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Cómputo evolutivo

La computación evolutiva (evolutionary computation, EC), aplica la teoría de la evolución natural y la genética en la adaptación evolutiva de estructuras computacionales, proporcionando un medio alternativo para atacar problemas complejos en diversas áreas, como la ingeniería, economía, química, medicina y, porque no, las artes.

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• Self Paced
• الإسبانية

离散优化算法篇 Solving Algorithms for Discrete Optimization

优化是决策的一般形式，在我们的社会中很常见。它的应用包括从求解数独谜题到婚礼上的座次安排。同样的技术可以调度航班和机组成员，协调钢铁生产，组织铁矿从矿井到港口的运输。人力资源和材料管理上好的决策可以令企业提升上百万的盈利。同样的问题很多也在我们日常生活出现，成为决定每天送货路线，决定学校时间表，传输电力到家里等种种问题的一部分。除了它们的重要性，这些问题如果用传统的本科计算机科学方法难以求解。 这门课程为已经完成离散优化高阶篇的同学设计。 请看这门课程的宣传视频：http://www.cpr.cuhk.edu.hk/cutv/detail/988

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• Self Paced
• صيني

Data Structures and Algorithms

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• Self Paced
• صيني

TensorFlow for Beginners: Basic Binary Image Classification

The goal of this project is to introduce beginners to the basic concepts of machine learning using TensorFlow. The project will include, how to set up the tool and get started as well as understanding the fundamentals of machine learning/neural network model and its key concepts. Learning how to use TensorFlow for implementing machine learning algorithms, data preprocessing, supervised learning. Additionally, learners develop skills in evaluating and deploying machine learning models using TensorFlow.

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• Self Paced
• 4 ساعات
• الإنجليزية

Business Analytics Executive Overview

Businesses run on data, and data offers little value without analytics. The ability to process data to make predictions about the behavior of individuals or markets, to diagnose systems or situations, or to prescribe actions for people or processes drives business today. Increasingly many businesses are striving to become “data-driven”, proactively relying more on cold hard information and sophisticated algorithms than upon the gut instinct or slow reactions of humans. This course will focus on understanding key analytics concepts and the breadth of analytic possibilities.

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• Self Paced
• 17 ساعات
• الإنجليزية

The Economics of AI

The course introduces you to cutting-edge research in the economics of AI and the implications for economic growth and labor markets. We start by analyzing the nature of intelligence and information theory. Then we connect our analysis to modeling production and technological change in economics, and how these processes are affected by AI. Next we turn to how technological change drives aggregate economic growth, covering a range of scenarios including a potential growth singularity.

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• Self Paced
• 28 ساعات
• الإنجليزية

Algorithms for DNA Sequencing

We will learn computational methods -- algorithms and data structures -- for analyzing DNA sequencing data. We will learn a little about DNA, genomics, and how DNA sequencing is used. We will use Python to implement key algorithms and data structures and to analyze real genomes and DNA sequencing datasets.

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• Self Paced
• 12 ساعات
• الإنجليزية

C for Everyone: Structured Programming

In the new world we live in, coding is a universally valuable skill, whether you're a scientist, artist, or a humanist. Algorithms are everywhere, and we all have to understand how they work. The C language is particularly well suited as an introduction to coding: It's a tried-and-true language, and it allows you to understand computing processes at a deep level. You will also get an introduction to more advanced programming in C++ in the final module. This is a continuation of C for Everyone: Fundamentals, which you should take before beginning this course.

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• Self Paced
• 10 ساعات
• الإنجليزية

Software Security

This course we will explore the foundations of software security. We will consider important software vulnerabilities and attacks that exploit them -- such as buffer overflows, SQL injection, and session hijacking -- and we will consider defenses that prevent or mitigate these attacks, including advanced testing and program analysis techniques. Importantly, we take a "build security in" mentality, considering techniques at each phase of the development cycle that can be used to strengthen the security of software systems.

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• Self Paced
• 18 ساعات
• الإنجليزية

Big Data, Artificial Intelligence, and Ethics

This course gives you context and first-hand experience with the two major catalyzers of the computational science revolution: big data and artificial intelligence. With more than 99% of all mediated information in digital format and with 98% of the world population using digital technology, humanity produces an impressive digital footprint. In theory, this provides unprecedented opportunities to understand and shape society. In practice, the only way this information deluge can be processed is through using the same digital technologies that produced it.

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• Self Paced
• 12 ساعات
• الإنجليزية

Computational Neuroscience

This course provides an introduction to basic computational methods for understanding what nervous systems do and for determining how they function. We will explore the computational principles governing various aspects of vision, sensory-motor control, learning, and memory. Specific topics that will be covered include representation of information by spiking neurons, processing of information in neural networks, and algorithms for adaptation and learning.

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• Self Paced
• 26 ساعات
• الإنجليزية

C for Everyone: Programming Fundamentals

This course is for everyone. In the new world we live in, coding is a universally valuable skill, whether you're a scientist, artist, or a humanist. Algorithms are everywhere, and we all have to understand how they work. The C language is particularly well suited as an introduction to coding: It's a tried-and-true language, and it allows you to understand computing processes at a deep level. No prior knowledge of coding is needed for this course. We'll start at the beginning. The time estimated time commitment for this course is five hours a week for five weeks.

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• Self Paced
• 15 ساعات
• الإنجليزية

Computer Science: Programming with a Purpose

The basis for education in the last millennium was “reading, writing, and arithmetic;” now it is reading, writing, and computing. Learning to program is an essential part of the education of every student, not just in the sciences and engineering, but in the arts, social sciences, and humanities, as well. Beyond direct applications, it is the first step in understanding the nature of computer science’s undeniable impact on the modern world.

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• Self Paced
• 88 ساعات
• الإنجليزية

Machine Learning for All

Machine Learning, often called Artificial Intelligence or AI, is one of the most exciting areas of technology at the moment. We see daily news stories that herald new breakthroughs in facial recognition technology, self driving cars or computers that can have a conversation just like a real person. Machine Learning technology is set to revolutionise almost any area of human life and work, and so will affect all our lives, and so you are likely to want to find out more about it.

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• Self Paced
• 22 ساعات
• الإنجليزية

Visual Perception for Self-Driving Cars

Welcome to Visual Perception for Self-Driving Cars, the third course in University of Toronto’s Self-Driving Cars Specialization. This course will introduce you to the main perception tasks in autonomous driving, static and dynamic object detection, and will survey common computer vision methods for robotic perception. By the end of this course, you will be able to work with the pinhole camera model, perform intrinsic and extrinsic camera calibration, detect, describe and match image features and design your own convolutional neural networks.

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• Self Paced
• 31 ساعات
• الإنجليزية

Problem Solving Using Computational Thinking

Have you ever heard that computers "think"? Believe it or not, computers really do not think. Instead, they do exactly what we tell them to do. Programming is, "telling the computer what to do and how to do it." Before you can think about programming a computer, you need to work out exactly what it is you want to tell the computer to do. Thinking through problems this way is Computational Thinking. Computational Thinking allows us to take complex problems, understand what the problem is, and develop solutions.

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• Self Paced
• 11 ساعات
• الإنجليزية

Computational Thinking for Problem Solving

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 field of study to take this course. Many quantitative and data-centric problems can be solved using computational thinking and an understanding of computational thinking will give you a foundation for solving problems that have real-world, social impact.

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• Self Paced
• 18 ساعات
• الإنجليزية

Practical Machine Learning

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests.

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• Self Paced
• 9 ساعات
• الإنجليزية

Data-driven Astronomy

Science is undergoing a data explosion, and astronomy is leading the way. Modern telescopes produce terabytes of data per observation, and the simulations required to model our observable Universe push supercomputers to their limits. To analyse this data scientists need to be able to think computationally to solve problems. In this course you will investigate the challenges of working with large datasets: how to implement algorithms that work; how to use databases to manage your data; and how to learn from your data with machine learning tools.

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• Self Paced
• 24 ساعات
• الإنجليزية

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the DeepLearning.AI TensorFlow Developer Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning.

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• التعلم الذاتي
• 18 ساعات
• الإنجليزية

Algorithms, Data Collection, and Starting to Code

This course starts you on your journey learning about computational thinking and beginning C programming. If you’d like to explore how we can interact with the world in a rigorous, computational way, and would also like to start learning to program, this is the course for you! You may have heard lots of talk about computational thinking recently, but if you ask 10 different people what it is you’ll probably get 10 different answers. Rather than trying to define computational thinking, we’ll just say it’s a problem-solving process that includes lots of different components.

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• Self Paced
• 15 ساعات
• الإنجليزية

Natural Language Processing in TensorFlow

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In Course 3 of the DeepLearning.AI TensorFlow Developer Specialization, you will build natural language processing systems using TensorFlow. You will learn to process text, including tokenizing and representing sentences as vectors, so that they can be input to a neural network.

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• Self Paced
• 24 ساعات
• الإنجليزية

IT Security: Defense against the digital dark arts

This course covers a wide variety of IT security concepts, tools, and best practices. It introduces threats and attacks and the many ways they can show up. We’ll give you some background of encryption algorithms and how they’re used to safeguard data. Then, we’ll dive into the three As of information security: authentication, authorization, and accounting. We’ll also cover network security solutions, ranging from firewalls to Wifi encryption options.

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• Self Paced
• 32 ساعات
• الإنجليزية

Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

In the second course of the Deep Learning Specialization, you will open the deep learning black box to understand the processes that drive performance and generate good results systematically.

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• Self Paced
• 24 ساعات
• الإنجليزية

Sequences, Time Series and Prediction

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In this fourth course, you will learn how to build time series models in TensorFlow. You’ll first implement best practices to prepare time series data. You’ll also explore how RNNs and 1D ConvNets can be used for prediction.

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• Self Paced
• 23 ساعات
• الإنجليزية