Free Engineering Courses from Stanford University
Access Free Quality Engineering Education from Stanford University Online
Stanford University is always on the leading edge regarding free online education provision in engineering courses, much varied, for learners across boundaries. Free Engineering Courses from Stanford University are taught by highly rated Stanford faculty and industry experts, so it denotes a great learning experience.
This further proves that it is wholly in agreement with the strong focus of the university on education outreach and its commitment to sharing knowledge outside the traditional campus environment. These come with zero fees, thereby offering a great chance for any person to enhance his or her skills and build knowledge in many aspects of engineering.
1. Convex Optimization SOE-YEECVX101- This is an online self-paced course from Stanford School of Engineering on edX. It has been designed to help participants identify and solve convex optimization problems prevalent in various applications. It covers convex sets, functions, and optimization problems, convex analysis basics, some programming methods — including least squares and semidefinite programming — with duality theory and interior-point methods, and signal processing applications, machine learning, and finance.
Prerequisites: Good knowledge of linear algebra, some probability, basic familiarity with MATLAB, due to the course being about writing scripts in MATLAB and using CVX particularly.
This course is suitable for professionals and students in engineering, computer science, operations research, and other related fields who use scientific computation or optimization in their work. Some courses may be audited for free, and there is also an option to earn a Verified Certificate for a fee.
2. Stanford University’s “Introduction to Haptics”- This course is offered online on edX and provides a unique opportunity to get engaged in the world of Haptic Technology. Instructed by experts Professor Allison Okamura and Ph.D. student Melisa Orta, this self-paced course covers, eidetically, constructing, programming, and controlling Haptic devices — mechatronic systems that simulate touch. While the course itself is free, some of the lab assignments do require a Hapkit, building and programming of which is left to the students. In these labs, there is a focus on practical skills, spanning robotics to bioengineering; target students are those with high school physics and pre-calculus, and experience in programming helps but is not required. Upon completion, students will have the opportunity to receive a Statement of Accomplishment at the end, even if they don’t have a Hapkit for doing lab work.
3. Introduction to Internet of Things”: This is a self-paced online course, “Introduction to Internet of Things” (XEE100), from Stanford School of Engineering, which provides learners with foundational knowledge about IoT. Any interested person may pursue it since there are no prerequisites to taking this course; from micro-cameras in healthcare to smart home devices, in this course, learn what impact IoT has on daily lives.
Under the guidance of Academic Director Olav Solgaard and other faculty, it covers five areas: Applications, Sensors, Embedded Systems, Networking, and Circuits. While this course is optional, it looks like the more intensive IoT Graduate Certificate program to which alone students may apply. The duration of this course is 60 days, without a certificate, and furnishes learners with such knowledge as would be pivotal to an IoT professional.
4. Introduction to Probability Management- This Stanford “Introduction to Probability Management” course on edX is among the first online learning experiences to have ever been placed on edX for learning how to handle the basics of uncertainty management using Stochastic Information Packets. The course is designed for those who know Microsoft Excel; previous statistical training is not necessary. The course covers the Flaw of Averages, common errors in uncertainty representation, and then introduces the Arithmetic of Uncertainty that performs a wide array of calculations that produce more accurate projections. Additionally, students learn to develop interactive Excel simulations that readily translate into programming environments like R and Python. Participants wanting deeper competence can earn a verified certificate by- Working with the free SIPmath Modeler Tools, Reading the book “Flaw of Averages”.
5. Probabilistic Graphical Models 2: Inference- This is the second course in Stanford’s PGM series, available online through Coursera. The course offers a friendly dive into probabilistic inference in learning how to efficiently answer possibly complex questions with PGMs within high-dimensional distributions. It merges statistics with computer science on topics of probability theory, graph algorithms, and machine learning, constituting a necessity in a wide range of application fields, from medical diagnosis to speech recognition. This class is free for participants, though for a fee one can get a verified certificate; an honors track involving implementation of some of the key algorithms in programming is also available.
6. Product Management Program — Stanford’s Product Management Program Preview is the hour-long, free online taste of the full Product Management Program. This self-paced course gives prospective students a sneak peek at the course materials and an opportunity to view instructional videos and complete activities so they can get a feel for the kind of content and teaching style presented in this program.
7. Quantum Mechanics for Scientists and Engineers- This nine-week online course with Stanford, “Quantum Mechanics for Scientists and Engineers” SOE-YEEQMSE01, on edX, is a rigorous 9-week program with a college science or engineering background.
Quantum mechanics has been mystified, and now, through this course, it will be hinted at in modern fields such as nanotechnology and photonics. It covers everything from the role that quantum mechanics has played in today’s technologies down to the very basics of Schroedinger’s wave equation and the principles of Quantum Behavior, such as eigenvalues and eigenfunctions. It’s definitely a course for all, not just physicists, and perfectly suitable to audit for free or acquire a verified certificate.
8. Quantum Mechanics for Scientists and Engineers- Stanford’s SOE-YEEQMSE-02: Quantum Mechanics for Scientists and Engineers, part 2, is an advanced online course using the edX platform. This course is a continuation of QMSE-01, Review of Quantum Mechanics for Scientists and Engineers. It focuses on the applications of quantum mechanics more in science and technology.
Inside, the course will delve into theory for angular momentum, time-independent perturbation theory, invariance and conservation laws, identical particles, quantum mechanics of light, and quantum information. Of interest are personnel who are college-level quantum mechanics-backgrounded individuals.
The course instructor is Professor David Miller. The programme is comprehensive, containing a curriculum that starts from topics on quantum mechanics in crystals right through to the interpretation of quantum mechanics itself, thus setting up the student for both practical applications and further specialized studies in this field.
