Search result for Master of applied data science Online Courses & Certifications
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Natural Language Processing and Capstone Assignment
by Dursun Delen , Julie Pai- 0.0
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Approx. 5 hours to complete
The Past, Present, and Future of Data Science I Future of Data Analytics The Past, Present, and Future of Data Science I The Past, Present, and Future of Data Science II The Past, Present, and Future of Data Science II Applications of natural language processing Future trends and possibilities in data science...
Spatial Data Science and Applications
by Joon Heo- 4.4
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Approx. 12 hours to complete
Based on such business trend, this course is designed to present a firm understanding of spatial data science to the learners, who would have a basic knowledge of data science and data analysis, and eventually to make their expertise differentiated from other nominal data scientists and data analysts. Solution Structures of Spatial Data Science Problems...
Applied Data Science for Data Analysts
by Kevin Coyle , Mark Roepke , Emma Freeman- 4.2
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Approx. 16 hours to complete
In this course, you will develop your data science skills while solving real-world problems. You'll work through the data science process to and use unsupervised learning to explore data, engineer and select meaningful features, and solve complex supervised learning problems using tree-based models. Review of Data Science Data Science Process vs....
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....
Managing, Describing, and Analyzing Data
by Wendy Martin- 4.4
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Approx. 17 hours to complete
In this course, you will learn the basics of understanding the data you have and why correctly classifying data is the first step to making correct decisions. This course 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....
Promote the Ethical Use of Data-Driven Technologies
by Renée Cummings , Aaron Hui , Megan Smith Branch , Eleanor 'Nell' Watson , Tania De Gasperis- 4.7
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Approx. 21 hours to complete
You will learn types of bias and common ethical theories and how they can be applied to emerging technology, and examine legal and ethical privacy concepts as they relate to technologies such as artificial intelligence, machine learning and data science fields. Benefits of Ethical Data Science Distinguish between artificial intelligence and data science concepts....
Introduction to High-Performance and Parallel Computing
by Shelley Knuth , Thomas Hauser- 3.4
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Approx. 18 hours to complete
This course introduces the fundamentals of high-performance and parallel computing. This course 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. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others....
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Computational Social Science Methods
by Martin Hilbert- 4.7
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Approx. 11 hours to complete
This course gives you an overview of the current opportunities and the omnipresent reach of computational social science. In short, all of them do social science by computational means. A Very Short History of Science A Very Simplistic Hierarchy of Science Example of Computational Social Science: Data Science Overview of Big Data...
Data Processing Using Python
by ZHANG Li- 4.2
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Approx. 29 hours to complete
Also, it discusses the fast, convenient and efficient data processing capacity of Python in humanities and social sciences fields like literature, sociology and journalism and science and engineering fields like mathematics and biology, in addition to business fields. 3 Data Clean of Data Exploration and Preprocessing 4 Data Transformation of Data Precessing...
AI Workflow: Business Priorities and Data Ingestion
by Mark J Grover , Ray Lopez, Ph.D.- 4.3
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Approx. 8 hours to complete
Know the advantages of carrying out data science using a structured process Explain where data science and data engineering have the most overlap in the AI workflow Explain the purpose of testing in data ingestion Know the initial steps that can be taken towards automation of data ingestion pipelines...
