FE Exam Prep — Fundamentals of Engineering has a 10+ year history of successfully preparing graduating and recently graduated engineering students, as well as professional engineers, to take the NCEES Fundamentals of Engineering (FE Exam), also referred to as the Engineer-in-Training Exam (EIT).

FE Exam Prep is held on four consecutive Saturdays starting Feb. 7 (8-hours each day), with multiple breaks. The sessions are taught by top instructors from the Cockrell School of Engineering. The synchronous online format (Zoom) allows participants to ask professors detailed questions in real-time. The sessions are recorded so students can review the study sessions and material later.

Faculty will review and explain sample questions and test-taking tips on:

  • Electrical Circuits
  • Mathematics Part I and Mathematics Part II
  • Fluid Mechanics and Chemistry
  • Mechanics of Materials
  • Statics and Dynamics
  • Thermodynamics
  • Economics
  • Materials Science
  • Ethics

A credit card must be used at the time of payment. Please contact epd@engr.utexas.edu for additional payment methods. If you have any issues with the shopping cart, please email epd@engr.uexas.edu for assistance.

Cohorts begin the first Tuesday of every month, starting November 3, 2026.


Dates: Saturdays Feb. 7-28, 2026

Location: Live Online

Registration Coming Soon

Time: 8 a.m. – 4 p.m. CT

Price: Individual Student

Student Rate: $299

UT Austin Alumni: $399

Public Rate: $499

Corporate / University Partners

•10–24 seats: $425 per seat

•25–49 seats: $375 per seat

50+ seats: Custom pricing — contact us at epd@engr.utexas.edu


Meet the Instructors

Ronald Bell

Ronald Bell

Engineering Scientist

UT Austin Applied Research Laboratories

Area(s) of Expertise:
Engineering systems, engineering education, engineering management, and field engineering

Educational Qualifications:
Ph.D., University of South Florida-Tampa, Electrical Engineering–1995
B.S. and M.S.,University of Missouri-Columbia,–Electrical Engineering–1991 and 1993

Technical Interests:
Systems engineering

Matthew Hall

Matthew Hall

Professor

Louis T. Yule Fellowship in Engineering

Department Research Areas:
Engine Combustion Processes, Thermal Fluids Systems and Transport Phenomena

Educational Qualifications:
B.S. and M.S. Mechanical Engineering. University of Wisconsin,
Ph.D. in Mechanical and Aerospace Engineering, Princeton University.
Post-doctoral positions at Sandia National Laboratories’ Combustion Research Facility and the University of California-Berkeley.

Rui Huang

Rui Huang

Professor

Bettie Margaret Smith Professorship in Engineering

Area(s) of Expertise:
Solids, Structures and Materials

Education:
B.S. Theoretical and Applied Mechanics, University of Science and Technology of China, 1994
 Ph.D., Civil and Environmental Engineering, Princeton University, 2001

Research Interests:

  • Nonlinear mechanics of hydrogels and soft materials
  • Mechanics of graphene and 2D nanomaterials
  • Thermomechanical reliability of advanced packaging for microelectronics
  • Mechanical instability of thin films and nanostructures
  • Computational mechanics, multiscale modeling and simulations
Chad Landis

Chad M. Landis

Professor, Department Associate Chair

T. U. Taylor Professorship in Engineering

Department Research Areas:
Solids, Structures and Materials

Education:
Ph.D.. University of California at Santa Barbara, 1999

Research Interests:

  • Mechanics of materials
  • Ferroelectrics
  • Ferromagnetic shape memory alloys
  • Fracture Mechanics
  • Continuum thermodynamics
  • Computational Mechanics
Howard Liliejstrand

Howard Liljestrand

Associate Chair for Environmental Engineering & Professor

Area(s) of Expertise:
Environmental and Water Resources Engineering

Educational Qualifications:
Ph.D., California Institute of Technology, Environmental Engineering Science, 1980
B.A., Rice University, Environmental Science and Engineering, 1974

Technical Interests:
Aquatic chemistry; contaminant transport; pollutant containment and remediation acid deposition; air pollution modeling