Algorithmic Thinking (Part 2)

Start Date: 12/13/2020

Course Type: Common Course

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About Course

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems. In part 2 of this course, we will study advanced algorithmic techniques such as divide-and-conquer and dynamic programming. As the central part of the course, students will implement several algorithms in Python that incorporate these techniques and then use these algorithms to analyze two large real-world data sets. The main focus of these tasks is to understand interaction between the algorithms and the structure of the data sets being analyzed by these algorithms. Once students have completed this class, they will have both the mathematical and programming skills to analyze, design, and program solutions to a wide range of computational problems. While this class will use Python as its vehicle of choice to practice Algorithmic Thinking, the concepts that you will learn in this class transcend any particular programming language.

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Course Introduction

Algorithmic Thinking (Part 2) In this course, you will study the concept of algorithm complexity in a general framework. We will use it to analyze systems of classical algorithms and introduce the concepts of indexing, traversals, and recursion. We will use the computer science tools of the formulae of abstract mathematics to study the algorithms themselves. We will discuss the huge variety of algorithms that are used in industry today. You will learn how to think more systematically about algorithms and their complexity. You will also learn to think more fluently on the machine learning front. After completing this course, you will be able to: - construct an index of contemporary algorithms to analyze as a function of their complexity - use the formulae of abstract mathematics to analyze algorithms - understand algorithms by applying them to a large variety of problems - recognize the use of recursion and traversals in a classical algorithm - understand the concepts of indexing, traversals, and recursion introduced in a classical algorithmWelcome & The Formulae of Abstract Mathematics Indexing & Recursion Trees & Solving Problems Simplified Programming & Summary Evaluation Algorithmic Thinking (Part 1) In this course, you will study the concept of algorithm complexity in a general framework. We will use it to analyze systems of classical algorithms and introduce the concepts of indexing, traversals, and recursion. We will use the computer science

Course Tag

Algorithms Python Programming Algorithmic Efficiency Dynamic Programming

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