1st University of Malta Data Science Summer School

The event is targeted at students (undergrad, MSc, and PhD), postdocs, academics, members of public institutions, ICT practitioners and professionals. The event will be on-campus (Msida) and will take place in the last two weeks of July (from 18 to 29 July).

Why Data Science? 

Data science has been described as the ‘sexiest job of the 21st Century’. It is expected to be one of the most sought-after skills in the next three years. Data science combines computer science, statistics, information science, AI, and statistics, together with their related methods, processes, algorithms, and systems for the purpose of extracting knowledge, patterns, trends, and insights from data. Over the past few years, data science has become increasingly popular and is now widely applied in business, industry, and academia.

The Data Science Platform (DSP) is organising the 1ST UM Data Science Summer School which will be held in the afternoons in the two-week period Monday 18 July to Friday 29 July. The school will be held at the University of Malta at the Msida campus. Sessions will be from 13:00 to 17:30 and consist of a two-hour lecture will be followed by a two-hour practical tutorial. There will be a 30-minute refreshment & networking break in between.

The school is targeted at undergrad and postgrad students in ICT and related areas as well as past graduates, practitioners, and professionals who are interested in learning more about this exciting new field. The DSP is committed to helping build a more diverse, and inclusive, data science community and also welcomes postgraduate students and professionals/practitioners in non-ICT areas.

Our lecturing team consists of academics and researchers in computer science, AI, computer and communications engineering, statistics, and information systems.

Learning and Skills Outcomes

Upon successful completion of the school attendees should be able to:

1. Outline the challenge of working with big data using statistical methods
2. Integrate the insights from data analytics into knowledge generation and decision-making
3. Analyse how to acquire data, both structured and unstructured, process it, store it, and convert it into a format suitable for analysis
4. Apply the basics of statistical inference including probability and probability distributions
5. Explain classification methods and related methods for assessing model fit and cross-validating predictive models
6. Identify, and illustrate, the main concepts of machine learning algorithms and their application
7. Outline the difference between supervised and unsupervised learning approaches
8. Summarize the quantitative methods of text analysis, including mining social media and other online resources
9. Compare, and contrast, the various data interpretation and visualization tools
10. Use Python as the main programming language to perform data science, and
11. Summarize the various privacy and ethics issues in Data Science.

Admission Requirements

UM Data Science Summer School applicants should have a good background, and proficiency, in any of the following or related areas: computer science, software, IT, or other related areas. A first degree in one of these areas is recommended but professional experience may also be sufficient to make up for the lack of a first degree. 

 A good knowledge of, and proficiency in, the Python programming language are recommended.

Teaching methods

• Lectures
• Practical Sessions and Tutorials
• Work in Groups

Schedule

Weekdays 1pm to 4.30pm on campus. 2-hour lecture followed by 2-hour practical with a 30-minute networking and tea & coffee break in between.

Attendees are expected to bring their own laptop. The first and second sessions will cover the installation, and configuration, of Anaconda and Python.

Language of Instruction

English

Assessment & Certification

Attendees will not be evaluated and graded. A certificate of attendance will be awarded to attendees who attend all the sessions.

Registration

Attendees can register and pay for the summer school online. Payment is required at the time of registration. Seats are allocated on a first-come first-served basis.

For group registrations please contact us as listed below.

At the moment only 5 places are left. Once all places are taken, registration portal will be closed. Thus registration deadline may be moved earlier than the advertised date.

Contact us

For more information and questions regarding the Summer School please do not hesitate to email

Download the Summer School brochure! 

Coming from abroad?
Click here for info on accommodation and travel requirements.