Search result for Courses taught by Neil Rhodes

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  • Computer Science(6)
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  • Algorithms(6)
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Description of Algorithms Courses
  • Algorithms is a course that focuses on the design and implementation of efficient algorithms for solving problems. This course is essential for computer science students and professionals who want to develop their skills in problem solving and software design.
Common Things Learned
  • In Algorithms courses, students learn about different algorithms and their complexity, time and space complexity analysis, sorting algorithms, searching algorithms, graph algorithms, dynamic programming, and much more. They also learn how to analyze the efficiency of an algorithm, and how to develop algorithms that optimize performance for specific situations.
Typical Student
  • Typical students of Algorithms courses are computer science majors, software engineers, and other professionals who want to improve their problem-solving and software design skills. These students have a strong foundation in mathematics and programming, and are looking to develop their skills in algorithm design and analysis.
 
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Algorithmic Toolbox

by Alexander S. Kulikov , Michael Levin , Neil Rhodes , Pavel Pevzner , Daniel M Kane
  • 4.6
Approx. 39 hours to complete
The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming. You will practice solving computational problems, designing new algorithms, and implementing solutions efficiently (so that they run in less than a second). Programming Challenges Welcome!...
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Data Structures

by Alexander S. Kulikov , Michael Levin , Daniel M Kane , Neil Rhodes
  • 4.6
Approx. 25 hours to complete
A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. In this course, we consider the common data structures that are used in various computational problems. You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments....
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Algorithms on Graphs

by Alexander S. Kulikov , Michael Levin , Daniel M Kane , Neil Rhodes
  • 4.7
Approx. 55 hours to complete
If you have ever used a navigation service to find optimal route and estimate time to destination, you've used algorithms on graphs. In this course, you will first learn what a graph is and what are some of the most important properties. You will use these algorithms if you choose to work on our Fast Shortest Routes industrial capstone project....
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Algorithms on Strings

by Alexander S. Kulikov , Michael Levin , Pavel Pevzner , Neil Rhodes
  • 4.5
Approx. 18 hours to complete
World and internet is full of textual information. We search for information using textual queries, we read websites, books, e-mails. All those are strings from the point of view of computer science. To make sense of all that information and make search efficient, search engines use many string algorithms. Suffix Trees...
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Advanced Algorithms and Complexity

by Alexander S. Kulikov , Michael Levin , Daniel M Kane , Neil Rhodes
  • 4.6
Approx. 27 hours to complete
You've learned the basic algorithms now and are ready to step into the area of more complex problems and algorithms to solve them. Advanced algorithms build upon basic ones and use new ideas. We then proceed to linear programming with applications in optimizing budget allocation, portfolio optimization, finding the cheapest diet satisfying all requirements and many others....
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Genome Assembly Programming Challenge

by Alexander S. Kulikov , Michael Levin , Pavel Pevzner , Neil Rhodes
  • 4.5
Approx. 18 hours to complete
In Spring 2011, thousands of people in Germany were hospitalized with a deadly disease that started as food poisoning with bloody diarrhea and often led to kidney failure. It was the beginning of the deadliest outbreak in recent history, caused by a mysterious bacterial strain that we will refer to as E....
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Time
  • To get the fundamentals of Algorithms, it usually takes around one semester of study, which is about 4-5 months. However, to become well adept in this topic, it requires years of practice and experience. Students need to constantly practice their algorithm design and analysis skills by solving problems and implementing algorithms in real-world scenarios.
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Fields

  • Algorithms is used in various fields, such as computer science, engineering, biology, finance, and many others. In computer science, algorithms are used to solve complex problems and optimize performance. In engineering, algorithms are used in the design and analysis of systems. In biology, algorithms are used to analyze genetic data and model biological systems. In finance, algorithms are used to analyze market data and make investment decisions. Algorithms are also used in many other fields that require mathematical modeling and optimization.

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Careers

  • Algorithms is needed in many specific careers, such as software engineering, data science, artificial intelligence, finance, and many others. In software engineering, algorithms are used to develop efficient and scalable software systems. In data science, algorithms are used to analyze and model large data sets. In artificial intelligence, algorithms are used to develop intelligent systems that can learn and adapt. In finance, algorithms are used to analyze market data and make investment decisions.

  • Examples of Common Careers
    • Software Engineer
    • Data Scientist
    • Artificial Intelligence Engineer
    • Quantitative Analyst
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