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We offer courses that are freely available for all researchers at UCL, from postgraduate research students to senior research staff related to research including high-performance computing, research.
Becoming a digital researcher
- Software Carpentry
What computing skills do you need to produce reproducible research?
- Instructor-lead
- 2 days
- 5 times per year
- Delivery: Online & in-person
- Provider: ARC
- Introduction to the Unix Shell
How can we automate tedious repetitive tasks?
- Self-paced learning
- Duration: 1 day
- Details and access: Moodle(UCL only), non-UCL: GitHub-Pages
- Open Science and the future of research applications
- Pre-recorded webinar
- Duration: 35 mins
- Access: MediaCentral(UCL only)
- DSD: In a Nutshell: Git version control
- Instructor lead
- Duration: 1 hr
- Delivery: Online
- Provider: Digital Skills Development
- Details and access: see the UCL Learning Portfolio
Improving research software
- Introduction to programming with Python for Research
- Instructor lead
- Duration: 2 days
- Frequency: 3 times per year
- Delivery: In-person
- Provider: ARC
- Details and access: Doctoral Skills Training Programme - Tools for research analysis
- Introduction to research software development with Python
- Instructor lead
- Duration: 2 days
- Frequency: 3 times per year
- Delivery: In-person
- Provider: ARC
- Details and access: Doctoral School Training Programme - Tools for research analysis
- DSD: An Introduction to R with Rstudio
- Instructor lead
- Duration: 6hrs (2 x 3hr sessions)
- Delivery: In-person
- Provider: Digital Skills Development
- Details and access: see the UCL Learning Portfolio
- Tips and techniques for developing research software, or how not to be slated by the media
- Pre-recorded webinar
- Duration: 40 mins
- Access: MediaCentral(UCL only)
Managing your research data
- Storing and sharing your research data
- Pre-recorded webinar
- Duration: 42 mins
- Access: MediaCentral(UCL only)
- Information Governance, sensitive data, and the Data Safe Haven
- Pre-recorded webinar
- Duration: 42 mins
- Access: MediaCentral(UCL only)
High-performance computing
- From laptop to supercomputer: HPC Carpentry for UCL clusters
What to do when your computer is not powerful enough?
- Instructor lead
- Duration: 2 days (12 hrs), 4 sessions
- Frequency: 3 times per year
- Delivery: Online or in-person
- Provider: ARC
- Access: View ARC events calendar for upcoming dates
- Efficient and secure use of the UCL compute clusters
- Pre-recorded webinar
- Duration: 44 mins
- Access: MediaCentral(UCL only)
- Python in High-Performance Computing
Learn how to analyse Python programmes and identify performance barriers to help you work more efficiently.
- Self-paced learning
- Provider: Futurelearn
- Details and access:Python in High Performance Computing
- Managing big data with R and Hadoop
An introduction to the MapReduce paradigm for distributed data processing on a cluster. Some experience with R, statistics and matrix operations is recommended.
- Self-paced learning
- Provider: FutureLearn
- Details and access: Managing Big Data with R and Hadoop
- Supercomputing
An introduction to the theory and practice of parallel computing. Provides a good explanation of different computing architectures and the pros and cons of each.
- Provider: Self-paced learning
- Provider: FutureLearn
- Details and access: Managing Big Data with R and Hadoo
- Introduction to HPC - ARCHER
A collection of YouTube videos, slides and exercises from ARCHER’s introductory high performance computing course. The course explains the theory and practice of parallel computing with a nice variety of practical examples.
- Provider: Self-paced learning
- Provider: ARCHER, EPCC
- Details and access: Intro to HPC
Data analysis and data science
- Machine Learning
Excellent course on the basic but still powerful and relevant methods in machine learning, easy to follow. The course is at an intermediate level, and Andrew Ng has a great way of explaining complicated concepts in a simplified and practical way.
- Self-paced learning
- Provider: Coursera
- Details and access: Machine Learning
- Deep Learning
A follow-up on the Machine Learning course above, with a focus on Deep Learning, presented in the context of the main applications such as Computer Vision and NLP. Highly recommended.
- Self-paced learning
- Provider: Coursera
- Details and access: Deep Learning