Search result for Coursera algorithms Online Courses & Certifications
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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....
Practical Reinforcement Learning
by Pavel Shvechikov , Alexander Panin- 4.3
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Approx. 26 hours to complete
- state of the art RL algorithms...
IBM AI Engineering Professional Certificate
- 0.0
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To stay competitive, organizations need qualified AI engineers who use cutting-edge methods like machine learning algorithms and deep learning neural networks to provide data driven actionable intelligence for their businesses. Through hands-on projects, you’ll gain essential data science skills scaling machine learning algorithms on big data using Apache Spark....
Delivery Problem
by Alexander S. Kulikov- 4.7
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Approx. 14 hours to complete
We still don’t have provably efficient algorithms for this difficult computational problem and this is the essence of the P versus NP problem, the most important open question in Computer Science. Exact Algorithms Approximation Algorithms Approximation Algorithms...
Bayesian Methods for Machine Learning
by Daniil Polykovskiy , Alexander Novikov- 4.5
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Approx. 33 hours to complete
People apply Bayesian methods in many areas: from game development to drug discovery. They give superpowers to many machine learning algorithms: handling missing data, extracting much more information from small datasets. Bayesian methods also allow us to estimate uncertainty in predictions, which is a desirable feature for fields like medicine. Do you have technical problems?...
Data Analysis with Python
by Joseph Santarcangelo- 4.7
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Approx. 13 hours to complete
Then we will introduce you to another open-source library, scikit-learn, and we will use some of its machine learning algorithms to build smart models and make cool predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge....
Computer Science: Algorithms, Theory, and Machines
by Robert Sedgewick , Kevin Wayne- 4.7
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Approx. 20 hours to complete
It covers the second half of our book Computer Science: An Interdisciplinary Approach (the first half is covered in our Coursera course Computer Science: Programming with a Purpose, to be released in the fall of 2018). First, we introduce classic algorithms along with scientific techniques for evaluating performance, in the context of modern applications....
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Machine Learning with Python
by SAEED AGHABOZORGI , Joseph Santarcangelo- 4.7
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Approx. 21 hours to complete
If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge upon successful completion of the course....
Computer Science: Programming with a Purpose
by Robert Sedgewick , Kevin Wayne- 4.7
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Approx. 88 hours to complete
This course covers the first half of our book Computer Science: An Interdisciplinary Approach (the second half is covered in our Coursera course Computer Science: Algorithms, Theory, and Machines)....
Advanced Machine Learning and Signal Processing
by Romeo Kienzler , Nikolay Manchev- 4.5
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Approx. 27 hours to complete
If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge....
