Online courses directory (19947)
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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 harvardx@harvard.edu and/or report your experience through the edX contact form.
Learn how to articulate your thoughts in a clear and concise manner that will allow your ideas to be better understood by your readers. Improve your business writing skill by learning to select and use appropriate formats for your audience, use the correct medium and adjust your writing style accordingly, as well as identify your objective and communicate it clearly.
The goal of this course is to review grammar and develop vocabulary building strategies to refine oral and written expression. Speaking and writing assignments are designed to expand communicative competence. Assignments are based on models and materials drawn from contemporary media (newspapers and magazines, television, Web). The models, materials, topics and assignments vary from semester to semester.
The goal of this course is to review grammar and develop vocabulary building strategies to refine oral and written expression. Speaking and writing assignments are designed to expand communicative competence. Assignments are based on models and materials drawn from contemporary media (newspapers and magazines, television, Web). The models, materials, topics and assignments vary from semester to semester.
The goal of this course is to review grammar and develop vocabulary building strategies to refine oral and written expression. Speaking and writing assignments are designed to expand communicative competence. Assignments are based on models and materials drawn from contemporary media (newspapers and magazines, television, Web). The models, materials, topics and assignments vary from semester to semester.
If you’re interested in data analysis and interpretation, then this is the data science course for you.
Enhanced throughput: Almost all recently manufactured laptops and desktops include multiple core CPUs. With R, it is very easy to obtain faster turnaround times for analyses by distributing tasks among the cores for concurrent execution. We will discuss how to use Bioconductor to simplify parallel computing for efficient, fault-tolerant, and reproducible high-performance analyses. This will be illustrated with common multicore architectures and Amazon’s EC2 infrastructure.
Enhanced interactivity: New approaches to programming with R and Bioconductor allow researchers to use the web browser as a highly dynamic interface for data interrogation and visualization. We will discuss how to create interactive reports that enable us to move beyond static tables and one-off graphics so that our analysis outputs can be transformed and explored in real time.
Enhanced reproducibility: New methods of virtualization of software environments, exemplified by the Docker ecosystem, are useful for achieving reproducible distributed analyses. The Docker Hub includes a considerable number of container images useful for important Bioconductor-based workflows, and we will illustrate how to use and extend these for sharable and reproducible analysis.
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 harvardx@harvard.edu and/or report your experience through the edX contact form.
Impara come utilizzare Highrise e tutte le sue funzioni. In questo video apprenderai le funzioni base del CRM.
Apply best practices to common types of machine learning problems, extract quantifiable data, and explore source tools.
An introduction to the math and processes to apply machine learning techniques to web data.
Ever wondered about the sacred scriptures that have sustained for millennia one of the oldest and most diverse religions of the world - Hinduism? Want to discover the lessons this history may offer mankind in the 21st century?
This religion course introduces the rich and diverse textual sources from which millions of Hindus have drawn religious inspiration for millennia. The Bhagavad Gita has offered philosophical insights to a number of modern thinkers. This course will introduce important passages from important Hindu sacred texts, their interpretations by moderns and will give you an opportunity to engage with them.
This course in part of the World Religions Through Their Scripture XSeries Program.
This class explores the political and aesthetic foundations of hip hop. Students trace the musical, corporeal, visual, spoken word, and literary manifestations of hip hop over its 30 year presence in the American cultural imagery. Students also investigate specific black cultural practices that have given rise to its various idioms. Students create material culture related to each thematic section of the course. Scheduled work in performance studio helps students understand how hip hop is created and assessed.
Learn how to comply with the duties, rights, and responsibilities of HIPAA, ARRA & HITECH.
By Jill Helms
Learn what it takes to get the best out of people and turn employees into your company champions
In this course Hurwitz explains to employers why they should hire veterans, and to veterans what they need to do to ente
This course explores artistic achievement in a culture that over the past century has engaged in constant and intense imaginative self-renewal. The class studies film, narrative (e.g., Márquez's One Hundred Years of Solitude), and poetry. Conducted in Spanish.
This course explores artistic achievement in a culture that over the past century has engaged in constant and intense imaginative self-renewal. The class studies film, narrative (e.g., Márquez's One Hundred Years of Solitude), and poetry. Conducted in Spanish.
Repercussions, causes and ideas.
A House Divided: The Road to Civil War — Discover how the issue of slavery came to dominate American politics, and how political leaders struggled and failed to resolve the growing crisis in the nation.
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