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Taking a college-level programming course? Maximize your learning with these Java tutorials. Peggy Fisher explores command-level programming, basic techniques such as managing loops and creating methods, debugging Java code, working with classes and objects, and storing and sorting arrays. Along the way, she investigates the Java API and Java's capabilities for running simulations and algorithm analysis, and issues challenges to write programs that utilize all of these Java features.
Lecturer at Penn State UniversityPeggy Fisher is a programmer and content manager at LinkedIn Learning.
Peggy's main focus is application programming in Java, Arduino, and C++. She has also worked on courses in COBOL and discrete ,athematics. Previously she was a faculty member at Penn State University's College of Information Sciences and Technology. She started out as a programmer working for a large insurance company, but after 18 years she left her job as a director of information technology to pursue her true passion teaching. She earned a master's degree in math education, and went on to teach high school math and computer science in Pennsylvania. In 2012, Peggy accepted a position as an instructional designer at Penn State, and shortly thereafter began teaching Intro to Application Programming with Java. She is a strong supporter of women in STEM. As one of the few female programming teachers, she serves as a mentor to incoming female freshmen who are considering a career in programming. She was also the K–12 outreach coordinator for the college, where she scheduled, ran, and taught summer camps for middle school and high school students. In a PBS NewsHour interview, she expressed that all students should take at least one programming class either in high school or college. Peggy enjoys constantly learning and finding new and exciting ways to bring technology to life in and outside of the classroom, such as using Arduino microcontrollers or Lego Mindstorms, to help make learning hands-on and fun.
Skills covered in this course
- Another common simulation technique is referred to as the Monte Carlo simulation. A Monte Carlo simulation is a way of approximating the value of a function where calculating the actual value is difficult or impossible. It uses random sampling to define constraints on the value, and then makes a sort of "best guess". Monte Carlo methods vary, but tend to follow a particular pattern. First, define a domain of possible inputs. Then, generate inputs randomly from a probability distribution over the domain. Third, perform a deterministic computation on the inputs. And, finally, aggregate the results. A simple Monte Carlo simulation can be used to calculate the value of PI, or to approximate the value of PI. If you had a circle and a square, where the length of a side of the square was the same as the diameter of the circle, the ratio of the area of the circle to the area of the square would be PI over four. So, if you put this circle inside the square and select many random points…
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