Search result for Examples of data manipulation Online Courses & Certifications
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Using Data to Provide Personalized Student Support
by Abelardo Pardo , Leah Macfadyen- 0.0
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3 Weeks
This course will benefit educational designers, learning technology managers, and academics that are interested in how to use data to guide the design and improvements of a learning experience. Technology has the ability to collect a large amount of data about how people participate in a learning experience. How can data help improve the overall quality of a learning experience?...
$99
Methods and Statistics in Social Science - Final Research Project
by Annemarie Zand Scholten- 4.3
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Approx. 13 hours to complete
The Final Research Project consists of a research study that you will perform in collaboration with fellow learners. Together you will formulate a research hypothesis and design, come up with operationalizations, create manipulation and measurement instruments, collect data, perform statistical analyses and document the results. Milestone 3 - Measurement and manipulation material...
Introduction to R Programming for Data Science
by Yan Luo- 4.8
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Approx. 10 hours to complete
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. You will begin the process of understanding common data structures, programming fundamentals and how to manipulate data all with the help of the R programming language....
Data Science and Machine Learning with R and Python
by Ankita khanna- 3
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6 hours on-demand video
Shape manipulation on Arrays,flatten the data set,reshape the data set,resize the array,split array,stacking of arrays,broadcasting,scalar on arrays,transpose function,inverse function on arrays using linalg function,sum of diagonal elements using trace. Shape manipulation on Arrays,flatten the data set,reshape the data set,resize the array,split array,stacking of arrays,broadcasting,scalar on arrays,transpose function,inverse function on arrays using linalg function,sum of diagonal elements using trace....
$12.99
Exploratory Data Analysis for Machine Learning
by Mark J Grover , Miguel Maldonado- 4.6
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Approx. 8 hours to complete
This first course in the IBM Machine Learning Professional Certificate introduces you to Machine Learning and the content of the professional certificate. In this course you will realize the importance of good, quality data. This course targets aspiring data scientists interested in acquiring hands-on experience with Machine Learning and Artificial Intelligence in a business setting....
Climate Adaptation for Human Health
by Kathryn Conlon- 4.5
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Approx. 19 hours to complete
In this course, you will learn why taking action to plan for and adapt to climate change is necessary for protecting human health, as well as what kinds of actions are most appropriate for a particular location and population. Role and Network of Adaptation Practitioners Informing Adaptation: Collecting Data for Adaptation...
Algorithms for Searching, Sorting, and Indexing
by Sriram Sankaranarayanan- 4.6
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Approx. 34 hours to complete
This course covers basics of algorithm design and analysis, as well as algorithms for sorting arrays, data structures such as priority queues, hash functions, and applications such as Bloom filters. Algorithms for Searching, Sorting, and Indexing can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform....
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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. You will learn how to get data into R from commonly used formats and harmonizing different kinds of datasets from different sources....
Data Visualization and Communication with Tableau
by Daniel Egger , Jana Schaich Borg- 4.7
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Approx. 25 hours to complete
One of the skills that characterizes great business data analysts is the ability to communicate practical implications of quantitative analyses to any kind of audience member. In this course you will learn how to become a master at communicating business-relevant implications of data analyses. Dynamic Data Manipulation and Presentation in Tableau...
A Crash Course in Causality: Inferring Causal Effects from Observational Data
by Jason A. Roy, Ph.D.- 4.7
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Approx. 18 hours to complete
Over a period of 5 weeks, you will learn how causal effects are defined, what assumptions about your data and models are necessary, and how to implement and interpret some popular statistical methods. Implement several types of causal inference methods (e. matching, instrumental variables, inverse probability of treatment weighting) Identify from DAGs sufficient sets of confounders...
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