Search result for Data structures and algorithms Online Courses & Certifications
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Laboratorio di Programmazione
by Marco Lapegna- 0.0
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7 Weeks
You will learn how to select the best methodology for your project, how to develop and analyze basic algorithms for scientific calculation, and how to use the main calculation tools (hardware e software). Language of algorithms Data structures and control structures How to translate algorithms into programmes (Linux, C and Foltran)...
$60
数据结构与算法第一部分 | Data Structures and Algorithms Part 1
by 张铭 Ming Zhang- 0.0
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4 Weeks
The course also introduces students to fundamental data structures and classical algorithms used in more specialized courses,including Operating Systems, Software Engineering, Database Systems, CompilerPrinciples, Computer Graphics and Human Computer Interaction. Niklaus Wirth described the important and indivisible link between algorithms and data structure in his book, Algorithms + Data Structures = Programs....
Competitive Programming for Beginners
by Filipp Rukhovich , Ilia Stepanov , Oleg Hristenko , Vladislav Nevstruev- 0.0
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Approx. 153 hours to complete
After this course, you will learn what types of problems you will have to solve at the competitions, what is the effective program, how to estimate the algorithms efficiency, how to use basic algorithms and ideas during the problems solution. Linear Algorithms Integer data types structure. Basic and Extended Euclidean Algorithm...
Python 3: Deep Dive (Part 3 - Hash Maps)
by Fred Baptiste- 4.9
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20.5 hours on-demand video
Dictionaries, Sets, and Related Data Structures specialized dictionary structures such as OrderedDict and how it relates to the built-in Python3. how to serialize and deserialize dictionaries to JSON a brief introduction to some useful libraries such as JSONSchema, Marshmallow, PyYaml and Serpy functions and functional programming (recursion, *args, **kwargs, zip, map, sorted, any, all, etc)...
$18.99
Data Visualization and D3.js
by Ryan Orban , Chris Saden , Jonathan Dinu- 0.0
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Approx. 7 weeks
Learn by doing! You will analyze existing data visualization and create new ones to learn about the field. Learn about bias in the data visualization process and learn how to add context. lesson 6 Animation and Interaction Learn how to leverage animation and interaction to bring more data insights to your audience....
Free
Approximation Algorithms
by Mark de Berg- 4.7
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Approx. 15 hours to complete
The goal of this course is to become familiar with important algorithmic concepts and techniques needed to effectively deal with such problems. In order to successfully take this course, you should already have a basic knowledge of algorithms and mathematics. - Graph terminology, representations of graphs (adjacency lists and adjacency matrix), basic graph algorithms (BFS, DFS, topological sort, shortest paths)...
Become a Junior Java Software Developer
by Tim Short- 4.7
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8 hours on-demand video
Complete practical and conceptual Java programming course for beginners Get comfortable with controlling the flow of programsUnderstand and apply the core concepts of object-oriented programmingKnow the different data structures and practice traversing through arrays and collectionsMaster the common algorithms in computer scienceLearn topics conceptually and practically to ace your job interview...
$17.99
Advanced R Programming
by Roger D. Peng, PhD , Brooke Anderson- 4.3
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Approx. 18 hours to complete
This course covers advanced topics in R programming that are necessary for developing powerful, robust, and reusable data science tools. Upon completing this course you will be able to identify and abstract common data analysis tasks and to encapsulate them in user-facing functions. Control Structures Overview Debugging and Profiling Reuse existing data structures...
Unsupervised Learning
by Mark J Grover , Miguel Maldonado- 4.9
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Approx. 9 hours to complete
Describe and use common clustering and dimensionality-reduction algorithms To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Probability, and Statistics. Introduction to Unsupervised Learning and K Means...
Unsupervised Machine Learning
by Mark J Grover , Miguel Maldonado- 4.8
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Approx. 9 hours to complete
Describe and use common clustering and dimensionality-reduction algorithms To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Probability, and Statistics. Introduction to Unsupervised Learning and K Means...
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