Learn. Model. Optimize. Control.

APMonitor is an open engineering platform for courses, optimization software, hands-on labs, and a community preparing for an automation future with generative AI.

Explore courses Open GEKKO docs

Millions access APMonitor learning resources each year

Nearly 1,000 technical videos across process systems engineering

10,000+ learners have used the Temperature Control Lab

Five ways into the field.

Start with programming, move through modeling and control, or go directly to machine learning and optimization. Every course is open on the web and built around engineering practice.

CHE 263

Programming for Engineers

Build problem-solving fluency with Python and spreadsheets, supported by MATLAB and Mathcad resources for data and design analysis.

Open programming course

DYNAMICS + CONTROL

Process Dynamics and Control

Connect data-driven and physics-based modeling to controller design, advanced control, and hands-on TCLab exercises.

Open control course

DATA + AI

Machine Learning for Engineers

Combine mathematical foundations with engineering case studies in regression, classification, time series, computer vision, and project work.

Open machine learning

GRADUATE

Dynamic Optimization

Solve time-varying systems with physics-based and machine-learned models, estimation, nonlinear programming, MPC, and optimal control.

Open dynamic optimization

ME 575 / CE 575

Engineering Optimization

Apply linear, nonlinear, discrete, metaheuristic, robust, and dynamic optimization to design problems across engineering disciplines.

Open optimization course

Optimization that leaves the classroom.

GEKKO and APMonitor connect mathematical models to simulation, estimation, control, and optimization. The open Python package supports research, teaching, and industrial applications.

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PYTHON / GEKKO · constrained optimization

from gekko import GEKKO

m = GEKKO(remote=False)
x = m.Var(value=0)
y = m.Var(value=0)

m.Equation(x + y == 1)
m.Minimize(x**2 + y**2)
m.solve(disp=False)

Put equations on the bench.

The Temperature Control Lab turns models, data, PID control, and model predictive control into a real experiment. APMonitor’s browser apps make more systems available without installing software.

Explore the TCLab Open browser apps

Hardware: Two heaters and two temperature sensors
Methods: Model identification, PID, MPC, Python, MATLAB, and Simulink
Learning: Real data, physical constraints, and repeatable experiments

Temperature Control Lab circuit board with two heaters and temperature sensors — Temperature Control Lab · an open Arduino-based experiment

Learn with people who keep building.

APMonitor connects students, professors, researchers, and industry professionals through recorded instruction, live technical exchange, open support, and page-aware AI assistance.

Nearly 1,000 videos

Process systems engineering, taught in public.

Follow technical lessons on programming, optimization, dynamics, control, machine learning, data science, and automation.

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Process Systems Engineering Webinars

Join free live sessions and watch recordings from researchers and practitioners in modeling, estimation, control, and optimization.

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Clara, the virtual TA

Open an instructional page and ask Clara about its concepts, equations, and code. The goal is coaching that strengthens engineering judgment.

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