Predictive analytics.
6+ Hours of Video Instruction This course is designed to bring a holistic, approachable, and best-practice-driven learning experience to predictive analytics. Overview: Updated and revamped, Predictive Analytics, 2nd Edition, provides comprehensive (yet easy-to-digest) coverage of business analytics...
Saved in:
| Online Access: |
Streaming Video (via O'Reilly/Safari) |
|---|---|
| Other Authors: | |
| Format: | Electronic Video |
| Language: | English |
| Published: |
[Place of publication not identified] :
Pearson,
[2022]
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| Edition: | Second edition. |
| Series: | LiveLessons (Boston, Massachusetts)
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| Subjects: |
MARC
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| 520 | |a 6+ Hours of Video Instruction This course is designed to bring a holistic, approachable, and best-practice-driven learning experience to predictive analytics. Overview: Updated and revamped, Predictive Analytics, 2nd Edition, provides comprehensive (yet easy-to-digest) coverage of business analytics concepts, applications, methods, and tools, with a special emphasis on predictive modeling and analysis. Over the course of the eight lessons, you will learn fundamental concepts, methods, and algorithms of business analytics and data mining, as well as their application areas and best practices. You also learn how to use a variety of software tools (both commercial as well as free/open source) and how to use those tools to discover knowledge from a wide variety of data sources. At the end of the course, you will not only know what predictive analytics is and what it can do for an organization but also develop basic skills to practice predictive analytics using numerous tools and platforms, most of which are free and open source. The course is designed to provide thorough coverage of the underlying concepts and definitions of predictive analytics in order to demystify the concepts and terminology of these popular evidence-based managerial decisioning trends and then help build hands-on skills with the most popular analytics tools and platforms using intuitive examples and data sets. Lesson Descriptions: Lesson 1: Introduction to Predictive Analytics Lesson 2: Introduction to Predictive Analytics and Data Mining Lesson 3: The Data Mining Process Lesson 4: Data and Methods in Data Mining Lesson 5: Data Mining Algorithms Lesson 6: Text Analytics and Text Mining Lesson 7: Big Data Analytics Lesson 8: Predictive Analytics Best Practices Skill Level: There is not a required minimum skill or knowledge level to take this course. Because of its holistic coverage, the course appeals to anyone (students and professionals) at any level of technical or managerial skill levels who is interested in learning about predictive analytics and its value propositions. Learn How To: The course provides thorough yet easy-to-digest coverage of predictive analytics concepts, theories, and best practices, followed by visual, intuitive, and highly practical hands-on illustrative examples using a variety of data sets and industry-leading software tools and platforms. Who Should Take This Course: This course is designed for anyone who is interested in learning about the best practices of predictive analytics and anyone who seeks to rapidly move into practical application of this popular technology with a minimal investment of time and resources. Course Requirements: There are no specific prerequisites or must-have requirements for this course. It is designed to attract and benefit anyone at any skill and managerial level who is interested in learning predictive analytics. About Pearson Video Training: Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Sams, and Que Topics include: IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more. Learn more about Pearson Video training at http://www.informit.com/video. | ||
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