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Dynamic Programming - Applications In Machine Learning and Genomics edX - online learning platform

Highlights
Tuition fee
150 USD / full
150 USD / full
Unknown
Tuition fee
150 USD / full
150 USD / full
Unknown
Duration
1 months
Duration
1 months
Apply date
Anytime
Unknown
Apply date
Anytime
Unknown
Start date
Anytime
Unknown
Start date
Anytime
Unknown
Taught in
English
Taught in
English

About

EdX is an online learning platform trusted by over 12 million users offering the Dynamic Programming - Applications In Machine Learning and Genomics Certificate in collaboration with University of California, San Diego - UC San DiegoX. Learn how dynamic programming and Hidden Markov Models can be used to compare genetic strings and uncover evolution.

Overview

If you look at two genes that serve the same purpose in two different species, how can you rigorously compare these genes in order to see how they have evolved away from each other?

In the first part of the Dynamic Programming - Applications In Machine Learning and Genomics Certificate, part of the Algorithms and Data Structures MicroMasters Program from EdX in partnership with University of California, San Diego - UC San DiegoX, we will see how the dynamic programming paradigm can be used to solve a variety of different questions related to pairwise and multiple string comparison in order to discover evolutionary histories.

In the second part of the course, we will see how a powerful machine learning approach, using a Hidden Markov Model, can dig deeper and find relationships between less obviously related sequences, such as areas of the rapidly mutating HIV genome.

What you'll learn

  • Dynamic programming and how it applies to basic string comparison algorithms
  • Sequence alignment, including how to generalize dynamic programming algorithms to handle different cases
  • Hidden markov models
  • How to find the most likely sequence of events given a collection of outcomes and limited information
  • Machine learning in sequence alignment

Programme Structure

Courses Include:

  • Pairwise Sequence Alignment
  • Advanced Sequence Alignment
  • Hidden Markov Models
  • Machine Learning in Sequence Alignment

Key information

Duration

  • Part-time
    • 1 months
    • 8 hrs/week

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online
  • Self-paced

Campus Location

  • Portland, United States

What students do after studying

Join for free or log in to access our complete career info list.

Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

  • Some prior experience required
  • To obtain additional information about the programme, we kindly suggest that you visit the programme website, where you can find further details and relevant resources. 

Tuition Fees

Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
  • International

    Non-residents
    150 USD / full
    150 USD / full
  • Out-of-State
    150 USD / full
    150 USD / full

Additional Details

  • Unlimited access + verified certificate: $150
  • Limited access: free

Funding

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Dynamic Programming - Applications In Machine Learning and Genomics
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