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  • Solving Algorithms for Discrete Optimization

    Solving Algorithms for Discrete Optimization

    Description Discrete Optimization aims to make good decisions when we have many possibilities to choose from. Its applications are ubiquitous throughout our society. Its applications range from solving Sudoku puzzles to arranging seating in a wedding banquet. The same technology can schedule planes and their crews, coordinate the production of steel, and organize the transportation…

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  • Divide and Conquer, Sorting and Searching, and Randomized Algorithms

    Divide and Conquer, Sorting and Searching, and Randomized Algorithms

    Description The primary topics in this part of the specialization are: asymptotic (“Big-oh”) notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts). Price: Enroll For Free! View Class Language: English Subtitles: English Divide and Conquer, Sorting and Searching, and Randomized…

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  • Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming

    Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming

    Description The primary topics in this part of the specialization are: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal search trees). Price: Enroll For Free! View Class Language: English Subtitles: English Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming – Stanford University

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  • Analysis of Algorithms

    Analysis of Algorithms

    Description This course teaches a calculus that enables precise quantitative predictions of large combinatorial structures. In addition, this course covers generating functions and real asymptotics and then introduces the symbolic method in the context of applications in the analysis of algorithms and basic structures such as permutations, trees, strings, words, and mappings. All the features…

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  • Algorithms, Part I

    Algorithms, Part I

    Description This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers elementary data structures, sorting, and searching algorithms. Part II focuses on graph- and string-processing algorithms. All the features of this course are…

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  • Computer Science:  Algorithms, Theory, and Machines

    Computer Science: Algorithms, Theory, and Machines

    Description This course introduces the broader discipline of computer science to people having basic familiarity with Java programming. It covers the second half of our book Computer Science: An Interdisciplinary Approach (the first half is covered in our Coursera course Computer Science: Programming with a Purpose, to be released in the fall of 2018). Our…

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  • Algorithms, Part II

    Algorithms, Part II

    Description This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers elementary data structures, sorting, and searching algorithms. Part II focuses on graph- and string-processing algorithms. All the features of this course are…

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  • Algorithms for DNA Sequencing

    Algorithms for DNA Sequencing

    Description We will learn computational methods — algorithms and data structures — for analyzing DNA sequencing data. We will learn a little about DNA, genomics, and how DNA sequencing is used. We will use Python to implement key algorithms and data structures and to analyze real genomes and DNA sequencing datasets. Price: Enroll For Free!…

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  • Advanced Trading Algorithms

    Advanced Trading Algorithms

    Description This course will provide back test results for all the strategies in developed and emerging markets. The learner will also be taught scientific ways of back testing without succumbing to either look ahead (or) survival bias. You will learn various methods of building a robust back testing system for the strategies discussed in the…

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  • Trading Algorithms

    Trading Algorithms

    Description This course covers two of the seven trading strategies that work in emerging markets. The seven include strategies based on momentum, momentum crashes, price reversal, persistence of earnings, quality of earnings, underlying business growth, behavioral biases and textual analysis of business reports about the company. In the first part of the course, you will…

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