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189 Algorithms Training Courses (Page 4)

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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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Genomic Data Science and Clustering (Bioinformatics V)

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In the first half of the course, we will introduce algorithms for clustering a group of objects into a collection of clusters based on their similarity, a classic problem in data science, and see how these algorithms can be applie…

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Machine Learning for Data Analysis

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Machine learning is the process of developing, testing, and applying predictive algorithms to achieve this goal. Make sure to familiarize yourself with course 3 of this specialization before diving into these machine learning conc…

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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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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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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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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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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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Probabilistic Graphical Models 1: Representation

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These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. They are the basis for the state-of-the-art methods in a …

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Computer Vision: From 3D Reconstruction to Visual Recognition

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We will study the fundamental theories and important algorithms of computer vision together, starting from the analysis of 2D images, and culminating in the holistic understanding of a 3D scene. About the Course When a 3-dimension…

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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…

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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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Analytic Combinatorics, Part I

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This course teaches a calculus that enables precise quantitative predictions of large combinatorial structures. Part I covers generating fu…

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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…