Upcoming Paid Online Courses (3)
Is my program correct? Will it give the right output for all possible permitted inputs? Computers are now essential in everyday life. Incorrect programs lead to frustration in the best case and disaster in the worst. Thus, knowing how to construct correct programs is a skill that all who program computers must strive to master.
In this computer science course, we will presents "goal oriented programming" the way Edsger Dijkstra, one of the most influential computer scientists, intended. You will learn how to derive programs hand-in-hand with their proofs of correctness. The course presents a methodology that illustrates goal-oriented programming, starting with the formalization of what is to be computed, and then growing the program hand-in-hand with its proof of correctness. The methodology demonstrates that, for a broad class of matrix operations, the development, implementation, and establishment of correctness of a program can be made systematic.
Since this technique focuses on program specifications, it often leads to clearer, correct programs in less time. The approach rapidly yields a family of algorithms from which you can then pick the algorithm that has desirable properties, such as attaining better performance on a given architecture.
The audience of this MOOC extends beyond students and scholars interested in the domains of linear algebra algorithms and scientific computing. This course shows how to make the formal derivation of algorithms practical and will leave you pondering how our results might extend to other domains.
As a result of support from MathWorks, learners will be granted access to MATLAB for the duration of the course.
How do you create robots that operate well in the real world? Learn the key math concepts and tools used to design robots that excel in navigating our complex, unstructured world in environments such as aerospace, automotive, manufacturing and healthcare.
In this course, part of the Robotics MicroMasters program, you will learn how to apply concepts from linear algebra, geometry and group theory and the tools to configure and control the motion of manipulators and mobile robots.
You will also learn how to use MATLAB, the standard robotics programming environment and learn step by step how to use this mathematical tool to write functions, calculate vectors and produce visualizations. You will get hands on experience applying your knowledge to projects using various simulations in MATLAB.
Please note that the verified certificate option is not currently open for this course. Please enroll in the audit track and you will be emailed when the verified certificate option is open for enrollment.
The modern data analysis pipeline involves collection, preprocessing, storage, analysis, and interactive visualization of data.
The goal of this course, part of the Analytics: Essential Tools and Methods MicroMasters program, is for you to learn how to build these components and connect them using modern tools and techniques.
In the course, you’ll see how computing and mathematics come together. For instance, “under the hood” of modern data analysis lies numerical linear algebra, numerical optimization, and elementary data processing algorithms and data structures. Together, they form the foundations of numerical and data-intensive computing.
The hands-on component of this course will develop your proficiency with modern analytical tools. You will learn how to mash up Python, R, and SQL through Jupyter notebooks, among other tools. Furthermore, you will apply these tools to a variety of real-world datasets, thereby strengthening your ability to translate principles into practice.