Algorithms Online Courses for University of Miami Students

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In this course you will learn what Artificial Intelligence (AI) is, explore use cases and applications of AI, understand AI concepts and terms like machine learning, deep learning and neural networks. You will be exposed to various issues and concerns surrounding AI such as ethics and bias, &...
The course will teach you how to develop deep learning models using Pytorch. The course will start with Pytorch\'s tensors and Automatic differentiation package. Then each section will cover different models starting off with fundamentals such as Linear Regression, and logistic/softmax...
This course can also be taken for academic credit as ECEA 5730, part of CU Boulder\'s Master of Science in Electrical Engineering degree. This course will provide you with a firm foundation in lithium-ion cell terminology and function and in battery-management-system requirements as needed by the...
This course dives into the basics of machine learning using an approachable, and well-known programming language, Python. In this course, we will be reviewing two main components: First, you will be learning about the purpose of Machine Learning and where it applies to the real world. Second, you...
What you\'ll achieve: In this project-centered course* you will build a modern computer system, from the ground up. We\'ll divide this fascinating journey into six hands-on projects that will take you from constructing elementary logic gates all the way through creating a fully functioning...
Computational thinking is the process of approaching a problem in a systematic manner and creating and expressing a solution such that it can be carried out by a computer. But you don\'t need to be a computer scientist to think like a computer scientist! In fact, we encourage students from any...
By the end of this course, learners will understand what computer vision is, as well as its mission of making computers see and interpret the world as humans do, by learning core concepts of the field and receiving an introduction to human vision capabilities. They are equipped to identify some...
Discrete Mathematics is the language of Computer Science. One needs to be fluent in it to work in many fields including data science, machine learning, and software engineering (it is not a coincidence that math puzzles are often used for interviews). We introduce you to this language through a...
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...
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...
Cloud computing systems today, whether open-source or used inside companies, are built using a common set of core techniques, algorithms, and design philosophies - all centered around distributed systems. Learn about such fundamental distributed computing \"concepts\" for cloud computing. Some of...
Discover the basic concepts of cluster analysis, and then study a set of typical clustering methodologies, algorithms, and applications. This includes partitioning methods such as k-means, hierarchical methods such as BIRCH, and density-based methods such as DBSCAN/OPTICS. Moreover, learn methods...
In this course, learners will complete several VBA projects. It is highly recommended that learners first take \"Excel/VBA for Creative Problem Solving, Part 1\" and \"Excel/VBA for Creative Problem Solving, Part 2\". This course builds off of skills learned in those two courses. This is a...
In this class you will learn the basic principles and tools used to process images and videos, and how to apply them in solving practical problems of commercial and scientific interests. Digital images and videos are everywhere these days - in thousands of scientific (e.g, astronomical,...
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...
A modern VLSI chip has a zillion parts - logic, control, memory, interconnect, etc. How do we design these complex chips? Answer: CAD software tools. Learn how to build thesA modern VLSI chip is a remarkably complex beast: billions of transistors, millions of logic gates deployed for computation...
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...
In this Specialization, Professional IQ: Preventing Solving Problems at Work, learners use real-world dilemmas and ethical problems experienced by professionals around the world to clarify and articulate their personal values as a foundation for the issues they face. Many successful people use...
>>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area...
Enterprises that seek to become proficient in advanced manufacturing must incorporate manufacturing management tools and integrate data throughout the supply chain to be successful. This course will make students aware of what a digitally connected enterprise is, as they learn about the...

Algorithms Online Courses for University of Miami Students

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