The Machine Learning, Models and Simulation Principles course offered by MIT xPRO in partnership with Global Alumni is a 5-week online program focused on applying computational tools and machine learning techniques to solve engineering problems and simulate physical processes. The course aims to teach participants how to utilize data analysis methodologies and machine learning in modeling and simulation.
Throughout the course, participants will:
- Learn to make simulations of physical processes using numerical discretization methods.
- Evaluate the trade-off between cost and accuracy in numerical simulations.
- Gain knowledge of optimization techniques and understand their role in machine learning.
- Describe canonical machine learning problems from a statistical perspective.
- Utilize the Monte Carlo method for making predictions and solving risk assessment problems.
This course is designed for:
- Industry professionals with a degree in engineering (mechanical, civil, aerospace, chemical, materials, nuclear, biological, electrical, etc.) or physical sciences.
- Technical professionals with a solid foundation in mathematics, including differential calculus, linear algebra, and statistics typically covered in university studies.
- No programming experience is required, but familiarity with MATLAB(R) can be helpful.
Please find more information on the course website: Machine Learning, Models and Simulation Principles
Please reach out directly to Global Alumni with any questions via this contact form.