E.g., Thursday, July 2, 2015
E.g., Thursday, July 2, 2015
E.g., Thursday, July 2, 2015
Self Paced

This course focuses on the fundamentals of computer algorithms, emphasizing methods useful in practice. We look into the algorithm analysis as a way to understand behavior of computer programs as a function of its input size.

0
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Self Paced

The advent of computers transformed science. Large, complicated datasets that once took researchers years to manually analyze could suddenly be analyzed within a week using computer software. Computational biology refers to the use of computers to automate data analysis or model hypotheses in the field of biology. This course will prepare students in all subfields of biology for future research and data analysis opportunities. Computer science students interested in biological applications will also find it useful.

0
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Mar 20th 2015

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.

7
Average: 7 (1 vote)
Mar 20th 2015

Analytic Combinatorics teaches a calculus that enables precise quantitative predictions of large combinatorial structures. This course introduces the symbolic method to derive functional relations among ordinary, exponential, and multivariate generating functions, and methods in complex analysis for deriving accurate asymptotics from the GF equations.

0
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Self Paced Course - Start anytime

Can we program machines to learn like humans? This Reinforcement Learning course will teach you the algorithms for designing self-learning agents like us!

0
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Self Paced Course - Start anytime

The main goal of this corse is to provide the student with the fundamentals on computer architecture and to introduce the C.

10
Average: 10 (1 vote)
Self Paced Course - Start anytime

The purpose of this course is to introduce students to the topics of data structures and algorithm design along with their respective applications.

10
Average: 10 (1 vote)
Jun 15th 2015

Introduction to Autonomous Mobile Robots – basic concepts and algorithms for locomotion, perception, and intelligent navigation.

0
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Self Paced Course - Start anytime

In this course you will examine real world problems -- rescue the Apollo 13 astronauts, stop the spread of epidemics, and fight forest fires -- involving differential equations and figure out how to solve them using numerical methods.

0
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Self Paced Course - Start anytime

Ever played the Kevin Bacon game? This class will show you how it works by giving you an introduction to the design and analysis of algorithms, enabling you to discover how individuals are connected.

0
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Aug 17th 2015

This course will cover algorithms for solving various biological problems along with a handful of programming challenges testing your ability to implement these algorithms. It offers a gentler-paced alternative to the instructors' two other courses, Bioinformatics Algorithms (Part 1 and Part 2).

0
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Jul 6th 2015

In this re-offering of our popular introductory course, you'll learn about the tools used by scientists to understand complex systems.

0
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Aug 3rd 2015

Use computer programming as a creative discipline to generate sounds, images, animations and more, with this free online course.

10
Average: 10 (1 vote)
Jun 30th 2015

In this course you will learn several fundamental principles of algorithm design: divide-and-conquer methods, graph algorithms, practical data structures, randomized algorithms, and more.

9.5
Average: 9.5 (2 votes)
Jun 19th 2015

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 basic iterable data types, sorting, and searching algorithms.

8
Average: 8 (1 vote)
Jul 6th 2015

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.

0
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Jul 6th 2015

Learn the basic components of building and applying prediction functions with an emphasis on practical applications.

0
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Jun 29th 2015

Learn the underlying principles required to develop scalable machine learning pipelines and gain hands-on experience using Apache Spark.

0
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