互联网年度工作总结之有前途的10个职业方向.doc

-精品合同推荐- 互联网年度工作总结之有前途的10个职业方向【导语】实际上Internet表示的意思是互联网，又称网际网路，根据音译也被叫做因特网、英特网，是网络与网络之间所串连成的庞大网络，这些网络以一组通用的协议相连，形成逻辑上的单一且巨大的全球化网络，在这个网络中有交换机、路由器等网络设备、各种不同的连接链路、种类繁多的服务器和数不尽的计算机、终端。使用互联网可以将信息瞬间发送到千里之外的人手中，它是信息社会的基础。以下是理的相关资料，希望帮助到您。 Based on current technology trends, here are 10 high-paying digital careers where the demand in the next decade will outstrip the supply of people with the necessary skills and training:基于目前科技发展的趋势，在未来十年，如下10个高收入技术类职业，对具备必要技能以及培训的人才需求很大。 1. 3D Printing3D打印Using open source design and 3D printing it is now possible to bring manufacturing to the desktop. The demand for craftsmen skilled in 3D Printing in the 2020s is going to be huge as on-shoring leads to the return of manufacturing to wealthy countries.开源设计和3D打印技术的运用让人们在桌子上就能制造东西。到21世纪20年代，在岸外包模式的流行使得生产回归发达国家，对能够操作3D打印技术的技师将有大量需求。 2. The Internet of Things物联网The Internet of Things is the interconnection via the Internet of computing devices embedded in everyday objects, enabling them to send and receive data. This includes everything from smartphones, coffee makers, washing machines, headphones, lamps, wearable devices and almost anything else you can think of.所谓物联网，是指通过在各种生活物品中植入计算设备构成计算网络，从而实现物与物的相互连接。这些生活物品无所不包，智能手机、咖啡机、洗衣机、耳机、台灯、可穿戴设备，还有其他任何你能想到的东西。 3. User Experience Design用户体验设计User Experience Design (often referred to as UX or Interaction Design) is the process of enhancing user satisfaction with a product by improving the usability, accessibility , and pleasure provided in the interaction with the product.用户体验设计（通常被称为UX或交互设计）是指通过增强用户使用产品时产品具有的可用性，可及程度和用户的愉悦感受，来提升用户对产品的满意程度的过程。 4. Digital Marketing数字营销With attention spans declining and information overload making advertising more challenging, digital marketing demands storytellers and content creators that also have technical skills like analytical ability and strategic business thinking.在当今信息超载，注意广度缩减的时代，广告业面临更多的挑战。数字营销需要会讲故事，会创造内涵，同时又具备数字分析、战略商务思维等技术才能的人才。 5. App Development应用开发With the average American now spending 3-4 hours a day on their smartphones, there is a huge demand for skilled app developer.美国人平均每天看手机的时间长达3-4个小时，这意味着对高技术应用开发人员的大量需求。 6. Robotics机器人学While robots are replacing manual labor and service-industry jobs, the new employment opportunities are for people to design, build and service the robots. While robotics technicians or robotics engineers involve skills that are not easily mastered, you can start laying a learning foundation to see if you have the aptitude to succeed in this growing industry.机器人取代了手工劳动者和服务行业从业者的工作，同时也为人提供了新的就业机会，即设计、制造和服务机器人。机器人技师或机器人工程师所要求的技术或许很难掌握，但你可以着手给自己打一个基础，说不定你能在这个日益兴盛的行业取得成功。 7. CyberSecurity网络安全The wars of the future will be fought in cyberspace. Cybersecurity is one of the fastest growing industries in the world and cybersecurity involves protecting networks, computers, programs and data from attack, damage or unauthorized access.网络空间将是未来战争的战场。网络安全是全球发展最迅猛的产业之一，主要涉及保护网络、计算机、程序和数据等免受攻击、破坏或未授权的入侵。 8. Data Science数据科学The new high-paid rock stars of the software engineering industry are data scientists. With so much data being accumulated, cutting edge companies need data scientists with both analytical and social skills to make sense of the data to optimize business processes.数据科学家是软件工程业的高薪新宠。行业的公司需要数据科学家对收集到的大量数据进行分析，他们需要同时具备数据分析能力和社会学技能，通过对数据的分析实现商务流程的化。 9. Artificial Intelligence人工智能Robots took the jobs of factory workers. Artificial Intelligence (AI) will take the jobs of office workers. The new jobs will be understanding how artificial intelligence can be applied to business processes and social challenges and managing new AI systems that work more efficiently than humans.机器人替代了工厂工人的工作。而人工智能则会替代办公室职员的工作。属于人类的新岗位将是设法在商务流程和社会挑战中运用人工智能， 并且研发出比人类的工作效率更高的新人工智能。 10. Deep Learning深度学习Whats behind the driverless cars? Artificial Intelligence, or more specifically a type of specialized AI called Deep Learning. It is part of a broader family of machine learning methods based on simulating neural networks and learning data representations, as opposed to task-specific algorithms.无人驾驶车的背后是什么？人工智能或者更确切的说，是一种叫做“深度学习”的特殊人工智能。“深度学习”是机器学习方法的一个分支，这种机器学习方法不同于目标导向的计算模式，而是基于对人类神经网络的模拟和计算机数据表示法的学习。