Scotland Data Science & Technology Meetup

6.30 for pizza and beers. Talks start 7pm ****************************** Talk 1 "#ScotWiki and other stories" - Dr Sara Thomas Sarah, who is Scotland Programme Coordinator at Wikimedia UK, has been in post since April 2018. She was the Wikimedian in Residence at the Scottish Library and Information Council [masked]), and at Museums Galleries Scotland (2015 - 2016). Sara joins us to talk about the work that Wikimedia UK is doing across Scotland, in libraries, education and heritage. Talk 2 "Automated Artificial Intelligence" Dr Andy Starkey The explosion of activity and interest in AI and machine learning has reached all industry sectors which has meant that the data scientists required to build these solutions are in high demand. Research at the University of Aberdeen has focussed on the development of automated methods of analysing data, and this talk will give an overview of the normal process of building AI solutions and then the improvements to be made by automating this process. The talk will give examples of where it has been applied and show the type of results that can be obtained and also some currently work being undertaken with industry. Dr Andrew Starkey is a lecturer in the School of Engineering at the University of Aberdeen. He has over 20 years of experience in Artificial Intelligence and currently is supervisor of a number of PhD students who are all involved in work related to automated data analysis using AI techniques or autonomous learning. He has previously been involved in research work with AI that resulted in commercial licenses that won a number of industry awards. He is CEO of a spinout company from the University that specialises in automated data analysis using AI technology. He has recently won research funding for projects with Halliburton and WFS in the area of the application of AI technologies. Thanks to MBN Solutions, Data Lab Scotland, and Scotland IS for sponsoring this event. ***************************** Photo by James L.W on Unsplash

Presentation 1 - Strengths and weaknesses of different programming languages With the ever-growing amounts of data we need to deal with, we are experiencing a growing demand for intelligent insights and data-driven strategies. We are also seeing more companies wanting to establish or further advance their data and data science functions. But what is the right skillset for your data science team? If you need to get into hands-on coding, what languages should you learn? Or, if you are already and experienced programmer, do you need to add any more tools to your portfolio of skills? And even if you already have quite a few tricks (languages) up your sleeve, how do you decide what the best language is for the job at hand? In this talk we will provide an overview of the top programming languages for Data Science, with their advantages and limitations. Dr Jasmina Lazić leads, facilitates and enables the commercial adoption of state-of-the-art data science and technology developed at the University of Edinburgh, fostering new collaborative partnerships and technical engagements between the University and industry. Before joining the University of Edinburgh, Jasmina held a number of consultancy and advisory roles in the technology sector, designing, implementing and delivering technical solutions for commercial clients including blue-chip companies. She is also an advocate for high-quality mathematics education and women in technology. Presentation 2 - Brain Computer Interface - An Introduction Description Brain computer interface (BCI) technology is a growing field of research with many current and potential applications. It may also be referred as BMI (Brain Machine Interface) in some literatures. BCI is applicable in medicine, education, monitoring and control systems, entertainment and many more fields. Typical BCI system consists of sensor devices capturing brain signals. Machine learning algorithms are used to associate the captured signals into cognitive state which can then be translated into computer commands. However, this technology is not flawless. There are challenges such as noise to signal ratio, physical and psychological differences of individuals and ethical matters. This talks will provide an introduction to modern BCI technologies with the following agenda. What is Brain Computer Interface (BCI)? How does it works? Where can it be used? What are the limitations? Ethics Prerequisites for Audience: basic understanding of machine learning concepts such as supervised/unsupervised learning would help but it will be covered briefly. No prior knowledge of neuroscience is required. Presenter - Tyn Ong worked as a software developer, system analyst and IT environment manager in Utility and Financial industries for over a decade. He took a career break and recently graduated with MSc in Brain Science from University of Glasgow. He is incubating a startup in BCI while looking for PhD studentship opportunities. https://www.linkedin.com/in/tynong/ Agenda: 6:30 PM – 7:00 PM: Networking 7:00 PM – 7:30 PM: Dr Jasmina Lazić - Chief Data Technologist, Bayes Centre - https://www.linkedin.com/in/jasmina-lazić-850aa9a07.30 PM 7.30 – 7.45 PM: Q & A Session 7:45 PM – 8:15 PM: Tyn Ong - https://www.linkedin.com/in/tynong/ 8:15 PM – 8:30 PM: Q & A Session 8.30 PM - 9.00 PM: Networking and Drink

6.30 for pizza and beers. Talks start 7pm ****************************** Talk 1 tbc Talk 2 tbc ***************************** Photo by Kari Shea on Unsplash

Note - we've moved this one to the second Tuesday in March to fall within #Datafest 2019. Expect something special. 6.30 for pizza and beers. Talks start 7pm ****************************** Talk 1 tbc Talk 2 tbc ***************************** Photo by Joshua Sortino on Unsplash