فرصة

Dynamic Programming: Applications In Machine Learning and Genomics

Learn how dynamic programming and Hidden Markov Models can be used to compare genetic strings and uncover evolution.

  • English
  • With Certificate

Tutor Name

edX
Dynamic Programming: Applications In Machine Learning and Genomics

About the Course

Edx is offering a free online course in the Applications of Dynamic Programming In Machine Learning and Genomics. In this course, you will learn how dynamic programming and Hidden Markov Models can be used to compare genetic strings and uncover evolution.

About the Course:-

  • In the first part of the course, part of the Algorithms and Data Structures MicroMasters program, you 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, you 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.

Syllabus:-

  • Week 1: Pairwise Sequence Alignment
    • A review of dynamic programming, and applying it to basic string comparison algorithms.
  • Week 2: Advanced Sequence Alignment
    • Learn how to generalize your dynamic programming algorithm to handle a number of different cases, including the alignment of multiple strings.
  • Week 3: Introduction to Hidden Markov Models
    • Learn what a Hidden Markov model is and how to find the most likely sequence of events given a collection of outcomes and limited information.
  • Week 4: Machine Learning in Sequence Alignment
    • Formulate sequence alignment using a Hidden Markov model, and then generalize this model in order to obtain even more accurate alignments.

Conditions:-

  • You should be good at English.
  • The course is free but if you want to Pursue a Verified Certificate to highlight the knowledge and skills you gain, you should pay $150.00.
  • The course needs 4 weeks with 8–10 hours of work per week.
  • Prerequisites: Basic knowledge of:
    • At least one programming language: loops, arrays, stacks, recursion.
    • Mathematics: proof by induction, proof by contradiction.

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Taught by

edX

Founded in 2012 by Harvard University and MIT, edX is a premier online learning platform and MOOC provider offering high-quality courses, professional certificates, and degrees from top-tier universities and institutions worldwide, with a mission to increase access to education. The platform enables over 86 million learners to acquire in-demand skills in fields like computer science, AI, and business, allowing them to audit courses for free or pay for verified certificates to boost their professional careers.

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