Applied Physics

Apply Physics to Emerging Technologies.

Applied Physics bridges physics, engineering, and other sciences to solve complex interdisciplinary problems. As technologies evolve, applied scientists draw on expertise in fields such as atmospheric physics, biomedical sciences, advanced materials, optics and photonics, and quantum technologies.

Consider, for example, magnetic resonance imaging (MRI). Producing clearer images in less time requires an understanding of physics (how magnetic fields and radio waves interact with the body), engineering (designing precise imaging systems), and computation (using algorithms to reconstruct images and reduce noise). It's one example of applied physics translating scientific principles into practical technologies.

9-credit online Graduate Certificate in Applied Physicshelps you build graduate-level expertise in specialized areas of applied physics, preparing you to apply scientific principles to emerging challenges in research and industry.

Who is This Certificate For?

close up of gold nanotubes on a card

MTU’s online certificate in Applied Physics is a versatile certificate that ideal for learners who want to strengthen their graduate-level technical foundation in physics-based problem solving and apply that knowledge to emerging engineering systems.

It may appeal especially to

Engineers and applied scientists who want stronger foundations in computational methods, data analysis, optics/photonics, or nano- and quantum materials
Working professionals seeking flexible online study in a field that bridges physics, engineering, and interdisciplinary technology applications
Learners interested in advanced technical study who want to explore one or more specialized areas of applied physics through a short graduate credential

What You'll Study

Through this certificate, students will build a graduate-level foundation in applied physics and strengthen their ability to work across technical domains.

Coursework will prepare you to

Apply physics concepts to interdisciplinary problems that connect science, engineering, and technology.
Use computational methods and statistical analysis to investigate systems such as low-dimensional materials and photonic systems.
Explore advanced topics in optics and photonics materials and devices, big-data/statistical analysis, machine-learning-enabled computation, and nano- and quantum materials and technology.
Evaluate and implement frameworks across specialized applied physics domains.
Assess emerging technologies by reading and interpreting professional and technical documents.

This graduate certificate requires 9 credits. You'll select three courses from the approved course list, with a maximum of one course coming from the Mathematics discipline.

Physics Course Options

PH 5320 - Mathematical Physics

Partial differential equations of physics, separation of variables, boundary value problems, Sturm-Liouville theory, Legendre and Bessel functions, inhomogeneous partial differential equations, Green's functions. Fourier series, Fourier and Laplace transforms, complex variables, evaluation of integrals by contour integration, linear algebra, matrix methods with emphasis on numerical applications.

Credits: 3.0
Lec-Rec-Lab: (3-0-0)
Semesters Offered: Fall
Restrictions: Must be enrolled in one of the following Level(s): Graduate

PH 5396 - Statistics, Data Mining and Machine Learning in Astronomy

The course focuses on modern problem solving in Astronomy and Astrophysics through statistical inference, machine learning algorithms and data mining techniques. Students will be presented with data sets and research problems in astrophysics and will learn how to formulate solutions.

Credits: 3.0
Lec-Rec-Lab: (2-0-3)
Semesters Offered: Spring, in even years
Pre-Requisite(s): PH 4390

PH 4292 - Light and Photonic Materials

Material properties controlling light wave propagation in optical crystals and optical waveguides. Photonic crystals and photonic devices based on electrical, magnetic, and strain effects.

Credits: 3.0
Lec-Rec-Lab: (3-0-0)
Semesters Offered: On Demand
Pre-Requisite(s): PH 2200(C)

PH 4390 - Computational Methods in Physics

An overview of numerical, computer, and AI methods to analyze and visualize physics problems in mechanics, electromagnetism, and quantum mechanics. Utility and potential pitfalls of these methods, basic concepts of programming, computing environments, AI engines, system libraries and computer graphics are included.

Credits: 3.0
Lec-Rec-Lab: (2-0-3)
Semesters Offered: Fall
Pre-Requisite(s): (PH 2021 or PH 2020) and PH 3410

PH 5530 - Selected Topics in Nanoscale Science and Technology

Presentation and discussion of selected topics in nanoscale science and engineering. Topics include growth, properties, applications, and societal implication of nanoscale materials. Evaluation: attendance and assignment.

Credits: 2.0
Lec-Rec-Lab: (2-0-0)
Semesters Offered: On Demand
Restrictions: May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior

Mathematical Sciences Electives

MA 5701 - Statistical Methods

Introduction to design, conduct, and analysis of statistical studies, with an introduction to statistical computing and preparation of statistical reports. Topics include design, descriptive, and graphical methods, probability models, parameter estimation and hypothesis testing.

Credits: 3.0
Lec-Rec-Lab: (0-3-0)
Semesters Offered: Fall, Spring, Summer
Restrictions: Must be enrolled in one of the following Level(s): Graduate

MA 5751 - Statistical Data Mining

Course will cover various topics in statistical data mining, including linear model selection and regularization, regression and smoothing splines, unsupervised learning, resampling methods, tree-based methods, and deep learning. This course will introduce modern statistical data mining techniques and their applications.

Credits: 3.0
Lec-Rec-Lab: (0-3-0)
Semesters Offered: Spring, in odd years
Pre-Requisite(s): (MA 4700 or MA 4760) and (MA 5701 or MA 4710)

MA 5761 - Computational Statistics

Introduction to computationally intensive statistical methods. Topics include resampling methods, Monte Carlo simulation methods, smoothing technique to estimate functions, and methods to explore data structure. This course will use the statistical software R.

Credits: 3.0
Lec-Rec-Lab: (0-3-0)
Semesters Offered: Fall
Pre-Requisite(s): MA 4770(C) or (MA 4700 and MA 5701)

MA 5781 - Time Series Analysis and Forecasting

Statistical modeling and inference for analyzing experimental data that have been observed at different points in time. Topics include models for stationary and non stationary time series, model specification, parametric estimation, model diagnostics and forecasting, seasonal models and time series regression models.

Credits: 3.0
Lec-Rec-Lab: (0-3-0)
Semesters Offered: Spring
Pre-Requisite(s): (MA 2710 or MA 2720 or MA 3710 or MA 3715 or MA 5701) and (MA 3720 or EE 3180 or MA 4700)

Students choose three total courses. A maximum of one course may be from the MA discipline.

Learn More About Research in Physics at MTU

Where You'll Apply Your Skills

Applied physics is used wherever organizations need professionals who can connect foundational physics to real-world engineering and technology challenges. This discipline supports careers and projects that involve designing and evaluating advanced materials and devices, building computational models, applying statistical and machine-learning methods to complex datasets, and working at the edge of emerging technologies.

Depending on their background and course selections, students may apply these skills in a range of research, laboratory, and technology-driven industry settings.

Optics and photonics materials and devices (Thorlabs, Gentex, Coherent, Lumentum, IPG Photonics)
Computational physics and numerical modeling (Ford, Ansys, COMSOL, NVIDIA)
Big-data statistical analysis and data mining (General Motors, Ford, IBM, Palantir)
Machine-learning–supported technical problem solving (General Motors, KLA, NVIDIA, IBM Research, Siemens)

Nano- and quantum materials and technology (Hemlock Semiconductor, Dow, IBM Quantum, Sandia National Laboratories)
Advanced engineering systems (General Motors, Ford, Lockheed Martin, Boeing, Northrop Grumman)
Interdisciplinary research environments (Dow, NIST, Sandia National Laboratories, Los Alamos National Laboratory)
Technology-driven industrial applications (Dow, Corning, 3M, GE Aerospace, Honeywell)

Get Started on Your Online Applied Physics Certificate.

As research and industry continue to evolve, professionals need stronger interdisciplinary foundations to understand advanced materials, data-intensive analysis, computational methods, and emerging technologies. Michigan Tech’s online graduate Certificate in Applied Physics offers a flexible online pathway for learners who want to connect physics knowledge to real-world technical challenges.