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Algorithms and Data Structures Capstone

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Course Features

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Duration

4 weeks

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Effort

10 hours per week

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Teaching Type

Self Paced

Course Description

Building a fully-fledged algorithm to assemble genomes from DNA fragments on a real dataset is an enormous challenge with major demand in the multi-billion dollar biotech industry.

In this capstone project, we will take the training wheels off and let you design your own optimized software program for genome sequencing.

This big data challenge will cover the entire MicroMasters program. After a brief introduction to the steps required to build a genome assembler, we will let you take steps on your own to start working with real data taken from a sequencing machine and see if you can design genome assembly software that can compete with popular software used in hundreds of sequencing labs around the world every day.

Course Overview

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International Faculty

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Post Course Interactions

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Instructor-Moderated Discussions

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Case Studies, Captstone Projects

Skills You Will Gain

Prerequisites/Requirements

Mathematics: proof by induction, proof by contradiction.

At least one programming language: loops, arrays, stacks, recursion

What You Will Learn

Algorithm optimization

Algorithms for genome assembly

Graph algorithms

Course Instructors

Pavel Pevzner

Ronald R. Taylor Professor of Computer Science

Pavel Pevzner is Ronald R. Taylor Professor of Computer Science at the University of California, San Diego. He holds a Ph.D. from Moscow Institute of Physics and Technology, Russia. He is a Howard Hu...

Phillip Compeau

Assistant Teaching Professor

Phillip Compeau is an Assistant Teaching Professor in the Carnegie Mellon University Computational Biology Department, where he serves as Assistant Director of the Master's in Computational Biology p...
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