About the Course

The “Fundamentals of Artificial Intelligence” course is an introduction to one of the most modern areas of information technology – the field of artificial intelligence (AI). The course covers the history of AI, its key concepts and stages of development, as well as its role in society and fields of application.

This course combines theoretical knowledge with practice, teaching how to use simple AI tools and apply them in real-world examples. During practical sessions, students will work with AI tools and learn text, image, and video generation.

The course demonstrates to learners the opportunities of applying AI technologies in science, business, healthcare, education, manufacturing, and other domains, while also developing practical skills in working with AI tools. In addition, the course addresses the legal and ethical issues of AI use.

Promising directions of AI will also be introduced, such as “Smart Cities,” “AI in Healthcare Systems,” “AI in the Financial Sector,” and “Future Autonomous Vehicles.”

Course Structure 

The “Introduction to Artificial Intelligence” course consists of three modules:

Module 1. Fundamentals of Artificial Intelligence. History of AI development. Generative AI.
Module 2. The impact of AI on society. Legal foundations, ethics, and professional applications of AI.
Module 3. Key issues and challenges of AI application, data privacy.

Each module includes theoretical video lectures, supplementary reading materials, practical tasks, knowledge-checking tests, and a forum for discussion.

Course Goal

The goal of the “Fundamentals of Artificial Intelligence” course is to explain the history and core concepts of AI, demonstrate its role in society and areas of application, and equip learners with both theoretical knowledge and practical skills in using AI tools.

Learning Outcomes (LO)

• LO1: Understand the fundamentals and development of AI (including generative AI).
• LO2: Analyze the impact of AI on society and professional domains.
• LO3: Identify key issues and risks in AI application.

Course Success Indicators

• AI 1.1: Names the main stages of AI development.
• AI 1.2: Distinguishes between types of AI, including generative AI.
• AI 1.3: Describes the basic principles of AI systems operation.
• AI 2.1: Provides examples of AI’s impact on society and professions.
• AI 2.2: Explains the legal and ethical aspects of AI use.
• AI 2.3: Justifies the positive and negative aspects of AI application in various fields.
• AI 3.1: Lists the key issues and risks of AI implementation.
• AI 3.2: Analyzes issues related to personal data protection.
• AI 3.3: Suggests possible approaches for risk mitigation.

 About the author

Makhmut Yerlan– 6M060200 – Master of Natural Science. From 2020 to 2023, completed doctoral studies in the specialty 8D06105 – System Engineering. Since 2019, he has been working at this department. Scientific works:The author has published more than 10 scientific papers. He has 2 articles published in journals indexed in the Scopus database (H-index – 1). erlanmahimut@gmail.com