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188 Algorithms Training Courses (Page 4)

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Java Programming: Solving Problems with Software

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About this course: Learn to code in Java and improve your programming and problem-solving skills. You will learn to design algorithms as well as develop and debug programs. Using custom open-source classes, you will write programs…

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Biology Meets Programming: Bioinformatics for Beginners

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This course will cover algorithms for solving various biological problems along with a handful of programming challenges helping you implement these algorithms in Python. It offers a gently-paced introduction to our Bioinformatics…

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Data Mining Project

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This six-week long Project course of the Data Mining Specialization will allow you to apply the learned algorithms and techniques for data mining from the previous courses in the Specialization, including Pattern Discovery, Cluste…

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Introduction to Data Science

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Tour the basic techniques of data science, including both SQL and NoSQL solutions for massive data management (e.g., MapReduce and contemporaries), algorithms for data mining (e.g., clustering and association rule mining), and bas…

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Machine Learning: Clustering & Retrieval

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In this third case study, finding similar documents, you will examine similarity-based algorithms for retrieval. In this course, you will also examine structured representations for describing the documents in the corpus, includin…

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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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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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Participants should have programming experience; knowledge of Java is highly recommended. Understanding of common computer science concepts is a plus. Prior knowledge of Hadoop is not required. Hands-On Exercises Throughout the co…

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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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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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Natural Language Processing

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In the past decade, successful natural language processing applications have become part of our everyday experience, from spelling and grammar correction in word processors to machine translation on the web, from email spam detect…

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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: …