Machine Learning Certificate
Degree: Certificate
Major: Machine Learning
Hours: 15
Machine Learning Certificate Overview
The graduate Machine Learning Certificate is a path for current Â鶹AV graduate students and individuals only seeking the certification to learn a critical skill that is transforming society. Machine learning techniques are algorithms can be applied to solve problems in robotics, engineering design, supply chain management, search engines, science, medicine, business, equipment monitoring and many other areas.
Academic credits taken as part of the certificate can be applied towards graduate degree programs in Industrial Engineering at LU. Â鶹AV's Industrial Engineering masters and doctoral students can earn this certificate using electives without taking additional coursework. The certificate is a way to demonstrate your interest in this area.
LU offers a wide range of courses that use machine learning to solve real-world problems including process control, computer vision, automation, chemical process modeling, quality control and data analysis. An undergraduate bachelor’s degree is required to enroll in the program and requires four courses (data mining, machine learning and two electives) plus Python proficiency. The certificate can be completed in one year.
Machine Learning Courses You May Take
Special Topics: An investigation into specialized study in advanced areas of engineering under guidance of a faculty member. This course may be repeated for credit when topics of investigation differ.
Data Mining: Data models, distributed databases, special databases, statistical databases, database machines, knowledge bases, database design theory and self-documenting databases.
Machine Learning: This course is an introduction to machine learning, the study of how to make a machine change its actions automatically to improve its performance. In addition, graduate students need to present a research paper.
Heuristic Algorithms: Heuristic Algorithms and applications to classical and real life problems. Justification and logic of heuristic algorithms. Greedy algorithms, Steepest Ascent, Numerical optimization, Simulated Annealing, Taboo Search, Cross entropy optimization, TSP, Set covering, Set partitioning.
Instrumentation Systems and Automation: The course starts with an overview of electronic instrumentation systems for performing engineering measurements on electrical, mechanical, and fluid systems and then progresses to more advanced topics and design of modern computerized industrial control and automation systems. The topics covered include: detailed discussion of physical principles of sensors’ operation; architectures of IAS; principals of signal conditioning, recording and measurement systems for: strain, force, displacement, velocity, acceleration, temperature, fluid mass/velocity, and vibration; digital-interface; PID controls; open system buses; and other advanced topics in ISA.
Career Paths for Machine Learning
Machine learning is a vitally important field and is attracting a lot of attention lately for its technological breakthroughs and lucrative opportunities. Careers in this industry are quickly growing because algorithms are becoming more essential. The high demand for machine learning talent is the driving force behind the high salaries in the field.
Primary Careers
Machine learning engineering, data scientist, natural language processing scientist, software engineer
- Healthcare
- Financial services
- Transportation
- Cybersecurity
- Manufacturing
- Marketing
- Software development
- Technological companies
- Banks and financial firms
- Aerospace product/part manufacturers
- Government agencies
- Hospitals and medical facilities
- Digital media companies