Search result for Examples of data manipulation Online Courses & Certifications
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Procedural Terrain Generation with Unity
by Penny de Byl- 4.8
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15 hours on-demand video
Programming realistic environments with C# through the algorithmic manipulation of mesh and vegetation data. The creation of beautiful virtual terrains isn't just the domain of the artist, but also of the programmer. Contents and OverviewThe course begins by examining the nature of a landscape and the design considerations you should include in making decisions on structure, colour and vegetation....
$13.99
Core skill for data science: learn dplyr package in R
by Dunk Chawannut- 3.5
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42 mins on-demand video
Master data manipulation task in R which is one of the most important tasks in data science cycle This course focus mainly on dplyr package which is one of the most amazing package in R that will make you life a lot easier when dealing with data manipulation task....
$12.99
Introduction to Neurohacking In R
by Dr. Elizabeth Sweeney , Ciprian M. Crainiceanu , John Muschelli III- 4.6
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Approx. 18 hours to complete
org/) and its associated package to perform manipulation, processing, and analysis of neuroimaging data. By the end of this course, you will be able to: Data Structures and Operations Basic Data Manipulation Basic Data Manipulation with ANTsR Across-Visit Co-Registration of T1 Images Affine Registration of T1 to Template Nonlinear Registration of T1 to Template...
Big Data Science with the BD2K-LINCS Data Coordination and Integration Center
by Avi Ma’ayan, PhD- 4.8
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Approx. 9 hours to complete
The idea is to perturb different types of human cells with many different types of perturbations such as: drugs and other small molecules; genetic manipulations such as knockdown or overexpression of single genes; manipulation of the extracellular microenvironment conditions, for example, growing cells on different surfaces, and more. The Library of Integrated Network-based Cellular Signatures (LINCS) Program Overview...
Introduction to Clinical Data
by Nigam Shah , Steven Bagley , David Magnus- 4.6
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Approx. 12 hours to complete
We will explore the variety of clinical data collected during the delivery of healthcare. Review of key entities and the data they collect Examples of rule based electronic phenotype definitions Secondary Uses of Data Ethical use of data in healthcare decisions How to make use of data that may be inaccurate in systematic ways...
Framework for Data Collection and Analysis
by Frauke Kreuter, Ph.D. , Mariel Leonard- 4.2
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Approx. 10 hours to complete
With the help of various examples you will learn how to identify which data sources likely matches your research question, how to turn your research question into measurable pieces, and how to think about an analysis plan. Types of Data Examples of Found Data Visualizing the Data Generation Process Quality of Data...
Introduction to Applied Machine Learning
by Anna Koop- 4.7
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Approx. 7 hours to complete
This course is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this course will introduce you to problem definition and data preparation in a machine learning project. Features and transformations of raw data Sources of Training Data...
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Foundations: Data, Data, Everywhere
by Google Career CertificatesTop Instructor- 4.8
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Approx. 20 hours to complete
- Discover a wide variety of terms and concepts relevant to the role of a junior data analyst, such as the data life cycle and the data analysis process. - Evaluate the role of analytics in the data ecosystem. Self-Reflection: Business use of data Conduct an analytical thinking self assessment giving specific examples of the application of analytical thinking...
Introduction to Big Data
by Ilkay Altintas , Amarnath Gupta- 4.6
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Approx. 17 hours to complete
Interested in increasing your knowledge of the Big Data landscape? * Describe the Big Data landscape including examples of real world big data problems including the three key sources of Big Data: people, organizations, and sensors. * Provide an explanation of the architectural components and programming models used for scalable big data analysis....
The STATA OMNIBUS: Regression and Modelling with STATA
by F. Buscha- 4.4
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17 hours on-demand video
This is especially true once one engages with “real life” data sets that do not allow for easy “click-and-go” analysis, but require a deeper level of understanding of programme coding, data manipulation, output interpretation, output formatting and selecting the right kind of analytical methodology. The assumptions and requirements of Ordinary Least Squares (OLS) regression. Data manipulation in Stata...
$9.99
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