perform numerical calculations
- Extended exercises
The course will be delivered through a combination of written material, demonstrations and hands-on practicals.
Learning Outcomes
On completion of this workshop you will be better able to:
- Describe the key functionality and advantages of NumPy and SciPy
- Utilise NumPy arrays to store and perform operations on data sets
- Locate appropriate SciPy functions for a specific problem
- Create basic programs using NumPy and SciPy to solve numerical problems
Dates & Booking Information
- Monday 03 February 2025 (Part 1) & Thursday 06 February 2025 (Part 2), 12:00-14:00, South Kensington (In-Person Teaching)
- Thursday 01 May 2025 (Part 1) & Friday 02 May 2025 (Part 2), 14:00-16:00, Microsoft Teams
To book your place, please follow the booking process advertised on the main programme page