Engineering
12 courses · Solano Community College · 2025-2026 Catalog
Classes: Spring 2026
ENGR 001 Introduction to Engineering
- Units
- 2
- Hours
- 2 hours lecture weekly, 36 contact hours total
- Advisory
- ENGL C1000 (Academic Reading and Writing)
- Transfers to
- CSU, UC
A first, non-technical course for engineering students and students who are considering majoring in engineering. Introduction to different engineering fields, the campus life of engineering students, schedule guidelines, opportunities in engineering, engineers' roles in society, ethics in engineering, and strategies and approaches required to survive math, science, and engineering courses. Develops communication skills pertinent to the engineering profession. Possible field trips.
ENGR 003 Introduction to Ethics in Engineering
- Units
- 3
- Hours
- 3 hours lecture weekly, 54 contact hours total
- Transfers to
- CSU, UC
Development of techniques of moral analysis and their application to ethical problems encountered by engineers, such as professional employee rights and whistle blowing; environmental issues; ethical aspects of safety, risk, and liability; conflicts of interest; and ethical issues associated with Data Science, Artificial Intelligence, and Machine Learning. Emphasis on developing the capacity for independent ethical analysis of real and hypothetical cases.
ENGR 007 Python Programming for Scientists and Engineers
- Units
- 4
- Hours
- 3 hours lecture weekly, 3 hours lab weekly, 108 contact hours total
- Prerequisite
- MATH 004 (Precalculus and Trigonometry) Objectives Apply functions to model real world applications. Recognize the relationship between functions and their inverses graphically and algebraically.Outcomes 1. Demonstrate the ability to use functions as a mathematical tool to model the conceptual ideas of college algebra and trigonometry. 2. Solve application problems involving trigonometric functions and graphs. or MATH 002 (College Algebra for Calculus) Objectives Apply functions and other algebraic techniques to model real-world STEM applications. Solve and apply rational, linear, polynomial, radical, absolute value, exponential and logarithmic equations. Recognize the relationship between functions and their inverses graphically and algebraically.Outcomes Apply functions as a mathematical tool to model the conceptual ideas of algebra. Determine relevant information to sketch graphs of functions appropriate to the college algebra curriculum and MATH 051 (Trigonometry) Objectives Analyze and determine procedures for solving equations involving trigonometric and inverse trigonometric expressions; obtain and interpret solutions. Define and graph the trigonometric functions and inverse trigonometric functions. State the domain, range and major properties of the trigonometric functions and inverse trigonometric functions and transformations of these.Outcomes 1. Solve applications using trigonometric functions. 2. Graph trigonometric functions.
- Advisory
- CIS 001 (Introduction to Computer Science) Objectives Comprehend a computer's operation, organization, function, and programming. Analyze a problem and design a solution for that problem. Write program code for the problem solution.Outcomes Students will be conversant in the general vocabulary and concepts of the computer and information science industry. Analyze a problem and then design a solution for that problem that includes a tested and debugged program and appropriate documentation.
- Transfers to
- CSU
- C-ID
- ENGR 120
Introduction to programming for scientists and engineers, utilizing the Python language and environment. Topics covered include object oriented programming, elementary data structures, modules, algorithms, recursion, data abstraction, code style, documentation, debugging techniques, and testing. Also covers the interface between software and the physical world (i.e., sensors).
ENGR 008 Data Science with Python for Scientists and Engineers
- Units
- 4
- Hours
- 3 hours lecture weekly, 3 hours lab weekly, 108 contact hours total
- Prerequisite
- STAT C1000 (Introduction to Statistics) Objectives Solve problems involving probabilities by applying concepts of sample space and probability. Recognize and apply the basic definitions and rules of probability theory. Select the appropriate technique for testing a hypothesis and interpret the result. Formulate hypothesis tests involving samples from one and two populations.Outcomes SLO 1: Critically analyze statistical information presented in media, journals, etc. SLO 2: Convert data to statistical evidence and interpret the evidence. and ENGR 007 (Python Programming for Scientists and Engineers) Objectives 1. Design, implement, test, and debug a program that uses each of the following fundamental programming constructs: basic computation, simple I/O, standard conditional and iterative structures, the definition of functions, and the use of interfaces to the physical world. 2. Use Python to implement, test, and debug algorithms for solving simple problems.Outcomes SLO 1: Student will be able to define, analyze and code the basic Python conditional and iterative control structures and explain how they can be nested and how exceptions can be used. SLO 2: Students will be able to use pre-written Python modules and learn the techniques necessary for creating Python modules. SLO 3: Students will be able to write to and read from files using intermediate file I/O operations in a Python program.
- Transfers to
- CSU
This course covers the three main aspects of data science: inferential thinking, computational thinking, and real-world relevance. Topics include critical concepts and skills in computer programming and statistical inference, and the analysis of real-world datasets, as well as social issues surrounding data analysis such as privacy and design. This course will be taught in Python.
ENGR 010 Machine Learning with Python for Scientists and Engineers
- Units
- 4
- Hours
- 3 hours lecture weekly, 3 hours lab weekly, 108 contact hours total
- Prerequisite
- ENGR 007 (Python Programming for Scientists and Engineers)
- Advisory
- MATH 022 (Analytic Geometry and Calculus III) and MATH 040 (Introduction to Linear Algebra)
- Transfers to
- CSU
Machine Learning encompasses the study of algorithms that learn from data. It has been a key component in a number of problem domains including computer vision, natural language processing, computational biology, and robotics. This class will introduce the fundamental concepts and algorithms in machine learning (supervised as well as unsupervised learning), as well as best practices in applying machine learning to practical problems.
ENGR 011 Deep Learning with Python for Scientists and Engineers
- Units
- 4
- Hours
- 3 hours lecture weekly, 3 hours lab weekly, 108 contact hours total
- Prerequisite
- ENGR 007 (Python Programming for Scientists and Engineers) Objectives 1. Design, implement, test, and debug a program that uses each of the following fundamental programming constructs: basic computation, simple I/O, standard conditional and iterative structures, the definition of functions, and the use of interfaces to the physical world. 2. Use Python to implement, test, and debug algorithms for solving simple problems.Outcomes SLO 1: Student will be able to define, analyze and code the basic Python conditional and iterative control structures and explain how they can be nested and how exceptions can be used. SLO 2: Students will be able to use pre-written Python modules and learn the techniques necessary for creating Python modules. SLO 3: Students will be able to write to and read from files using intermediate file I/O operations in a Python program.
- Advisory
- MATH 022 (Analytic Geometry and Calculus III) Objectives Investigate the fundamental concepts of vector calculus including determining differentiability, and discover the relationship between these concepts and those of the calculus of scalar functions including velocity, acceleration and arc length. Create vector models for applied problems including finding equations of lines and planes and use vector methods to solve them.Outcomes 1. Define, understand, and apply concepts of three dimensional analytical geometry, vector calculus, and functions of two or more variables. and MATH 040 (Introduction to Linear Algebra) Objectives Find the dimension of spaces such as those associated with matrices and linear transformations. Write basic proofs about matrix properties, linear independence, vector spaces and subspaces, linear transformations and eigenvectors using appropriate proof-writing techniques.Outcomes Define, understand and apply the concepts of introductory linear algebra.
- Transfers to
- CSU, UC
Deep Learning is a branch of Artificial Intelligence (AI) that is based on the architecture of Neural Networks. When the number of hidden layers in a neural network is extended, it becomes a ‘Deep Learning’ Neural Network. This course will cover the basic concepts and tools of Neural Networks and Deep Learning, using interfaces such as TensorFlow, Keras, and PyTorch.
ENGR 012 Discrete Mathematics for Scientists and Engineers
- Units
- 4
- Hours
- 4 hours lecture weekly, 72 contact hours total
- Prerequisite
- MATH 004 (Precalculus and Trigonometry) Objectives Manipulate and simplify trigonometric expressions. Recognize the relationship between functions and their inverses graphically and algebraically. Synthesize results from the graphs and/or equations of functions and relations.Outcomes 1. Demonstrate the ability to use functions as a mathematical tool to model the conceptual ideas of college algebra and trigonometry. or MATH 002 (College Algebra for Calculus) Objectives Recognize the relationship between functions and their inverses graphically and algebraically. Synthesize results from the graphs and equations of functions.Outcomes Apply functions as a mathematical tool to model the conceptual ideas of algebra. and MATH 051 (Trigonometry) Objectives Simplify trigonometric expressions.Outcomes 1. Solve applications using trigonometric functions.
- Transfers to
- CSU, UC
Discrete mathematics is the study of mathematical structures that are countable or otherwise distinct and finite. Topics covered include set theory, logic, Boolean algebra, methods of proof, mathematical induction, number theory, discrete probability, combinatorics, functions, relations, recursion, algorithm efficiencies, graphs, trees. Discrete mathematics is a cornerstone of computer science and data science.
ENGR 014 Introduction to Statistical Programming in R for Scientists and Engineers
- Units
- 4
- Hours
- 3 hours lecture weekly, 3 hours lab weekly, 108 contact hours total
- Advisory
- STAT C1000 (Introduction to Statistics) May enroll concurrently. Objectives Recognize and apply the basic definitions and rules of probability theory. Applications will use data from disciplines including business, social sciences, psychology, life science, health science, and education. Select the appropriate technique for testing a hypothesis and interpret the result. Formulate hypothesis tests involving samples from one and two populations. Use linear regression and ANOVA analysis for estimating and inference and interpret the associated statistics. Identify the basic concept of hypothesis testing including Type I and Type II errors.Outcomes SLO 1: Critically analyze statistical information presented in media, journals, etc. and CIS 001 (Introduction to Computer Science) Objectives Comprehend a computer's operation, organization, function, and programming. Debug and test the coded solution for syntax and logic errors. Write program code for the problem solution.Outcomes Analyze a problem and then design a solution for that problem that includes a tested and debugged program and appropriate documentation.
- Transfers to
- CSU, UC
Advances in computing power have enabled scientists to amass huge amounts of data on everything from genetics to climate science, but there is a need for someone to make sense of this data. In this class we will learn how to perform basic statistical analysis such as writing data frames, creating functions, using variables, statements, and loops and employing statistical concepts such as exploratory data analysis, probabilities, hypothesis tests, regression modeling and data visualization, using the statistical software R.
ENGR 017 Introduction to Electrical Engineering
- Units
- 5
- Hours
- 4 hours lecture weekly, 3 hours lab weekly, 126 contact hours total
- Prerequisite
- PHYS 007 (Physics for Science and Engineering) Objectives Calculate the electric field and potential due to a given distribution of charges. Analyze simple electrical circuits using Kirchhoff's laws. Calculate magnetic fluxes and induced EMFs in simple situations involving wires and coils using Maxwell's equations.Outcomes SLO 2: Calculate the electric field and potential due to a given distribution of charges. SLO3: Use Kirchhoff's laws to analyze simple electrical circuits. SLO 4: Use Maxwell's equations to calculate magnetic fluxes and induced EMFs in simple situations involving wires and coils. and MATH 023 (Differential Equations) (may enroll concurrently) Objectives Characterize differential equations according to type (ordinary or partial), linearity and order. Identify higher-order linear differential equations and develop appropriate solution techniques from among classical, power series and Laplace transform methods. Investigate given information on problems involving mechanics, rate of growth and decay, chemical mixtures, and electrical circuits; formulate appropriate mathematical model; develop and interpret solutions.Outcomes 1. Analyze a differential equation and select and implement an appropriate method to solve the equation. 2. Construct and solve a differential equation that models a given situation.
- Transfers to
- CSU, UC
- C-ID
- ENGR 260, ENGR 260L
A study of basic DC circuit analysis techniques including Kirchhoff’s laws, mesh-currents, node-voltages, Thevenin and Norton equivalent circuits, transient and steady-state response of AC passive circuits, power calculations, active circuit elements including operational amplifiers and semiconductor devices. Construction and measurement of electrical circuits using multimeters, oscilloscopes, power supplies, and function generators. Introduction to circuit simulation software.
ENGR 026 Mathematics and Engineering Problem Solving Using Matlab
- Units
- 4
- Hours
- 3 hours lecture weekly, 3 hours lab weekly, 108 contact hours total
- Prerequisite
- MATH 021 (Analytic Geometry and Calculus II) (May enroll concurrently) Objectives Apply numerical methods to evaluate a definite integral and estimate the error. Identify basic differential equations and develop strategies to find their solutions. Define and interpret infinite sequences and infinite series. Use technology (e.g., graphing calculators, computer software) to explore and understand the concepts of calculus.Outcomes Use information to deduce appropriate application of integration. Apply the concepts of infinite series (including series of constants and power series) to questions of convergence, divergence and representation of functions.
- Transfers to
- CSU, UC
This course covers methodologies for solving mathematics and engineering problems. Students will also learn to perform mathematics and engineering computation and visualization using the MATLAB language. Students will write a variety of programs in the MATLAB language.
ENGR 030 Engineering Mechanics: Statics
- Units
- 4
- Hours
- 4 hours lecture weekly, 72 contact hours total
- Prerequisite
- MATH 021 (Analytic Geometry and Calculus II) Minimum grade of C. Objectives Analyze given information and develop strategies for solving problems involving area, volume, and other applications. Demonstrate the relationship between rectangular and polar coordinates and use polar coordinates in applications. Graph, differentiate and integrate functions in polar and parametric forms.Outcomes Use information to deduce appropriate application of integration.; PHYS 006 (Physics for Science and Engineering) Minimum grade of C. Objectives Apply Newtons laws of motion to solve two-dimensional problems in particle statics and dynamics. Solve dynamics problems involving translational or rotational motion to particles and rigid bodies through the use of energy methods.Outcomes SLO 1: Use Newton's laws of motion to solve two-dimensional problems in particle statics and dynamics. SLO 2: Use energy methods to solve dynamics problems involving translational or rotational motion of particles and rigid bodies.
- Transfers to
- CSU, UC
- C-ID
- ENGR 130
This course, which is required for Engineering majors, presents a study of the principles of statics of particles and rigid bodies as applied to equilibrium problems of two and three-dimensional structures, and the principles of friction, virtual work, and stability of equilibrium.
ENGR 045 Properties of Materials
- Units
- 4
- Hours
- 3 hours lecture weekly, 3 hours lab weekly, 108 contact hours total
- Prerequisite
- PHYS 006 (Physics for Science and Engineering) Objectives Apply Newtons laws of motion to solve two-dimensional problems in particle statics and dynamics. Solve the equations for simple harmonic motion for simple systems such as a mass on a spring and a pendulum. Relate the results of experimental data to the physical concepts discussed in the lecture portion of the class.Outcomes SLO 1: Use Newton's laws of motion to solve two-dimensional problems in particle statics and dynamics. SLO 2: Use energy methods to solve dynamics problems involving translational or rotational motion of particles and rigid bodies. and CHEM 001 (General Chemistry I) Objectives Chemical Equilibrium Atomic Structure Chemical Composition Chemical bondingOutcomes Relate atomic and molecular structure to the periodic table and chemical properties.
- Transfers to
- CSU, UC
- C-ID
- ENGR 140B
This required course for Engineering majors covers the application of basic principles of physics and chemistry to the structure and properties of engineering materials. Special emphasis is devoted to the relationship between microstructure and the mechanical properties of metals, polymers, and ceramics and the electrical, magnetic, and optical properties of materials.