Fundamentals of Engineering Exam Review (Coursera)

Fundamentals of Engineering Exam Review (Coursera)

The purpose of this course is to review the material covered in the Fundamentals of Engineering (FE) exam to enable the student to pass it. It will be presented in modules corresponding to the FE topics, particularly those in Civil and Mechanical Engineering. Each module will review main concepts, illustrate them with examples, and provide extensive practice problems.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Syllabus

WEEK 1
About this course
This section of the course will provide you with an overview of the course, an outline of the topics covered, as well as instructor comments about the Fundamentals of Engineering Exam and reference handbook.

WEEK 2
Mathematics
This module reviews the basic principles of mathematics covered in the FE Exam. We first review the equations and characteristics of straight lines, then classify polynomial equations, define quadric surfaces and conics, and trigonometric identities and areas. In algebra we define complex numbers and logarithms, and show how to manipulate matrices and determinants. Basic properties of vectors with their manipulations and identities are presented. The discussion of series includes arithmetic and geometric progressions and Taylor and Maclaurin series. Calculus begins with definitions of derivatives and gives some standard forms and computation of critical points of curves, then presents grad, del and curl operators on scalar and vector functions. Differential equations are calcified and to methods to solve linear, homogenous equations are presented. Fourier series and transforms are defined along with standard forms, and finally Laplace transforms and their inverse are discussed. In all cases, basic ideas and equations are presented along with sample problems that illustrate the major ideas and provide practice on expected exam questions.

WEEK 3
Probability and Statistics
This module reviews the basic principles of probability and statistics covered in the FE Exam. We first review some basic parameters and definitions in statistics, such as mean and dispersion properties followed by computation of permutations and combinations. We then give the definitions of probability and the laws governing it and apply Bayes theorem. We study probability distributions and cumulative functions, and learn how to compute an expected value. Particular probability distributions covered are the binomial distribution, applied to discrete binary events, and the normal, or Gaussian, distribution. We show the meaning of confidence levels and intervals and how to use and apply them. We define and apply the central limit theorem to sampling problems and brieflyt- and c2. We define hypothesis testing and show how to apply it to random data. Finally, we show how to apply linear regression estimates to data and estimate the degree of fit including correlation coefficients and variances.In all cases, basic ideas and equations are presented along with sample problems that illustrate the major ideas and provide practice on expected exam questions.

WEEK 4
Statics
This module reviews the principles of statics: Forces and moments on rigid bodies that are in equilibrium. We first discuss Newton’s laws and basic concepts of what is a force, vectors, and the dimensions and units involved. Then we consider systems of forces and how to compute their resultants. We discuss the main characteristics of vectors and how to manipulate them. Then the meaning and computation of moments and couples. We discuss the concept of equilibrium of a rigid body and the categories of equilibrium in two dimensions. We show how to draw a meaningful free body diagram with different types of supports. Then how to analyze pulleys and compute static friction forces and solve problems involving friction. The concept and major characteristics of trusses are discussed, especially simple trusses, and we show how to analyze them by the method of joints and the method of sections. Finally, we analyze the geometrical properties of lines, areas, and volumes that are important in statics and mechanics of materials. These are moments of inertia, centroids, and polar moments of inertia of simple and composite objects. In all cases, basic ideas and equations are presented along with sample problems that illustrate the major ideas and provide practice on expected exam questions.

WEEK 5
Mechanics of Materials
This module reviews the principles of the mechanics of deformable bodies. We first review the basic concepts of equilibrium and stresses and strains in prismatic bars under axial loading. Then we discuss the major mechanical properties of common engineering materials, particularly the diagrams for normal stress and strain leading to Hooke’s Law, and their relation to lateral strain through Poisson’s ratio. Shear stresses and their relation to shear strains are then presented. We then analyze in detail deformations and stresses in axially loaded members. This includes uniform and nonuniform loading for statically determinate and indeterminate structures. Thermal effects are then considered: expansion and contraction under temperature changes and the stresses that may develop both with and without prestresses. Stresses on inclined planes under axial loadings and the resulting maximum and minimum normal and shear stresses that result are then discussed. Torsion, the twisting of circular rods and shafts by applied torques is then analyzed. We show how to calculate the angle of twist and shear stress as functions of rod properties and shape under uniform and nonuniform torsion. Applications to power transmission by rotating shafts are presented. We then discuss how shear forces and bending moments arise in beams subject to various loading types and how to calculate them. This is then generalized to local forms of the equilibrium equations leading to rules for drawing shear force and bending moment diagrams. Finally, we compute bending stresses in beams. Strains due to bending and their relation to curvature are first discussed. This is used to compute the bending stresses and their relation to the applied bending moment and beam material and cross sectional properties. This includes a review of computation of centroids and moments of inertia of various areal shapes. We complete this module with a discussion how shear stresses arise in beams subject to nonuniform bending and how to compute them. In all cases, basic ideas and equations are presented along with sample problems that illustrate the major ideas and provide practice on expected exam questions.

WEEK 6
Fluid Mechanics
This module reviews the basic principles of fluid mechanics particularly the topics covered in the FE Exam. It first discusses what a fluid is and how it is distinguished from a solid, basic characteristics of liquids and gases, and concepts of normal and shear forces and stresses. The major fluid properties are then discussed. Next fluid statics are addressed: pressure variation in homogeneous and stratified fluids and application to manometers; forces on submerged plane surfaces and buoyancy forces on fully and partially submerged objects.Flowing fluids are then covered. This includes the equations for conservation of mass (the continuity equation) and energy (the Bernoulli equation). These are then applied to velocity and flow measuring devices: the Pitot tube, and Venturi and orifice meters.The final topic is similitude and dimensional analysis. This includes concepts of fundamental dimensions and dimensional homogeneity, the Buckingham Pi theorem of dimensional analysis, and the conditions for complete similitude between a full-scale prototype flow situation and a small scale model.In all cases, basic ideas and equations are presented along with sample problems that illustrate the major ideas and provide practice on expected exam questions.

WEEK 7
Hydraulics and Hydrologic Systems
This module applies basic principles of fluid mechanics to practical problems in hydraulics, hydrology, and groundwater flow. We first discuss the generalized and one-dimensional momentum theorem and apply it to various typical problems. Flow in pipes and non-circular conduits is discussed beginning with the Bernoulli equation accounting for energy losses and gains. Calculation of head loss due to friction and minor losses due to valves and other accoutrements are presented. Friction losses are calculated for laminar Poiseuille flow and turbulent flow using the Moody chart; examples include computation of pressure drop in laminar pipe flow and turbulent water flow. Methods to calculate flow in pipe networks consisting of multiple connecting pipes and other fittings is then discussed with examples for parallel pipes. Pipes and turbines are then discussed along with their basic equations and definitions. Characteristic curves, especially of centrifugal pumps, are presented and it is shown how to match a pump to a system head.Flow in open channels are discussed including classification of flow types and prediction of uniform flow by the Manning equation. The use of specific energy concepts to solve gradually varying flows, and the importance of the Froude number and sub and supercritical flows are presented. Predictions of hydraulic jumps and flow over weirs are given.Hydrological principles include predictions of surface runoff by the curve number method and peak runoff by the rational formula. Groundwater principles include Darcy’s law for flow through porous media and prediction of drawdown by wells in confined and unconfined aquifers by the Dupuit and Thiem equations.In all cases, basic ideas and equations are presented along with sample problems that illustrate the major ideas and provide practice on expected exam questions.

WEEK 8
Structural Analysis
This module reviews basic principles of the structural analysis of trusses and beams. It builds on material covered in Statics (Module 6) and Mechanics of Materials (Module 8). We first review the conditions for static equilibrium, then apply them to simple trusses and beams. We then consider the deflections of beams under various types of loadings and supports. We derive the differential equations that govern the deflected shapes of beams and present their boundary conditions. We show how to solve the equations for a particular case and present other solutions. The method of superposition and its application to predicting beam deflection and slope under more complex loadings is then discussed. Finally the conditions for static determinacy and indeterminacy are presented along with example applications to trusses and beams. In all cases, basic ideas and equations are presented along with sample problems that illustrate the major ideas and provide practice on expected exam questions.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Delivery Problem (Coursera) Coursera
University of California, San Diego,Higher School of Economics - HSE University

Delivery Problem (Coursera)

We’ll implement (in Python) together efficient programs for a problem needed by delivery companies all over the world millions times per day — the travelling salesman problem. The goal in this problem is to visit all the given places as quickly as possible. How to find an optimal solution to this problem quickly? We still don’t have provably efficient algorithms for this difficult computational problem and this is the essence of the P versus NP problem, the most important open question in Computer Science.

Jun 22nd 2026
3 Weeks
Six Sigma Advanced Define and Measure Phases (Coursera) Coursera
University System of Georgia

Six Sigma Advanced Define and Measure Phases (Coursera)

This course is for you if you are looking to dive deeper into Six Sigma or strengthen and expand your knowledge of the basic components of green belt level of Six Sigma and Lean. Six Sigma skills are widely sought by employers both nationally and internationally. These skills have been proven to help improve business processes and performance. This course will take you deeper into the principles and tools associated with the "Design" and "Measure" phases of the DMAIC structure of Six Sigma.

Jun 22nd 2026
5-12 Weeks
Control of Nonlinear Spacecraft Attitude Motion (Coursera) Coursera
University of Colorado Boulder

Control of Nonlinear Spacecraft Attitude Motion (Coursera)

This course trains you in the skills needed to program specific orientation and achieve precise aiming goals for spacecraft moving through three dimensional space. First, we cover stability definitions of nonlinear dynamical systems, covering the difference between local and global stability. We then analyze and apply Lyapunov's Direct Method to prove these stability properties, and develop a nonlinear 3-axis attitude pointing control law using Lyapunov theory. Finally, we look at alternate feedback control laws and closed loop dynamics.

Jun 22nd 2026
4 Weeks
Introduction to Logic (Coursera) Coursera
Stanford University

Introduction to Logic (Coursera)

This course is an introduction to Logic from a computational perspective. It shows how to encode information in the form of logical sentences; it shows how to reason with information in this form; and it provides an overview of logic technology and its applications - in mathematics, science, engineering, business, law, and so forth.

Jun 22nd 2026
5-12 Weeks
Writing Skills for Engineering Leaders (Coursera) Coursera
Rice University

Writing Skills for Engineering Leaders (Coursera)

Engineering leaders must write extensively for their jobs, and their writing needs to be professional, reader-focused, and error-free. What leaders write in particular can affect productivity and the bottom line, so the written communication that leaders create must be clear and concise. In this course, you’ll learn essential writing skills that you can apply in your daily activities on the job as an engineering leader.

Jun 22nd 2026
4 Weeks
MBSE: Model-Based Systems Engineering (Coursera) Coursera
University at Buffalo,The State University of New York

MBSE: Model-Based Systems Engineering (Coursera)

This Model-Based Systems Engineering (MBSE) course and the Digital Thread courses featured earlier in this specialization bring together the concepts from across digital manufacturing and design, forming a vision in which the geometry of a product is just one way of describing it. MBSE is where the model resulting from the evolution of system requirements, design, analysis, verification and validation activities is the focus of design and manufacturing.

Jun 22nd 2026
4 Weeks
Material Processing (Coursera) Coursera
Georgia Institute of Technology

Material Processing (Coursera)

Have you ever wondered why ceramics are hard and brittle while metals tend to be ductile? Why some materials conduct heat or electricity while others are insulators? Why adding just a small amount of carbon to iron results in an alloy that is so much stronger than the base metal? In this course, you will learn how a material’s properties are determined by the microstructure of the material, which is in turn determined by composition and the processing that the material has undergone.

Jun 22nd 2026
2 Weeks
Experimentation for Improvement (Coursera) Coursera
McMaster University

Experimentation for Improvement (Coursera)

We are always using experiments to improve our lives, our community, and our work. Are you doing it efficiently? Or are you (incorrectly) changing one thing at a time and hoping for the best? In this course, you will learn how to plan efficient experiments - testing with many variables. Our goal is to find the best results using only a few experiments. A key part of the course is how to optimize a system.

Jun 22nd 2026
5-12 Weeks
Statistical Inference (Coursera) Coursera
Johns Hopkins University

Statistical Inference (Coursera)

Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and numerous complexities (missing data, observed and unobserved confounding, biases) for performing inference.

Jun 22nd 2026
4 Weeks
Machine Design Part I (Coursera) Coursera
Georgia Institute of Technology

Machine Design Part I (Coursera)

“Machine Design Part I” is the first course in an in-depth three course series of “Machine Design.” The “Machine Design” Coursera series covers fundamental mechanical design topics, such as static and fatigue failure theories, the analysis of shafts, fasteners, and gears, and the design of mechanical systems such as gearboxes. Throughout this series of courses we will examine a number of exciting design case studies, including the material selection of a total hip implant, the design and testing of the wing on the 777 aircraft, and the impact of dynamic loads on the design of an bolted pressure vessel. In this first course, you will learn robust analysis techniques to predict and validate design performance and life.

Jun 22nd 2026
5-12 Weeks
Introduction to Probability and Data with R (Coursera) Coursera
Duke University

Introduction to Probability and Data with R (Coursera)

This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization.

Jun 22nd 2026
5-12 Weeks
Linear Regression and Modeling (Coursera) Coursera
Duke University

Linear Regression and Modeling (Coursera)

This course introduces simple and multiple linear regression models. These models allow you to assess the relationship between variables in a data set and a continuous response variable. Is there a relationship between the physical attractiveness of a professor and their student evaluation scores? Can we predict the test score for a child based on certain characteristics of his or her mother? In this course, you will learn the fundamental theory behind linear regression and, through data examples, learn to fit, examine, and utilize regression models to examine relationships between multiple variables, using the free statistical software R and RStudio.

Jun 22nd 2026
4 Weeks