Below you can find the best algorithm courses that are currently available on the internet. They are updated regularly with the aim to keep all their characteristics like price, level of difficulty, and certificate quality up to date so you can make an informed decision about which is the best algorithm course for you. Feel free to use the filters below to sift through the entire database on Courseroot.
This course will teach you how to build models for natural language, audio, and other sequence data. Thanks to deep learning, sequence algorithms are working far better than just two years ago, and this is enabling numerous exciting applications in speech recognition, music synthesis, chatbots, machine translation, natural language understanding, and many others. You ... More information
Learn the basic concepts in theoretical computer science. Discover what they imply for solving tough computational challenges. This class teaches you about basic concepts in theoretical computer science -- such as NP-completeness -- and what they imply for solving tough algorithmic problems. Play Trailer Play Trailer... More information
Learn to create Deep Learning Algorithms in Python from two Machine Learning & Data Science experts. Templates included.
Sub-category: Data & Analytics
Language: English, Italian , 4 moreJapanese Portuguese Spanish Turkish
Normal price: $199.99
This course will give you solid foundations for developing, analyzing, and implementing parallel and locality-efficient algorithms. Offered at Georgia Tech as CS6220 The goal of this course is to give you solid foundations for developing, analyzing, and implementing parallel and locality-efficient algorithms. This course focuses on theoretical underpinnings. To give ... More information
Learn tools and techniques that will help you recognize when problems you encounter are intractable and when there an efficient solution. This class is offered as CS6505 at Georgia Tech where it is a part of the Online Masters Degree (OMS). Taking this course here will not earn credit towards the OMS degree.In this course, we will ask the big questions, ... More information
This class will give you an introduction to the design and analysis of algorithms, enabling you to analyze networks and discover how individuals are connected. Ever played the Kevin Bacon game? This class will show you how it works by giving you an introduction to the design and analysis of algorithms, enabling you to discover how individuals are connected. Play Tra... More information
Learn advanced techniques for designing algorithms and apply them to hard computational problems. This is a graduate-level course in the design and analysis of algorithms. We study techniques for the design of algorithms (such as dynamic programming) and algorithms for fundamental problems (such as fast Fourier transform or FFT).In addition, we study computational int...
In this course, we introduce the characteristics of medical data and associated data mining challenges on dealing with such data. We cover various algorithms and systems. Data science plays an important role in many industries. In facing massive amount of heterogeneous data, scalable machine learning and data mining algorithms and systems become extremely important fo... More information
Implement machine learning based strategies to make trading decisions using real-world data. This course introduces students to the real world challenges of implementing machine learning based trading strategies including the algorithmic steps from information gathering to market orders. The focus is on how to apply probabilistic machine learning approaches to trading... More information
The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming. We will learn a lot of theory: how to sort data and how it helps for searching; how to break a large problem into pieces and solve them recursively; when it ... More information
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 that access and transform images, websites, and other types of data. At the end of the course you will build a program that determines the popularity of diffe... More information
The primary topics in this part of the specialization are: asymptotic ("Big-oh") notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts).... More information
A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. In this course, we consider the common data structures that are used in various computational problems. You will learn how these data structures are implemented in different programming languages and will practice implementing them in... More information
How do Java programs deal with vast quantities of data? Many of the data structures and algorithms that work with introductory toy examples break when applications process real, large data sets. Efficiency is critical, but how do we achieve it, and how do we even measure it? This is an intermediate Java course. We recommend this course to learners who have previous ex... More information
Learn numpy , pandas , matplotlib , quantopian , finance , and more for algorithmic trading with Python!
Sub-category: Programming Languages
Language: English, Italian , 3 moreJapanese Portuguese Spanish
Normal price: $194.99
Generative art is all about using programming to generate artwork that is algorithmically defined and created. In this project-based class, you'll learn how to create your own series of patterns using generative art techniques and computer programming! What You'll Learn How to setup your programming environment for making generative artwork. An introduction to Process... More information
Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, ... More information
Want to make sense of the volumes of data you have collected? Need to incorporate data-driven decisions into your process? This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up... More information
If you have ever used a navigation service to find optimal route and estimate time to destination, you've used algorithms on graphs. Graphs arise in various real-world situations as there are road networks, computer networks and, most recently, social networks! If you're looking for the fastest time to get to work, cheapest way to connect set of computers into a netwo... More information