mit why course 2 blog

How to identify and solve complex engineering problems?

Identify, formulate, and solve complex engineering problems by applying fundamental principles of mechanical engineering, science, and mathematics including the steps of abstracting essential information, critically assessing its validity, and making appropriate assumptions.

What is the minimum grade point average for a bachelor's degree?

You must also earn a grade-point average of at least 4.0.

What is the mission of MIT?

That mission, as stated in the current edition of the MIT Bulletin is: The mission of MIT is to advance knowledge and educate students in science, technology, and other areas of scholarship that will best serve the nation and the world in the 21st century.

How to identify and solve complex engineering problems?

Identify, formulate, and solve complex engineering problems by applying fundamental principles of mechanical engineering, science, and mathematics including the steps of abstracting essential information, critically assessing its validity, and making appropriate assumptions.

What is a probability course?

A course in probability, it goes into the foundations of probability using calculus to analyze more difficult probabilistic questions than those posed in 6.042J. The textbook is designed for this course specifically, so it is extremely useful.

Why are differential equations important?

They play a particularly important role in electrical engineering where they (and their discrete counterparts) are essential for understanding circuits, signals and systems. The video lectures associated with this class have significant deviations from the rest of the course content, which caused me to waste some time.

What is an excellent biology course?

Excellent biology course which explores biology from an experimentalist’s viewpoint, giving a grounding in the basics of biochemistry, immunology, genetics and ecology. Textbook is a good supplement as well, also showing the experimental mindset leading to the discoveries.

What is 6.003 signal analysis?

It takes the basic concepts of signal analysis and filters and extends it to state-machine representations and stochastic signals. The inclusion of random signals is very useful for handling noise, so many of the concepts in this class are more practical than their ideal counterparts in 6.003. The free textbook/course notes was very useful.