High-Dimensional Data Analysis powered by edX –Online Program

Offered by: Harvard University

College credits:

Course length: 4 Weeks

Overview

If you’re interested in data analysis and interpretation, then this is the data science course for you. We start by learning the mathematical definition of distance and use this to motivate the use of the singular value decomposition (SVD) for dimension reduction and multi-dimensional scaling and its connection to principle component analysis. We will learn about the batch effect: the most challenging data analytical problem in genomics today and describe how the techniques can be used to detect and adjust for batch effects. Specifically, we will describe the principal component analysis and factor analysis and demonstrate how these concepts are applied to data visualization and data analysis of high-throughput experimental data.

Finally, we give a brief introduction to machine learning and apply it to high-throughput data. We describe the general idea behind clustering analysis and descript K-means and hierarchical clustering and demonstrate how these are used in genomics and describe prediction algorithms such as k-nearest neighbors along with the concepts of training sets, test sets, error rates and cross-validation.

Given the diversity in educational background of our students we have divided the series into seven parts. You can take the entire series or individual courses that interest you. If you are a statistician you should consider skipping the first two or three courses, similarly, if you are biologists you should consider skipping some of the introductory biology lectures. Note that the statistics and programming aspects of the class ramp up in difficulty relatively quickly across the first three courses. By the third course will be teaching advanced statistical concepts such as hierarchical models and by the fourth advanced software engineering skills, such as parallel computing and reproducible research concepts.

These courses make up 2 XSeries and are self-paced:

PH525.1x: Statistics and R for the Life Sciences

PH525.2x: Introduction to Linear Models and Matrix Algebra

PH525.3x: Statistical Inference and Modeling for High-throughput Experiments

PH525.4x: High-Dimensional Data Analysis

PH525.5x: Introduction to Bioconductor: annotation and analysis of genomes and genomic assays

PH525.6x: High-performance computing for reproducible genomics

PH525.7x: Case studies in functional genomics


This class was supported in part by NIH grant R25GM114818.

HarvardX requires individuals who enroll in its courses on edX to abide by the terms of the edX honor code. HarvardX will take appropriate corrective action in response to violations of the edX honor code, which may include dismissal from the HarvardX course; revocation of any certificates received for the HarvardX course; or other remedies as circumstances warrant. No refunds will be issued in the case of corrective action for such violations. Enrollees who are taking HarvardX courses as part of another program will also be governed by the academic policies of those programs.

HarvardX pursues the science of learning. By registering as an online learner in an HX course, you will also participate in research about learning. Read our research statement to learn more.

Harvard University and HarvardX are committed to maintaining a safe and healthy educational and work environment in which no member of the community is excluded from participation in, denied the benefits of, or subjected to discrimination or harassment in our program. All members of the HarvardX community are expected to abide by Harvard policies on nondiscrimination, including sexual harassment, and the edX Terms of Service. If you have any questions or concerns, please contact [email protected] and/or report your experience through the edX contact form.


The edX - Guild Experience:
All edX courses, MicroMasters and XSeries in partnership with Guild are offered as an enhanced program to promote successful completion of course and relevance to professional goals. The three-month program includes:
  • Full access to course & content components for extended time - though expected duration of courses vary, all students will have access to content for three months to ensure you can fit the course into your busy life
  • Credential upon completion of each course - credentials matter today, to help you stay current at work, learn a new skill, or expand your professional growth
  • Network of peers - connect with colleagues around the country in an easy-to-use forum to engage in professional and academic topics
  • Community coach - professional coach right at your fingertips. Interact with with a Master's degree coach who provides 1:1 and group coaching to help you stay on track  
  • Weekly events - webinars, study sessions and virtual group coaching to discuss student-driven topics 
  • Resource hub - videos, articles, tracking tools and content around relevant content like time management, leadership development and leveraging credentials at work

Curriculum

If you’re interested in data analysis and interpretation, then this is the data science course for you. We start by learning the mathematical definition of distance and use this to motivate the use of the singular value decomposition (SVD) for dimension reduction and multi-dimensional scaling and its connection to principle component analysis. We will learn about the batch effect: the most challenging data analytical problem in genomics today and describe how the techniques can be used to detect and adjust for batch effects. Specifically, we will describe the principal component analysis and factor analysis and demonstrate how these concepts are applied to data visualization and data analysis of high-throughput experimental data.

Finally, we give a brief introduction to machine learning and apply it to high-throughput data. We describe the general idea behind clustering analysis and descript K-means and hierarchical clustering and demonstrate how these are used in genomics and describe prediction algorithms such as k-nearest neighbors along with the concepts of training sets, test sets, error rates and cross-validation.

Given the diversity in educational background of our students we have divided the series into seven parts. You can take the entire series or individual courses that interest you. If you are a statistician you should consider skipping the first two or three courses, similarly, if you are biologists you should consider skipping some of the introductory biology lectures. Note that the statistics and programming aspects of the class ramp up in difficulty relatively quickly across the first three courses. By the third course will be teaching advanced statistical concepts such as hierarchical models and by the fourth advanced software engineering skills, such as parallel computing and reproducible research concepts.

These courses make up 2 XSeries and are self-paced:

PH525.1x: Statistics and R for the Life Sciences

PH525.2x: Introduction to Linear Models and Matrix Algebra

PH525.3x: Statistical Inference and Modeling for High-throughput Experiments

PH525.4x: High-Dimensional Data Analysis

PH525.5x: Introduction to Bioconductor: annotation and analysis of genomes and genomic assays

PH525.6x: High-performance computing for reproducible genomics

PH525.7x: Case studies in functional genomics


This class was supported in part by NIH grant R25GM114818.

HarvardX requires individuals who enroll in its courses on edX to abide by the terms of the edX honor code. HarvardX will take appropriate corrective action in response to violations of the edX honor code, which may include dismissal from the HarvardX course; revocation of any certificates received for the HarvardX course; or other remedies as circumstances warrant. No refunds will be issued in the case of corrective action for such violations. Enrollees who are taking HarvardX courses as part of another program will also be governed by the academic policies of those programs.

HarvardX pursues the science of learning. By registering as an online learner in an HX course, you will also participate in research about learning. Read our research statement to learn more.

Harvard University and HarvardX are committed to maintaining a safe and healthy educational and work environment in which no member of the community is excluded from participation in, denied the benefits of, or subjected to discrimination or harassment in our program. All members of the HarvardX community are expected to abide by Harvard policies on nondiscrimination, including sexual harassment, and the edX Terms of Service. If you have any questions or concerns, please contact [email protected] and/or report your experience through the edX contact form.

Cost and Schedule

Guild provides reduced cost education for working adults. We’ll help you have an affordable path to move your education forward.

Cost

Guild students may pay as little as 0-10% of the published cost of a course or program by taking advantage of:
  • Tuition assistance benefits from your employer 
  • Guild's tuition discount, and no out-of-state tuition costs.
Talk to your Guild Education Coach about whether this program is eligible for funding from your employer!

Schedule

edX courses are 100% online and asynchronous, which means you can log in when it's convenient for you - from almost any place in the world with an internet connection. You'll be able to move through the courses at your own pace. Stay a little longer where you need or want more time, and speed through the materials that you master quickly.

Frequently Asked Questions


Tell me more about Guild Education.
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Guild Education partners with employers to offer a variety of online classes, programs, and degrees from top-ranked universities that you can complete while working.

You will get support from a Guild advisor, who will help you find the right program, navigate the financial aid process, and provide you with personal college and career advising to help you navigate the college process from day one to graduation.

To give employees a variety of options, Guild partners with a consortium of universities and learning providers, including Brandman University, Western Governors University, Bellevue University, and StraighterLine, in addition to offering custom content. 

Benefits of partnering with Guild include:
  • A path to finish your degree or take graduate courses, at little to no cost
  • A personal college and career adviser to help you navigate programs and offerings
  • Online classes that allow you to work at your own pace
  • Relevant classes and programs designed to help you advance in your career
  • Credit recognition for past college credits and corporate credits towards your degrees

What are Guild's guiding principles?
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  • Students first: We're here to help you, and you come first in our world. In exchange, we expect you give your all and to support your fellow classmates.
  • We learn best by doing: Experimentation, learning by doing, feedback and reflection lay at the core of every learning experience with Guild.
  • Feedback makes us better, in fact, it’s a gift: Practice only makes perfect when we get feedback on how to improve.
  • Reflection is a need-to-have, not a nice-to-have: Reflection allows us to digest the learnings and feedback we’ve received.
  • Community matters: We’re all in this together and we expect all Guild members to appreciate the role we play in each other’s learning experience.