E.g., Tuesday, February 9, 2016
E.g., Tuesday, February 9, 2016
E.g., Tuesday, February 9, 2016
Jan 18th 2016

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.

Average: 7 (2 votes)
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.

Average: 5.5 (2 votes)
Self Paced Course - Start anytime

Using CUDA to Harness the Power of GPUs.

No votes yet
Mar 16th 2016

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.

Average: 5.2 (5 votes)
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!

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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.

Average: 8.2 (6 votes)
Jan 25th 2016

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).

Average: 7 (4 votes)
Jan 25th 2016

This course begins a series of classes illustrating the power of computing in modern biology. Please join us on the frontier of bioinformatics to look for hidden messages in DNA without ever needing to put on a lab coat. After warming up our algorithmic muscles, we will learn how randomized algorithms can be used to solve problems in bioinformatics.

Average: 9.3 (3 votes)
Jan 22nd 2016

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.

Average: 7.4 (9 votes)
Feb 1st 2016

Learn the basic components of building and applying prediction functions with an emphasis on practical applications. This is the eighth course in the Johns Hopkins Data Science Specialization.

Average: 5.5 (4 votes)
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.

Average: 10 (2 votes)
Jan 25th 2016

Learn the principles of machine learning and the importance of algorithms.

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Sep 15th 2015

Learn the basics of data structures and methods to design algorithms and analyze their performance.

Average: 8 (1 vote)
Jun 15th 2015

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

Average: 9 (2 votes)
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.

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Nov 6th 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.

Average: 3.5 (8 votes)
Oct 5th 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.

Average: 6.5 (4 votes)
Nov 2nd 2015

This course explains how computer science supports the interpretation of the text of genomes. It introduces genomics and algorithmics in a joint approach.

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Nov 3rd 2015

Aprenderemos a modelizar problemas del mundo real mediante su representación con grafos y a resolverlos mediante sus algoritmos asociados

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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.

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