Artificial Intelligence

Bukhara State Technical University

Artificial Intelligence Program

Overview

Artificial intelligence today plays a vital role in the digital development of industry, medicine, finance, education, transport and many other fields. The Artificial Intelligence program at Bukhara State Technical University trains highly qualified specialists capable of analyzing data, building intelligent systems, developing machine learning algorithms, and effectively using modern AI technologies. The curriculum is based on international standards, advanced AI technologies, and IT industry requirements, combining theoretical knowledge with practical experience.

What will you learn?

• Fundamentals of Artificial Intelligence – intelligent systems, AI algorithms and their fields of application.
• Machine Learning – prediction based on data, building classification and regression models.
• Deep Learning – solving complex problems using artificial neural networks.
• Computer Vision – analyzing images and videos, object detection and recognition.
• Natural Language Processing (NLP) – analyzing text and speech, building chatbots and language models.
• Big Data – technologies for collecting, processing and analyzing large volumes of data.
• Cloud Technologies and AI Platforms – building, training and deploying AI models on cloud infrastructure.

What will the graduate achieve?

Graduates will gain professional knowledge and practical skills in developing AI systems, creating machine learning models, analyzing big data, and developing intelligent solutions for real-world problems. They will master the ability to design AI algorithms, process data, use modern programming tools, work effectively in teams, and carry out innovative IT projects. They will also become qualified specialists capable of applying artificial intelligence, deep learning, computer vision, and natural language processing technologies in practice.

Why this program?

• The curriculum is designed in line with international AI standards and modern IT industry requirements.
• Practical laboratory sessions are organized in artificial intelligence, machine learning, and deep learning.
• Training is provided in Python, TensorFlow, PyTorch, Scikit-learn, and other modern AI platforms.
• Practical experience is built through real AI projects, startups, and research work.
• Internship opportunities are available at IT companies, innovation centers, and research laboratories.
• Graduates can work in the public and private sectors as an AI Engineer, Machine Learning Engineer, Data Scientist, Computer Vision Engineer, NLP Engineer, Data Analyst, AI Researcher, MLOps Engineer, or Business Intelligence specialist, or continue their studies at the master's level.

Method of study

The educational process is organized by combining theoretical knowledge with practical experience:

• Lectures and interactive seminar sessions.
• Laboratory sessions in artificial intelligence and machine learning.
• Data analysis and AI model development.
• Practical projects in computer vision, natural language processing, and neural networks.
• Team-based AI projects, hackathons, and startup work.
• Production internships at IT companies, research centers, and technology laboratories.
• Independent research and project-based practical assignments.