The Faculty of Mathematics and Computer Science is organizing an open introductory course in artificial intelligence for students or persons interested in data analysis and problem-solving from various fields.

The title of the course is Solving Real Problems Using Artificial Intelligence Techniques and contains four modules (2 hours each). The course provides participants with an insight into the world of artificial intelligence and shows examples of how different intelligent optimization and learning algorithms can solve real problems.

The course takes place onsite (BBU building) and online on the Zoom platform according to the following schedule:

• Introduction to Artificial Intelligence, prof. dr. Horia F. Pop, 12^th of May 2021, 3:30-5:30 pm

The course aims to define the field of artificial intelligence by association with human intelligence, concerning the problem-solving qualities of humans. We will also address the difference between AI-based solutions and standard solutions. We will then present, as an example, a set of introductory algorithms in the field of artificial intelligence, namely search algorithms in state space.

• Optimization techniques, Prof. Camelia Chira, 12^th of May 2021, 6:00-8:00 pm

Optimization problems arise in many real applications in industry and society. Optimization involves choosing the best decision or solution from a crowd of possible solutions (which is usually far too large to check all possibilities and then choose the optimal one). Complex problems such as finding the shortest route in traffic, planning tasks, allocating resources, or optimizing a financial portfolio require the use of intelligent optimization techniques. The course introduces some artificial intelligence techniques that can be useful in optimization and exemplifies their use in solving complex real-world problems.

• Supervised Machine Learning, prof. dr. Laura Dioșan, 13^th of May 2021, 3:30-5:30 pm

Today's society is often faced with problems such as predicting the price of a product, tailoring a marketing strategy to a customer profile, recognizing traffic signs, or estimating the risk of cervical cancer in women. While each problem has its specificities, artificial intelligence and supervised learning techniques can identify feasible solutions to these problems. The solutions built interactively in the course will be analyzed from both extrinsic (customer/business perspective) and intrinsic (data analyst perspective) perspectives.

• Unsupervised Machine Learning, assistant drd. Bogdan Mursa, 13^th of May 2021, 6:00-8:00 pm

Most of the above-mentioned processes usually require datasets specifically annotated by specialists in the target domains (marketing experts, doctors, etc.), which leads to higher costs and sometimes even to the impossibility of applying supervised learning. An alternative in these cases is unsupervised learning, which can work with more diverse data that are not specifically prepared for use by certain algorithms. The course will present, interactively, the main algorithms in unsupervised learning, with a focus on understanding them at a conceptual level.

The course will end with an evaluation of the concepts taught and the participants will receive a certificate of attendance.

The participation fee is 500 lei/learner. BBU students and teachers benefit from a 50% reduction of this fee.

Important deadlines:

• 20^th of April 2022 at 4:00 pm pre-registration - Persons interested in this course are invited to fill out a pre-registration form (https://forms.office.com/r/ZPWvs8J4EP).
• 8^th of May 2022, 4:00 pm registration - completion of the training contract and payment of the fee (details of this stage will be communicated individually by email to all pre-registrants).

Contact person:

Alexandrina Colț, alexandrina.colt@ubbcluj.ro