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Data Structures

Apply basic algorithmic techniques such as greedy algorithms, binary search, sorting and dynamic programming to solve programming challenges. Apply various data structures such as stack, queue, hash table, priority queue, binary search tree, graph and string to solve programming challenges. Apply graph and string algorithms to solve real-world challenges: finding shortest paths on huge maps and assembling genomes from millions of pieces. Solve complex programming challenges using advanced techniques: maximum flow, linear programming, approximate algorithms, SAT-solvers, streaming.



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The techniques and tools covered in Data Structures are most similar to the requirements found in Data Scientist job advertisements.


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Tools
Github Java C++ Python

Techniques
Algorithms Data Analysis Data Sets Data Visualization Decision Trees Image Analysis Programming Optimization Cluster Analysis Big Data Data Processing Segmentation Analysis

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