Search result for Trends in data science Online Courses & Certifications
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Databases and SQL for Data Science with Python
by Rav Ahuja , Hima Vasudevan- 4.7
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Approx. 18 hours to complete
Much of the world's data resides in databases. It is also intended to get you started with performing SQL access in a data science environment. The emphasis in this course is on hands-on and practical learning . As such, you will work with real databases, real data science tools, and real-world datasets. Welcome to SQL for Data Science...
Big Data, Artificial Intelligence, and Ethics
by Martin Hilbert- 4.6
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Approx. 12 hours to complete
This course gives you context and first-hand experience with the two major catalyzers of the computational science revolution: big data and artificial intelligence. Since an important part of this data is about ourselves, using algorithms in order to learn more about ourselves naturally leads to ethical questions. Big Data Overview Big Data Limitations...
Smart Materials: Microscale and Macroscale Approaches
by Yury Galyametdinov , Fedor Senatov , Artem Bezrukov- 4.9
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Approx. 17 hours to complete
Smart materials represent a cutting-edge global trend both in fundamental science and emerging technologies. An online course in smart materials will be of obvious interest for everyone who is interested in modern materials science and emerging trends in engineering, biotechnology, and medicine. We will highlight inspiring trends in applications of smart materials....
Importing Data in the Tidyverse
by Carrie Wright, PhD , Shannon Ellis, PhD , Stephanie Hicks, PhD , Roger D. Peng, PhD- 4.6
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Approx. 15 hours to complete
Getting data into your statistical analysis system can be one of the most challenging parts of any data science project. Data must be imported and harmonized into a coherent format before any insights can be obtained. Importing (and Exporting) Data in R Exporting Data from R Importing and Exporting Data Quiz...
Distributed Computing with Spark SQL
by Brooke Wenig , Conor Murphy- 4.5
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Approx. 14 hours to complete
Students will gain an understanding of the fundamentals of data analysis using SQL on Spark, setting the foundation for how to combine data with advanced analytics at scale and in production environments. The third module focuses on Engineering Data Pipelines including connecting to databases, schemas and data types, file formats, and writing reliable data. Continuing with Spark and Data Science...
eHealth: More than just an electronic record
by Tim Shaw- 4.6
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Approx. 12 hours to complete
- What kind of health data we are currently collecting and how it will transform healthcare in the future Guest presenters (listed in alphabetical order): Activity 5 - Learn about current trends in internet and communications technology (ICT) Patient reported data in practice Activity 8 - Learn about current trends in electronic data in healthcare...
The Data Science of Health Informatics
by Hadi H. K. Kharrazi, MD, Ph.D , Sam Meiselman- 4.7
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Approx. 10 hours to complete
Health data are notable for how many types there are, how complex they are, and how serious it is to get them straight. These data are used for treatment of the patient from whom they derive, but also for other uses. Introduction to Databases and Data Types Real World Applications of Data Science in Health Informatics...
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Wrangling Data in the Tidyverse
by Carrie Wright, PhD , Shannon Ellis, PhD , Stephanie Hicks, PhD , Roger D. Peng, PhD- 4.8
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Approx. 14 hours to complete
Data never arrive in the condition that you need them in order to do effective data analysis. The key goal in data wrangling is transforming non-tidy data into tidy data. Investing the time to learn these data wrangling techniques will make your analyses more efficient, more reproducible, and more understandable to your data science team....
Introduction to R Programming for Data Science
by Yan Luo- 4.8
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Approx. 10 hours to complete
When working in the data science field you will definitely become acquainted with the R language and the role it plays in data analysis. This course introduces you to the basics of the R language such as data types, techniques for manipulation, and how to implement fundamental programming tasks. Welcome to Introduction to R Programming for Data Science...
Studying Cities: Social Science Methods for Urban Research
by Laura Neijenhuis , Jan Fransen , Dorcas Nthoki , Rick Wolff , Maria Zwanenburg- 4.7
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Approx. 7 hours to complete
Are you looking to learn more about how to conduct scientific research, specifically in an urban or local context? Then you have found the right course: Studying Cities: Social Science Methods for Urban Research by the Institute for Housing and Urban Development Studies (IHS), Erasmus University Rotterdam. Introduction to Studying Cities: Social Science Methods for Urban Research...
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