Search result for Applications in computer science Online Courses & Certifications
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Ubiquitous Learning and Instructional Technologies
by Dr William Cope , Dr Mary Kalantzis- 4.5
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Approx. 14 hours to complete
Areas addressed include: learning management systems, intelligent tutors, computer adaptive testing, gamification, simulations, learning in and through social media and peer interaction, universal design for learning, differentiated instruction systems, big data and learning analytics, attention monitoring, and affect-aware systems. The Not-So-New School: Individualization in Computer Adaptive Learning Computer Science Teaching Practices...
Convex Optimization
by Stephen Boyd , Henryk Blasinski- 0.0
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8 Weeks
This course concentrates on recognizing and solving convex optimization problems that arise in applications. This course concentrates on recognizing and solving convex optimization problems that arise in applications. Candidate in Computer Science at Stanford University. , summa cum laude, in Mathematics and Computer Science from the University of Pennsylvania and an M. in Computer Science from Stanford University....
Convex Optimization
by Stephen Boyd , Henryk Blasinski- 0.0
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8 Weeks
This course concentrates on recognizing and solving convex optimization problems that arise in applications. This course concentrates on recognizing and solving convex optimization problems that arise in applications. Candidate in Computer Science at Stanford University. , summa cum laude, in Mathematics and Computer Science from the University of Pennsylvania and an M. in Computer Science from Stanford University....
Computational Social Science Methods
by Martin Hilbert- 4.7
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Approx. 11 hours to complete
All of them study human behavior in order to shape it. In short, all of them do social science by computational means. In this last part, we take a bird’s-eye view on four main applications of CSS. Smaldino, from UC Merced, explains how computer simulation help us to untangle some of the mysteries of social emergence. Computational Social Science (CSS)...
Code Free Data Science
by Natasha Balac, Ph.D.- 4.3
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Approx. 14 hours to complete
The Code Free Data Science class is designed for learners seeking to gain or expand their knowledge in the area of Data Science. Participants will receive the basic training in effective predictive analytic approaches accompanying the growing discipline of Data Science without any programming requirements. Welcome to the Code Free Data Science Class...
Algorithms for Searching, Sorting, and Indexing
by Sriram Sankaranarayanan- 4.6
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Approx. 34 hours to complete
This course covers basics of algorithm design and analysis, as well as algorithms for sorting arrays, data structures such as priority queues, hash functions, and applications such as Bloom filters. Algorithms for Searching, Sorting, and Indexing can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform....
Foundations of Computer Science
by Aspen Olmsted- 4.8
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Approx. 16 hours to complete
In the first course in the sequence we will provide you with a solid foundation in the computer science topics that are important to understand when programming Visual Basic. In these courses you need to have access to a computer that is running Windows, macOS or Linux with the . Computer Hardware and Organization...
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MyCS: Computer Science for Beginners
by Zachary Dodds- 0.0
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6 Weeks
In this fun and creative introduction to computer science for learners of all ages, you'll learn and apply concepts by programming in Scratch. Lessons alternate between general exercises and assignments in Scratch, which offer a chance to both practice some basic concepts of computer programming and explore the many cool, creative, and useful applications of CS....
$50
Mathematical Thinking in Computer Science
by Alexander S. Kulikov , Michael Levin , Владимир Подольский- 4.4
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Approx. 40 hours to complete
Mathematical thinking is crucial in all areas of computer science: algorithms, bioinformatics, computer graphics, data science, machine learning, etc. In this course, we will learn the most important tools used in discrete mathematics: induction, recursion, logic, invariants, examples, optimality. Balls in Boxes Numbers in Tables Puzzle: Balls in Boxes Puzzle: Numbers in Boxes...
Python easy way
by Abhay Gadkari- 0.0
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7 hours on-demand video
Basics to introductory Data Science Data science part includes dataframe and its functions and one case study, Numpy, Visualization. Introduction to computer programming Database driven applications Introduction to data science...
$12.99
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