Artificial Intelligence

Educational Process

The degree program in Artificial Intelligence at the IEU in Poland aims to introduce international students to the core fundamentals of Artificial Intelligence like Statistics, Data Science with Python, Machine Learning, Deep Learning, NLP, Reinforcement Learning, and the working of regenerative AI like ChatGPT. The Artificial Intelligence course gives students the ability to understand and develop Intelligent Software and Hardware Systems. Students explore the techniques and applications of Artificial Intelligence and develop practical skills through exposure to real-world problems and datasets.

The program material is taught through lectures, discussions, practical labs, working in teams, presentations with coursework, and exams used for assessment. In the IEU, Poland students undertake individual research projects under the supervision of a faculty member. Practical classes are conducted in fully equipped IEU, PolandComputer Laboratories with the latest software and technologies. The curriculum is taught by expert faculty with real-world experience ensuring students gain the competencies needed in the field of Artificial Intelligence. The staff of professionals of the European School of IT is ready to support international students’ needs providing a collaborative learning environment with quality interaction between faculty and students.

IEU, Poland has its digital educational platform, which combines European Studying Curriculums and modern technical equipment. It helps IEU, Poland students quickly and easily learn new information required in their work process. University-renowned classrooms and reading rooms, IEU, Poland Library with thousands of books and scientific journals, and Digital IEU, Poland Library with access to electronic resources are freely accessible to students and staff at any time they need it. The Artificial Intelligence course at the IEU in Poland offers exchange and study abroad students the possibility to join internship programs, study abroad programs in Europe, and interactive online courses.

After graduating students are able:

• Comprehend and investigate client needs to create AI models to address real-world issues;
• Design, employ, and improve machine-learning algorithms for many applications, such as time series analysis, language processing, predictive modeling, and computer vision;
• Create or implement artificial intelligence-powered services like chatbots;
• Solve industry problems using natural language processing (NLP), image recognition, or text recognition;
• Research the most recent developments in machine learning and artificial intelligence to keep the organization updated on new techniques;
• Coach and implement machine learning models in a real-world setting;
• Observe the performance of machine learning models and make adjustments as necessary;
• Cooperate with data engineers to help the data be accurate, clean, and accessible;
• Work with software engineers to incorporate machine learning models into the company’s goods and services;
• Prepare technical documentation to explain complicated ideas to non-technical listeners;
• Communicate results and suggestions to upper management;
• Supervise projects, including defining their scope, developing a timeframe, allocating resources, and monitoring their progress;
• Keep up with market trends to spot new AI application prospects;
• Develop computer models based on existing data sets to predict future outcomes;
• Apply artificial intelligence techniques to areas such as machine learning, robotics, image processing, and others;
• Develop specialized computer programs to improve efficiency in business processes such as customer service or inventory management;
• Write computer programs to identify patterns in large sets of data;
• Analyze data sets to identify patterns, anomalies, or other relevant information;
• Develop computer programs to learn from experience and improve their performance over time without being reprogramed;
• Research artificial intelligence topics such as knowledge representation, reasoning, planning, perception, and robotics;
• Create and develop AI models and teach other employees like the product managers and stakeholders the benefits of using them;
• Help employees learn about the systems by designing training manuals and creating online learning materials;
• Convert machine learning models to Application Program Interfaces (APIs);
• Automate the processes needed for data collation purposes;
• Uncover relationships, insights, and inconsistencies in vast and highly variable data sets;
• Work with inputs regular computers can’t handle, including speech, handwritten text, or images;
• Perform data entry, detect fraud, identify unsafe conditions, respond to customer service inquiries, and read radiological scans.