Algorithms Specialization

Start Date: 07/04/2021

Course Type: Specialization Course

Course Link:

About Course

Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This specialization is an introduction to algorithms for learners with at least a little programming experience. The specialization is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. After completing this specialization, you will be well-positioned to ace your technical interviews and speak fluently about algorithms with other programmers and computer scientists. About the instructor: Tim Roughgarden has been a professor in the Computer Science Department at Stanford University since 2004. He has taught and published extensively on the subject of algorithms and their applications.

Course Syllabus

Divide and Conquer, Sorting and Searching, and Randomized Algorithms
Graph Search, Shortest Paths, and Data Structures
Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
Shortest Paths Revisited, NP-Complete Problems and What To Do About Them

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Course Introduction

Learn To Think Like A Computer Scientist. Master the fundamentals of the design and analysis of algorithms. Algorithms Specialization This course is designed for learners with some or no prior programming experience in computer science or mathematics. We want to introduce the foundations of algorithms to the general audience, but more importantly this course will help you to apply the algorithms to solve real world problems. This is the third and last course in the specialization, and it is the most rigorous. We hope that learners who complete the first two courses in this specialization are able to understand the topics covered in these third courses. This course requires some prior knowledge of Python programming, as there are multiple files to download and some interactive parts to the course. There are also several functions to refer to to for help. The course consists of six modules, each consisting of an equal amount of video lectures, reading assignments, and quizzes. The final project is a computer program (written in Python) that solves a real world problem. The lectures contain the basics of the algorithms, but the short form of the project is an interactive coding game with your classmates using Python. All of the materials required for the course are available for free. All you will need is a computer with a stable Internet connection, and a willingness to put in the extra effort required in the course. The course is structured as part of a larger Specialization in Computer Science and Programming, and each module is a dedicated video lecture with an assigned homework task. The quizzes are intended to reinforce the material learned in each

Course Tag

Algorithms Dynamic Programming Greedy Algorithm Divide And Conquer Algorithms

Related Wiki Topic

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Interactive specialization According to the second, the Interactive Specialization (IS)
Specialization (functional) Specialization is when people specialize in one thing or another which they are good at.
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Specialization (pre)order For any sober space "X" with specialization order ≤, we have
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Specialization (pre)order The specialization order is often considered in applications in computer science, where T spaces occur in denotational semantics. The specialization order is also important for identifying suitable topologies on partially ordered sets, as it is done in order theory.
Specialization (pre)order The specialization order yields a tool to obtain a partial order from every topology. It is natural to ask for the converse too: Is every partial order obtained as a specialization order of some topology?
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Functional specialization (brain) Subsequent cases (such as Broca's patient Tan) gave further support to the doctrine of specialization.
Functional specialization (brain) Functional specialization suggests that different areas in the brain are specialized for different functions.
Specialization (pre)order On the other hand, the symmetry of specialization preorder is equivalent to the R separation axiom: "x" ≤ "y" if and only if "x" and "y" are topologically indistinguishable. It follows that if the underlying topology is T, then the specialization order is discrete, i.e. one has "x" ≤ "y" if and only if "x" = "y". Hence, the specialization order is of little interest for T topologies, especially for all Hausdorff spaces.
Cognitive specialization Watson et al. provide support for a specific specialization in language-dependent humor. Its adaptive value has both extrinsic and intrinsic components: humor facilitates social bonding if shared extrinsically, and provides pleasure if enjoyed in one's own mind. In addition, Johnson-Frey (2003) proposed a unique human specialization for tool use. According to Johnson-Frey, humans' ability to use tools is based on complex cognitive mechanisms, not just advanced sensorimotor skills. Rather than it being considered a purely physical specialization based only in motor areas of the brain, Johnson-Frey argues that tool use should be classified as a cognitive phenomenon due to its foundation in cognition. On a more philosophical level, Boyer (2003) argues that "religious thought and behavior" is a specialization that originally developed as a by-product of brain function, and its adaptive purposes led to its continued evolution by natural selection. Krueger et al. (2007) have argued that trust, which may form the foundation for helping and altruism and thus the basis of human social interaction, is also a cognitive specialization.
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