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674 courses
Harvard University
Learn the principles guiding humanitarian response to modern emergencies, and the challenges faced in the field today.
Harvard University
Learn basic data visualization principles and how to apply them using ggplot2.
Harvard University
Learn simple graphical rules that allow you to use intuitive pictures to improve study design and data analysis for causal inference.
Lectures from Stanford graduate course CS230 taught by Andrew Ng. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and na…
Harvard University
Take your introductory knowledge of Python programming to the next level and learn how to use Python 3 for your research.
Harvard University
Learn inference and modeling, two of the most widely used statistical tools in data analysis.
Great Learning
This Data Science with Python course is designed to equip you with skills to work with Python Programming to achieve Data Science tasks. You will be knowledgeable about the concept of statistics in detail, followed by a case study demonstration. You will then understand data transformation, differe…
Harvard University
Learn skills and tools that support data science and reproducible research, to ensure you can trust your own research results, reproduce them yourself, and communicate them to others.
Great Learning
The Big Data course will introduce you to prominent big data tools, with a few demonstrations and case studies for each of these tools. The course shall focus on working with each of these tools for analytics purposes. It shall begin with a briefing on Hadoop, discussing the framework and its diffe…
Harvard University
Perform RNA-Seq, ChIP-Seq, and DNA methylation data analyses, using open source software, including R and Bioconductor.
Harvard University
A focus on several techniques that are widely used in the analysis of high-dimensional data.
Harvard University
The structure, annotation, normalization, and interpretation of genome scale assays.
Harvard University
This course is a variant of Harvard University's introduction to computer science, CS50, designed especially for lawyers (and law students).
Harvard University
Get the opportunity to see TinyML in practice. You will see examples of TinyML applications, and learn first-hand how to train these models for tiny applications such as keyword spotting, visual wake words, and gesture recognition.
Harvard University
A focus on the techniques commonly used to perform statistical inference on high throughput data.
Harvard University
In Leadership: Creating Public Value, learn how to face and meet today’s challenges and design a public value proposition that is both actionable and value creating.
Harvard University
An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences.
Harvard University
Learn advanced approaches to genomic visualization, reproducible analysis, data architecture, and exploration of cloud-scale consortium-generated genomic data.
Harvard University
Learn how to use R to implement linear regression, one of the most common statistical modeling approaches in data science.
Harvard University
Learn to use R programming to apply linear models to analyze data in life sciences.
