Search result for Courses taught by Mark J Grover
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AI Workflow: Data Analysis and Hypothesis Testing
by Mark J Grover , Ray Lopez, Ph.D.- 4.2
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Approx. 11 hours to complete
This is the second course in the IBM AI Enterprise Workflow Certification specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. By the end of this course you should be able to:...
AI Workflow: Enterprise Model Deployment
by Mark J Grover , Ray Lopez, Ph.D.- 4.2
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Approx. 9 hours to complete
This is the fifth course in the IBM AI Enterprise Workflow Certification specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. Apache Spark is a very commonly used framework for running machine learning models....
AI Workflow: Machine Learning, Visual Recognition and NLP
by Mark J Grover , Ray Lopez, Ph.D.- 4.5
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Approx. 14 hours to complete
This is the fourth course in the IBM AI Enterprise Workflow Certification specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. Out-of-the-box Watson models for natural language understanding and visual recognition will be used....
The AI Ladder: A Framework for Deploying AI in your Enterprise
by Mark J Grover , Ray Lopez, Ph.D.- 4.7
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Approx. 3 hours to complete
This course is intended for business and technical professionals involved in strategic decision-making focused on bringing AI into their enterprises. Through the use of a conceptual model called “The AI Ladder”, participants in this course will learn the requirements, terms and concepts associated with successfully developing and deploying AI solutions in their enterprises....
Supervised Machine Learning: Regression
by Mark J Grover , Miguel Maldonado- 4.7
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Approx. 11 hours to complete
This course introduces you to one of the main types of modelling families of supervised Machine Learning: Regression. You will learn how to train regression models to predict continuous outcomes and how to use error metrics to compare across different models. This course also walks you through best practices, including train and test splits, and regularization techniques....
Supervised Machine Learning: Classification
by Mark J Grover , Miguel Maldonado- 4.9
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Approx. 11 hours to complete
This course introduces you to one of the main types of modeling families of supervised Machine Learning: Classification. You will learn how to train predictive models to classify categorical outcomes and how to use error metrics to compare across different models. By the end of this course you should be able to:...
Unsupervised Machine Learning
by Mark J Grover , Miguel Maldonado- 4.8
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Approx. 9 hours to complete
This course introduces you to one of the main types of Machine Learning: Unsupervised Learning. You will learn how to find insights from data sets that do not have a target or labeled variable. You will learn several clustering and dimension reduction algorithms for unsupervised learning as well as how to select the algorithm that best suits your data....
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Learn online and earn valuable credentials from top universities like Yale, Michigan, Stanford, and leading companies like Google and IBM. Join Coursera for free and transform your career with degrees, certificates, Specializations, & MOOCs in data science, computer science, business, and dozens of other topics....
Course Definition & Meaning - Merriam-Webster
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course: [noun] the act or action of moving in a path from point to point....
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Free Online Courses. Our free online courses provide you with an affordable and flexible way to learn new skills and study new and emerging topics. Learn from Stanford instructors and industry experts at no cost to you....
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