Simulation, Algorithm Analysis, and Pointers

This course is a part of Computational Thinking with Beginning C Programming, a 4-course Specialization series from Coursera.

This course is the fourth and final course in the specialization exploring both computational thinking and beginning C programming. Rather than trying to define computational thinking, we’ll just say it’s a problem-solving process that includes lots of different components. Most people have a better understanding of what beginning C programming means! This course assumes you have the prerequisite knowledge from the previous three courses in the specialization. You should make sure you have that knowledge, either by taking those previous courses or from personal experience, before tackling this course. The required prerequisite knowledge is listed below. Prerequisite computational thinking knowledge: Algorithms and procedures; data collection, analysis, and representation; abstraction; and problem decomposition Prerequisite C knowledge: Data types, variables, constants; STEM computations; selection; iteration (looping); arrays; strings; and functions Throughout this course the computational thinking topics you'll explore are: automation, simulation, parallelization, and algorithm analysis.For the programming topics, you'll continue building on your C knowledge by implementing file input and output in your programs and by exploring pointers in more depth. Module 1: Learn how to read, write, and append to files. Explore automation Module 2: Discover the benefits of simulation and parallelization Module 3: Learn how to perform algorithm analysis to quantify algorithm complexity Module 4: Explore how to use pointers in more depth