and autoML algorithms based on Bayesian optimization, genetic programming, and hyperband. Development in python and tensorflow is required. The main objectives are: Given a business problem identify ...

Algorithm Design Approaches: Divide and Conquer including analysis using recurrences Greedy Algorithms Dynamic Programming Algorithms Algorithms for the following primitives: Sorting: bubblesort, ...

This is an advanced undergraduate course on algorithms. This course examines such topics as greedy algorithms, dynamic programming, graph algorithms, string processing, and algorithms for ...

Advanced study in models of computation, programming languages and algorithms with a specific focus on concurrent programming. The course includes models of computation, programming language paradigms ...

Standard algorithms have evolved to take account of this need. Programming fundamentals - OCR Programs are designed using common building blocks, known as programming constructs. These programming ...

Teaching courses: Programming, Algorithms and Data Structures, Data Science, Machine Learning, GNU/Linux Tools, Natural Language Processing, Non-sqlDatabases, Scrum, Advance Python, Deep Learning, ...

Programming languages: Intermediate to advanced experience with Python Math ... Explore the differences between classical and quantum algorithms. This module covers a brief recap of elementary number ...