The Department of Engineering Education offers a wide range of undergraduate and graduate courses that support foundational engineering learning, multidisciplinary design, programming, AI, and engineering education research. Our faculty teach large college-wide courses, support specialized programs, and deliver advanced graduate seminars.
Explore the list below to see the courses regularly taught by our department.
For detailed course outlines and learning objectives, visit our course syllabi page.
Reinforce basic computer engineering skills; design, produce, and report on a computer engineering project, meeting defined specifications and using a structured design methodology and project management.
Prereq: CEN 3031 and EEL 3744C with minimum grades of C.
Reinforce basic computer engineering skills; design, produce, and report on a computer engineering project, meeting defined specifications, and using a structured design methodology and project management.
Prereq: CEN3907C with minimum grade of C.
Two- and three-dimensional graphical methods of visualizing and communicating features of projects for construction involving parcel boundaries, topography, drainage, site modeling, site development, structures, buildings and objects using both traditional and computer-aided drafting and design techniques.
Prereq: minimum 2EG classification.
Problem-solving introduction and thorough exploration of word processing, spreadsheet management, data analysis, graphical display of data, and multimedia presentations. The problem-solving approach also aids students in their specific majors through software applications requiring major-specific professional communication skills in written, graphical, and presentation forms. (M)
COP2271 (can be repeated with change in content up to 6 credits.)
Computer programming and the use of computers to solve engineering and mathematical problems. Emphasizes applying problem solving skills; directed toward technical careers in fields employing a reasonably high degree of mathematics. The programming language used depends on the demands of the departments in the college. Several languages may be taught each semester, no more than one per section. Those required to learn a specific language must enroll in the correct section.
Credits: 2
Prereq: MAC 2312 with minimum grade of C
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COP2271L (can be repeated with change in content up to 3 credits. )
Optional laboratory for COP 2271L.
Prereq: MAC 2312; Coreq COP 2271
Credits: 1
Introductory course for those who have little experience in programming and have been looking to obtain hands-on learning experience in the Python programming language. Developing problem solving and computational thinking skills in an engineering field is encouraged in this course and emphasized with a reasonably high degree of mathematics.
Credits: 3
Prereq:: MAC 2311 with a C grade or better.
Introductory course for those who have little experience in programming and have been looking to obtain a hands-on learning experience to the C++ programming language. Developing problem solving and computational thinking skills in an engineering field is encouraged in this course and emphasized with a reasonably high degree of mathematics.
Credits: 3
Prereq: MAC 2312 with minimum grade of C
Introduces the theory and practice of electrical engineering for those not majoring in electrical engineering. Discusses circuits, machines, electronics and systems.
Credits: 3; Prereq: MAC 2313 and PHY 2049.
An overview of Artificial Intelligence (AI), approaching the concept from its origins to expectations for the future. The course will focus on different technologies from a functionality perspective, utilizing the concepts/skills widely accepted for AI and Machine Learning. Some of the concepts that will be introduced in course are types of AI and machine learning, Hacking, and the IoT, AI today and its outlook for the future.
Credits: 3
Prereq: Junior standing or above
Dynamics of particles and rigid bodies for rectilinear translation, curvilinear motion, rotation and plane motion. Also includes principles of work and energy, and impulse and momentum.
Credits: 2
Prereq: EGM 2511 or EGM 2500, and MAC 2313.
An introductory course on makerspace hands-on skills for prototyping and invention. Exploration of makerspace safety, hand tools, common engineering fasteners, design notebooks, power tools, solid modeling, 3D printing, electrical soldering, wearable electronics, and other maker tools for engineering prototyping. Students will complete individual hands-on projects utilizing makerspace skills introduced. No prior knowledge or experience necessary.
Credits: 1
An overview of Digital Literacy and Digital Culture. The course will take an introductory approach to different technologies from a functionality perspective utilizing the concepts/skills widely accepted for digital competency.
Credits: 3
Prerequisites: Non-Engineering Majors Only
An overview of home automation technologies from a functionality, specification perspective. Apply knowledge of home automation to group designed implementation.
Credits: 2
Prereq: Engineering major or instructor permission
This course is designed to provide the new engineering student with experiences in problem solving, engineering design, programming, and technical communication skills that will provide a foundation for success at the University of Florida. Students will follow the complete life cycle of a typical engineering design project from the inception and idea generation stage all the way to manufacture, experimentation and re-evaluation.
Credits: 3
An introductory engineering course emphasizing the human-centered design process to address a societal challenge. Exploration of solid modeling, introductory programming, sensors, data acquisition, and 3D printing as maker tools for engineering prototyping. Teams will utilize multidisciplinary approaches, project management, written and oral communication skills in creating a societal-based design.
Credits: 2
Covers selected, rotating topics in engineering.
Credits: 1-4
Grading Scheme: Letter Grade
Practical internship/co-op work experience under approved industrial supervision
To register, fill out the registration form, obtain signatures and submit to Pam Simon (phs@ufl.edu) with the request to register. Please indicate the semester for which you want to register.
Credits: 1-3
A two-semester-course sequence in which multidisciplinary teams of engineering students partner with industry sponsors to design and build authentic products and processes—on time and within budget. Working closely with industry liaison engineers and a faculty coach, students gain practical experience in teamwork and communication, problem solving and engineering design, and develop leadership, management and people skills.
Credits: 3
Prereq: prereqs are the same as the equivalent departmental capstone courses
A two-semester-course sequence in which multidisciplinary teams of engineering students partner with industry sponsors to design and build authentic products and processes—on time and within budget. Working closely with industry liaison engineers and a faculty coach, students gain practical experience in teamwork and communication, problem solving and engineering design, and develop leadership, management and people skills.
Credits: 3
Prereq: EGN4951
This course aims to provide a framework to develop real-world machine learning systems that are deployed, reliable, and scalable. The focus of this course is to introduce basic modules of machine learning systems, namely, data management, data engineering, approaches to model selection, training, scaling, monitoring, and deploying to Machine Learning systems.
Credits: 3
Concepts used to skillfully apply and create new Data Science algorithms using a high-level language such as Python or R.
Credits: 3
Prereq: previous experience with computer programming strongly encouraged.
Fundamentals of research design in engineering education research. How to select a research approach that aligns with a research question, principles of research design, management of data, and ethics of human subject research.
The Online Pedagogy for Engineers course is a semester-long, remote course aimed to introduce novice engineering and computer science graduate students with best practices and strategies in online education. Through a learning community of practice, students in this course will learn about relevant learning theories, course development, assessment, accessibility, and inclusion in an online platform. They will collaboratively develop strategies to disseminate the learned content to the larger engineering education community.
Credits: 3
Prereq: Must be enrolled in a graduate-level engineering program
Introduce basic principles and practices of quantitative, qualitative, and mixed method research methods used in engineering education research.
Credits: 3
Introduces students to the design of instructional interventions in engineering education that are focused on facilitating students’ learning. Includes how to align the content, assessment and pedagogy of these interventions guided by the premises of a learning theory.
Credits: 3
This graduate course explores the fascinating yet challenging field of learning in engineering education. Over the past ten decades, research on the mind has provided profound insights into cognitive and affective dimensions of learning, significantly impacting educational practices in higher education and workplaces. This course focuses on cognitive psychology, educational learning theory, and instructional design, introducing novice engineering and computer science graduate students to essential concepts and processes for research and instructional practice. Students from other disciplinary areas are also welcome! Through readings, special speakers, and reflection as part of a community of practice, students in this course will delve into selected topics from human learning, including the nature of expertise, knowledge organization, and implementation, transfer of learning, and cognitive skill assessment from a practical, rather than theoretical, perspective.
Learn and apply evidence-based teaching and assessment techniques. Understand how to create course content based on the student-centered learning approach to teaching. Be introduced to methods to foster an inclusive classroom environment to support diverse learners in your classroom. Develop teaching philosophy based on the principles provided through this course.
Credits: 1
Prereq: Must be enrolled in a graduate-level engineering program
Graduate seminar in engineering education. Speakers may include graduate students in the program, faculty from campus, and speakers from other institutions.
Credits: 1
Applications of first and second laws of thermodynamics to closed and open systems. Steady one-dimensional conduction, lumped parameter analysis, convection, radiation. Intended for non-mechanical engineering students.
Credits: 3
Prereq: CHM 2045, MAC 2313 and PHY 2048.