PROGRAMS

BACHELOR OF AI/DATA SCIENCE EDUCATIONAL PROGRAM

The actuality of the Bachelor’s Program in Data Science and Artificial Intelligence is caused by the increased demand from the modern organizations on such specialists, who will be able to answer the challenges related to modern technologies. The Data Science and Artificial Intelligence Program includes not only the field of programming, but also basics of mathematics as well. Except for the program skills, the alumni of this field necessarily need algorithmic thinking and solid base in mathematics. The curriculum of Data Science and Artificial Intelligence is prepared in such manner, that most of the core subjects serve to provide students with such base. The curriculum offers the students a rich list of practical subjects as elective courses, which will enable them to select courses based on their interest and according to the market demand. 

The mission of the program

The mission of the program of Data Science and Artificial Intelligence is to prepare students in the mentioned field. The program ensures for students high quality educational process, modern learning courses and access to all necessary resources. Also, to provide students with necessary knowledge and skills, which are necessary for achieving success in the fast-developing and complex field of computer science.

GENERAL INFORMATION 

  • Program Name: Data Science and Artificial Intelligence
  • Higher Education Cycle: First level (bachelor)
  • Qualification to be granted: Bachelor of Computer Science 0613.1.2 
  • Detailed field: Software and Applications Development and Analysis 0613
  • Study Language: Georgian
  • Duration of studies: 4 academic years / 8 terms
  • Volume of the program: 120 ECTS

PROGRAME GOALS

The goals of the Bachelor’s Program in Data Science and Artificial Intelligence of the Georgian National University SEU are:

I. Provide the alumni with profound theoretical and practical knowledge of Computer Science;
II. Provide the alumni with the competence of solution of practical tasks given in the field of Data Science and Artificial Intelligence;
III. Provide the alumni with the skill of using of the methods and instruments of the field of Computer and Data Science;
IV. By means of the received education, provide the alumni with the skill to answer the challenges related to the modern technologies and become a competitive specialist, who will be able to get employed at private and public structures. 

Outcomes

LEARNING OUTCOMES

The alumni of the Data Science and Artificial Intelligence Program of the Georgian National University SEU:

I. Knows basic concepts of Data Science and theoretical issues;
II. Describes the instruments and the theoretical issues necessary for the implementation of the projects of the field of Data Science and Artificial
Intelligence;
III. Discusses the algorithms, respective models and software related to Computer and Data Science pursuant to the given task;
IV. Analyzes the tasks given in Computer and Data Sciences using respective disciplines;
V. Applies the instrument sof Data Science and Artificial Intelligence for the development of the computer technology-based solutions.
VI. Obtains, processes, analyses and presents information pursuant to the given requests;
VII. Prepares presentation, can communicate effectively in the process of professional activities;
VIII. Considering the principles of professional ethics, plans development-oriented activities, in the process of both – individual and teamwork.

TEACHING AND LEARNING METHODS

 The totality of the teaching and learning methods applied to various components of the program ensure the achievement of the learning outcomes determined under the program. It is impossible to study any specific issue during the learning process using just one method. The lecturer has to apply different methods in the learning process, also, in frequent cases, there is a merger of methods. In the learning process the methods complement each other. The lecture selects the necessary method among them based on specific goal and objective.

Lecture – is a creative process where a lecturer and a student take part simultaneously. The main aim of the lecture is to understand the idea of the subject regulations to be learnt, which means a creative and active perception of presented material. In addition, an attention should be paid to the main provisions of transferable material, definitions, indications, assumptions. Critical analysis of the main issues, facts and ideas are necessary. A lecture should provide a scientific and logically consistent knowledge of main subject regulations to be learnt without excessive details overloading. Therefore, it must be logically completed.

Collaborative – teaching method involves dividing students into groups and giving them learning assignments. The members of the group work on the issue individually and at the same time share it with the other members of the group. Due to the set task, it is possible to redistribute functions among the members during the group work process. This strategy ensures maximum involvement of all students in the learning process.

Independent work- material heard in the lecture is formed as a whole system of knowledge by the independent work of the student. The student should be interested in the book and other sources of information and want to study the issues independently, which is a way to stimulate independent thinking, analysis and drawing conclusions.

Verbal, or oral, method includes lecture, narration, conversation, and etc. In this process, the lecturer conveys the teaching material through words, while the students actively perceive and master it by listening, remembering and understanding.

Method of working on a book reading, processing and analysis of the given extra materials.

Method of written work implies the following activities: making excerpts and notes, writing a paper etc.

Practical methods combine all the forms of teaching that develop the student’s practical skills, here the student independently performs this or that activity on the basis of acquired knowledge, for example: professional practice, field work, etc.

Discussion / debate is one of the most common methods of interactive teaching. The discussion process drastically increases the quality and activity of student engagement. The discussion can turn into an argument. This process is not limited to questions asked by the lecturer. This method develops the student’s ability to argue and justify his or her own opinion.

Problem-Based Learning (PBL) – a learning method that uses the problem in the early levels of the process of acquiring and integrating new knowledge.

Cooperative learning – is a teaching strategy in which each member of the group is required not only to study but also to help his or her teammate learn the course better. Each group member works on the problem until all of them have mastered the issue.

Case study – an active problem-situation analysis method, based on teaching by solving specific tasks – situations (so-called case solving). This method of teaching is based on the discussion of specific practical examples (cases). The case is a kind of tool that allows the application of the acquired theoretical knowledge to solve practical tasks. By combining theory and practice, the method effectively develops the ability to make reasoned decisions in a limited amount of time. Students develop analytical thinking, teamwork, listening and understanding alternative thinking, the ability to make generalized decisions based on alternatives, plan actions, and predict their outcomes.

Brain storming- is a method student can use to generate ideas for solving the problem. In the process of brainstorming students must suspend any concerns about staying organized. The goal is to pour their thoughts without worrying about whether they make sense or how they fit together. It is effective method within the group and contains following levels:

  • Creative definition of problem
  • Taking notes of ideas without criticism
  •  Definition of estimation criterion
  • Evaluation of ideas by preliminarily defined criterion
  • Selection of best matching ideas by exclusion
  • Manifestation of idea with the highest estimation for solving the problem

Demonstration method- involves visual representation of information. It is quite effective in terms of achieving results. In many cases, it is best to provide the material to students in both audio and visual form. Demonstration of the study material can be done by both the teacher and the student. This method helps us to visualize the different levels of perception of the learning material, to specify what students will have to do independently; At the same time, this strategy visually illustrates the essence of the issue / problem. Demonstrations may look simply, such as solving a mathematical problem, visualizing a step on its board, or taking on a complex look, such as conducting a multi-level science experiment.

Inductive Method- the process of reasoning in which the premises seek to supply strong evidence for the truth of the conclusion. The truth of the conclusion of an inductive argument is probable, based upon the evidence given.

Deductive Method- the process of reasoning from one or more statements (premises) to reach a logically certain conclusion. It works from the more general to the more specific.

Analysis- through this method, lecturers and students discuss specific cases together. Students thoroughly learn the previously unknown sides of the issue. The method of analysis enables us to break up the whole part of the study the material into constituent parts, which simplifies the understanding of the specific issues of the problem.

The synthesis method – involves composing one whole by grouping individual issues. This method helps to develop the problem as the ability to see the whole.

The explanatory method is based on reasoning around a given issue. In presenting the material, the lecturer gives a specific example, which is discussed in detail in the given topic.

Action-oriented teaching – requires the active involvement of the lecturer and the student in the teaching process, where the practical interpretation of the theoretical material becomes particularly important.

The heuristic method- is based on a step-by-step solution to a task posed to students. This process is accomplished by teaching the facts independently and seeing the connections between them.

Laboratory learning- is more visible method and allows you to perceive an event or process. In the lab, the student learns to conduct an experiment. During the laboratory study, the student should be able to control the devices, adjust them and determine the mode of operation. Habits developed in learning laboratories provide an understanding of the theoretical material heard in lectures.

The development and presentation of the project – is a combination of educational and cognitive tools, which allows to solve the problem in the conditions of the necessary presentation of the student’s independent actions and the obtained results. Teaching in this way raises students’ motivation and responsibility. Work on the project includes levels of planning, research, practical activity and presentation of results according to the chosen issue. The project will be considered feasible if its results are visible, convincing and concrete. It can be performed individually, in pairs or in groups; Also, within one subject or several subjects (integration of subjects). Upon completion, the project will be presented to a wide audience.

E-learning – This method includes three types of teaching:

  • Attendance when the teaching process takes place within the contact hours of the lecturer and the students, and the teaching material is delivered through an electronic course.
  •  Hybrid (attendance / distance), the main part of the learning course is done remotely, and a small part is done within the contact hours.
  •  Completely distance learning involves conducting the learning process without the physical presence of the lecturer. The learning course is held electronically from beginning to end.

Bachelor’s project is the final phase of the Bachelor level and it aims at the systematization of the gained theoretical and practical knowledge and the reasoned solution of certain scientific, technical, economic and professional objectives. The thesis must reveal the level of knowledge of the research methods and experiments related to the given issue and the readiness of the student to work independently in the conditions of the future professional activities. Consultation – the contact time used by the student with the supervisor of the Bachelor’s thesis, when the student obtains information regarding the issues of drafting the plan, searching for empirical materials, their preparation, making conclusions in terms of the contents of the thesis, technical design of the thesis, its preparation for presentation.

Professional practice is an important part of the learning process and represents the planned and purposeful activity of the student, reinforcement of the theoretical knowledge obtained in an academic environment and gaining of practical skills. The aim of the practice is to equip students with

SCOPE OF EMPLOYMENT OF THE PROGRAM

The alumni of the Bachelor’s Program in Data Science and Artificial Intelligence can get employed both in public and private structures. The alumni
will be able to work as a software developer, data analyst, specialist of information technologies, network administrator etc. They will be able to get
employed everywhere, where they will practice their major professional work.