Electrical Engineering, Machine Learning
The Bachelor of Science in Electrical Engineering with a focus on Machine Learning at the University of North Carolina is a four year program designed for students interested in combining electrical engineering principles with advanced computational methods. The curriculum emphasizes machine learning, signal processing, circuit design, data analysis, and automation, providing students with the skills needed to develop intelligent systems and solve complex engineering problems. Students study electronics, control systems, algorithms, and artificial intelligence while developing analytical, technical, and problem-solving skills essential for careers in engineering, technology development, and research. This program prepares graduates to integrate machine learning solutions into electrical systems and drive innovation in a variety of industries.
Throughout the program, students participate in hands-on laboratory work, design projects, and collaborative research that connect theoretical knowledge with practical applications. Coursework emphasizes embedded systems, predictive modeling, data-driven decision making, and software development for engineering applications, equipping graduates to design and implement intelligent systems for real-world challenges. By combining electrical engineering fundamentals with machine learning techniques, the program cultivates professionals capable of developing innovative solutions across technology, energy, automation, and research fields.
Key information
Key Facts
- Program Title: Electrical Engineering, Machine Learning
- Degree Type: Bachelor of Science
- Duration: 4 years
- Mode of Study: Full-time, On Campus
- Application Deadline: 01 February 2026
- Location: University of North Carolina at Chapel Hill, United States
- Field of Study: Electrical Engineering
- Language of Instruction: English
Program Structure
Year 1 - Foundations in Electrical Engineering and Machine Learning
• Introduction to Electrical Engineering
• Calculus and Linear Algebra
• Academic Writing and Research Methods
• Introduction to Programming and Data Analysis
Year 2 - Developing Technical and Analytical Skills
• Circuit Analysis and Electronics
• Probability and Statistics for Engineers
• Algorithms and Data Structures
• Digital Systems and Signal Processing
Year 3 - Advanced Study and Applied Practice
• Machine Learning and Artificial Intelligence
• Embedded Systems and Robotics
• Applied Engineering Projects
• Internship or Research Collaboration
Year 4 - Capstone and Professional Integration
• Senior Seminar in Electrical Engineering and Machine Learning
• Independent Machine Learning Project or Thesis
• Advanced Topics in Automation and Intelligent Systems
• Capstone Portfolio and Presentation
Career Opportunities
Graduates of this program are prepared for careers in electrical engineering, machine learning, automation, robotics, and technology development. Potential roles include machine learning engineers, electrical systems designers, data engineers, automation specialists, and research engineers in technology firms, manufacturing, energy, robotics, and research institutions. The program also provides a foundation for graduate study in electrical engineering, artificial intelligence, data science, or robotics. Graduates gain technical, analytical, and problem-solving skills, enabling them to design intelligent systems, optimize processes, and implement advanced engineering solutions in professional contexts.
Why Choose This Program
This program is ideal for students seeking a curriculum that combines electrical engineering fundamentals, machine learning, and applied problem solving. Learners benefit from laboratory work, design projects, and research mentorship that strengthen technical proficiency, analytical thinking, and professional capabilities. The program emphasizes innovation, real-world applications, and interdisciplinary integration, preparing graduates for careers in technology, automation, and research development. By combining theoretical knowledge with hands-on experience, students acquire the expertise, confidence, and professional readiness necessary to pursue impactful careers or advanced study in electrical engineering and machine learning.
Contact Information
Phone: +1 (919) 966-3621
Email: unchelp@admissions.unc.edu
Address: Jackson Hall, 174 Country Club Road, Chapel Hill, NC 27514, USA
