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187 Algorithms Training Courses (Page 4)

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Introduction to Data Science

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Join the data revolution. Companies are searching for data scientists. This specialized field demands multiple skills not easy to obtain through conventional curricula. Introduce yourself to the basics of data science and leave ar…

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Machine Learning: Clustering & Retrieval

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Learning Outcomes: By the end of this course, you will be able to: -Create a document retrieval system using k-nearest neighbors. -Identify various similarity metrics for text data. -Reduce computations in k-nearest neighbor searc…

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Mastering the Software Engineering Interview

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You now know how to solve problems, write algorithms, and analyze solutions; and you have a wealth of tools (like data structures) at your disposal. You may now be ready for an internship or (possibly) an entry-level software engi…

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OpenCV with Python By Example

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OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we are getting more processing power to work with. Using this technology, we can seamlessly integrate our computer …

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Intelligent Machines: Perception, Learning, and Uncertainty

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The recorded lectures are from the Harvard School of Engineering and Applied Sciences course Computer Science 181. Prerequisites: CSCI E-207, CSCI E-250, and STAT E-150, or the equivalent. (4 credits)

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Data Structures and Algorithms

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The recorded lectures are from the Harvard School of Engineering and Applied Sciences course Computer Science 124. Prerequisites: CSCI E-119, or the equivalent and sound knowledge of discrete mathematics (CSCI E-120, or the equiva…

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Cloudera Developer Training for Apache Hadoop

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You Will Learn The core technologies of Hadoop How HDFS and MapReduce work How to develop MapReduce applications How to unit test MapReduce applications How to use MapReduce combiners, partitioners and the distributed cache Best p…

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Design and Analysis of Algorithms

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Course Description Course Overview: Introduction to fundamental techniques for designing and analyzing algorithms, including asymptotic ana…

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Customer Care & Billing: Rate Configuration

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The main rate tools, which are characteristics, bill factors, service quantity rules, register rules, algorithms, and eligibility criteria, will be introduced, discussed and configured in the course. On completion of this course, …

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Natural Language Processing

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In this class, you will learn fundamental algorithms and mathematical models for processing natural language, and how these can be used to …

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Algorithms, Part I

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Baker Professor of Computer Science at Princeton, where he was the founding chair of the Department of Computer Science. He received the Ph.D. degree from Stanford University, in 1975. Prof. Sedgewick also served on the faculty at…

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Parallel programming

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Throughout, we'll apply these concepts through several hands-on examples that analyze real-world data, such as popular algorithms like k-means clustering. Learning Outcomes. By the end of this course you will be able to: - reason …

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Probabilistic Graphical Models 1: Representation

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About this course: Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: …

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Probabilistic Graphical Models 3: Learning

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About this course: Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: …

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Natural Language Processing

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About this course: In this class, you will learn fundamental algorithms and mathematical models for processing natural language, and how these can be used to solve practical problems. Created by: Stanford University Taught by: Dan…