The Introduction to R for the Engineering and Construction Industry course aims to give participants, who are engineers in construction and other industries, a grounding in data science and analytics in relation to their fields. 

There are no formal entry requirements for this course, however it is recommended that Qualified engineers (BEng) or similar, are likely to gain the most from this course. 

This course is for professional engineers working in various sectors, including construction, manufacturing, automotive and related industries.

The two-day course will focus on R programming language at a basic level. 

The course provides a practical introduction to fundamental statistical concepts and tests, such as an introduction to R and R Studio (GUI) and basic commands (variables, operators, data structures, functions and flow control). 

The course also covers sources of datasets and how to clean and import them into R Studio, such as use of vectors, matrices, factors, data frames and lists, as well as summary measures, graphical displays plus statistical tests, such as t-test.

On completion of Introduction to R for the Engineering and Construction Industry, participants will be able to understand computational techniques of analysing data for business intelligence, including predictions and forensic applications.

The course is taught by leading experts in the field: 

• Dr Zulfikar Adamu is an Associate Professor of Strategic IT in Construction at LSBU, with expertise in several areas, including BIM, construction data analytics, blockchain development, smart buildings and computational modelling and simulation of buildings. He is also a Chartered Building Engineer and a fellow of Chartered Association of Building Engineers (FCABE).
• Dr Ayodeji Akiwowo is a data scientist and has had experience at Westcoast Limited, BNP Paribas and SWIFT.
• Dr Shefiu Zakaria is a data scientist at Advanced Technovation.

The course will be taught online via the LSBU learning platform. 

The 2-day course totals approximately 8-hours, and comprises a 4-hour session each day.

There is no formal assessment for this course. 

There is no formal accreditation for this course. By the end participants will have an understanding of R programming language and computational techniques for analysing data for business intelligence, including predictions and forensic applications.

For information on our policies (payment, cancellation, terms and conditions, etc.) visit our general information page.

If you have a question that we haven’t answered here, please contact lsbushortcourses@lsbu.ac.uk and we will respond to your query within 24 hours.