Massachusetts Institute of Technology (MIT) is one of the top tier universities in the world for Engineering related disciplines. MIT offers a platform named MIT OpenCouresWare (mit ocw) in which we can have the access to around 2000+ courses offered in the University for free of charge. The courses related to this discipline (ENTC and BME) fall under the sub topic of Electrical Engineering in the Engineering discipline of MIT OCW.
The courses are available for both Undergraduate and Graduate levels while some of the courses comprises of the video lectures. All the courses are provided with a clear lecture notes and a proper calendar system for covering each topic. The syllabus of the course content delivers the course outline just we get here in the department at the initial lecture. One most important thing to consider in following OpenCourseWare courses is that, these are made available for spreading the knowledge. This is solely to develop your core knowledge with your self-learning abilities while the MIT OCW does not provide any certificates for the completion of the course.
I will now focus on a course available in MIT OCW and some tips on how to get the maximum use from the course. The course I choose is Matrix Methods in Data Analysis, Signal Processing and Machine Learning.
This course provides a guidelines or rather the deep mathematical understanding of Signal Processing and Machine Learning which are one of the major expertise in our department. It contains the lecture videos with reading materials extracted from Prof. GIlbert Strang’s Linear Algebra and Learning from Data textbook. The nice thing about this particular course is you have some cool and impressive project ideas you can implement on your own get some hands on experience with mathematical background of what we’re applying in the department. Some courses relevant to our department curriculum provides similar final project ideas from which you can get a Hands on Experience with the tools and technologies you learn.
Nevertheless it is totally up to you to grab the relevant knowledge from a specific course that interest you and that you think will be supportive for you in you projects or researches. Good Luck with your learning process with MIT OCW and hope you get the most out of the freely available course content.