This month Forbes tells the story of 41-year-old American Ryan Petersen, whose supply chain management software has made his company Flexport the seventh-largest container shipping player in the Pacific region in just eight years. One of the pillars of his success is data analytics and artificial intelligence (AI), which make it much faster and easier to get goods from the manufacturer to ocean carriers and on to the customer.
Dmitry Pavlyuk, Dr. ing., professor of the Faculty of Engineering at the Transport and Telecommunication Institute (TSI), says that AI and data analytics, which complement each other, are playing an increasingly important role in everyday life. Most people already use services based on data analysis and artificial intelligence algorithms, such as using voice commands on their phones, searching for relevant information on the internet or running advanced robot assistants.
“AI algorithms should be able to understand our speech, recognize commands and execute them. Natural language recognition is one of the hallmarks of intelligence. There is a lot of research going on to develop human speech recognition and making decision, based on voice commands,” says the professor.
AI can be used in many industries. AI is often associated with computer algorithms that easily defeat world champions in chess, Go or Dota, or with “intelligent” robotic assistants. In order to make optimal decisions the skills and competences to analyse large data amounts are becoming increasingly important and demanded by businesses. The Transport and Telecommunication Institute conducts research on data analytics using artificial intelligence and offers education in this field.
“Researchers at the Transport and Telecommunication Institute are developing AI methods and models that can handle large data sets and help analysts to make their decisions,” says Pavlyuk.
It is estimated that devices equipped with AI algorithms can do about 45% of the work that humans currently do and expected advances in natural language recognition and use will increase that percentage up to 60%. AI technology will become an integral part of our lives, therefore companies are increasing their investment in it.
“We are gradually moving in that direction. The benefits of artificial intelligence are not yet being fully exploited by real business. Like the industrial revolution, now we speak about the artificial intelligence revolution. AI algorithms have been developed, but they are underutilised by business. It was the same at the beginning of the first industrial revolution – the steam engine had already been invented, but not many entrepreneurs took advantage of it and were able to capitalise on it” – compares Pavlyuk.
At the same time, he stresses that introducing artificial intelligence and automating various processes does not mean that people will lose their jobs. As an example, one of the Transport and Telecommunication Institute’s projects can be mentioned. As the covid pandemic swept the world, people increasingly used various remote working solutions (for example, the now-famous Zoom platform experienced a 610% increase in workload at the start of the pandemic). Developers of such platforms need to analyse large amounts of user data to increase profitability, and AI algorithms have proved essential in the face of rapid user growth. TSI researchers are working on implementing AI-based data analytics for one such platform. “We have developed an algorithm that is based on user behavior and automatically identifies potential customers of individual features. However, the analysts, who used to examine the user information earlier didn’t lose their job – they are doing it more efficiently. It’s a general trend that AI is doing some of the work, making the performance of company employees much more efficient compared to those, who have not implemented AI in their work,” says the professor.
The double degree programme at the Transport and Telecommunication Institute in Computer Science: Data Analytics and Artificial Intelligence ensures students with the skills demanded by business and industry for the complete cycle of data analytics: from formulating a business problem to presenting results and implementation. The focus of the programme is the use of artificial intelligence for big data analysis.
As the name of the programme suggests, students will receive two degrees – one from the Transport and Telecommunication Institute and the other from UWE Bristol, a leading institution in the UK. For the university to offer its students the double degree, the British experts were given full access to curricula, teaching materials, faculty information and even a list of literature available in the university’s libraries. Only when the experts of the University of West England validated all the requirements, the programme was successfully approved.
UWE Bristol contribution is not limited to coordinating curricula. TSI professors are in close contact with their UWE colleagues during course implementation – coordinating study materials, courses, and examination questions, discussing students’ answers together and giving marks, etc. Naturally, this close cooperation means that the language of instruction at TSI is English.
Professor Pavlyuk stresses that students do not need to have a degree in computer science to start this programme. “Classically, the MSc in Computer Science programmes accept people with a bachelor’s degree in computer science who already know mathematics and are good at programming. The distinctive feature of our master’s programme is a wider entry – we invite applicants who have no formal IT education but are professionally involved in data analysis in their applied areas” explains Pavlyuk. Recognizing that it can be difficult for professionals without a formal IT background to start the programme, the Transport and Telecommunication Institute invites graduates with another university degree to take one extra semester of training (Pre-master). This covers the necessary fundamentals of programming and mathematics before the core curriculum. “In many companies, data analytics staff have good business experience but lack the theoretical knowledge and skills in AI. For them, our double degree programme will be very useful,” says the professor.