In the government work report last year and this year, artificial intelligence has been the focus of the government's top-level design. The "New Generation Artificial Intelligence Development Plan" issued by the State Council also shows that by 2020, the scale of my country's artificial intelligence core industry will exceed 150 billion yuan, driving the scale of related industries to exceed 1 trillion yuan. As the core driving force of the next round of industrial transformation, artificial intelligence is becoming a new driving force for economic development in China and the world.
Whether it is to improve innovation capabilities, in-depth integration of informatization and industrialization, or to promote breakthroughs in key areas and improve the international development level of manufacturing, artificial intelligence is inseparable from artificial intelligence. Artificial intelligence is an indispensable core technology for intelligent manufacturing.
The artificial intelligence talent market is seriously insufficient, and the salary has exceeded one million
According to IDC statistics, after two years, 80% of applications will be related to AI. However, affected by the serious shortage of professional talents, it is still difficult for artificial intelligence to achieve large-scale commercial landing in the industry.
According to Gartner's "2018 CIO Agenda Survey", only 4% of CIOs have implemented artificial intelligence, and 46% of CIOs have made relevant plans, and the commercial deployment of artificial intelligence has just begun. More statistics show that the global AI talent is estimated to be about 300,000 people, and the overall market demand is more than one million people.
With the increasingly hot prospects of the artificial intelligence industry and the serious shortage of related professional talents, the competition for artificial intelligence talents by enterprises has become increasingly fierce. According to the "2017 Spring Internet Talent Trend Report" released by BOSS Zhipin, the supply of talents for big data and artificial intelligence-related positions is seriously insufficient. Among them, the gap ratio of search algorithm engineers exceeds 50%, and the gap of deep learning alone is as high as 33.8%.
By sorting out the recruitment salaries of artificial intelligence-related positions, it is found that the annual salary of international giants such as Google China and Microsoft is more than 500,000 yuan, and some algorithm engineers even reach more than one million, and there are even more than 30 domestic companies targeting fresh graduates or even Offered a price of more than 300,000 yuan.
To this end, many industry insiders said that now is the best time to enter the artificial intelligence industry!
Five advantages of DLI to help you successfully embark on the road to artificial intelligence
There is a window of opportunity with huge temptation, and there are many people who want to learn, but it is not easy for most of my friends to successfully embark on the road of artificial intelligence. Many senior learners complained. They went to the website to collect free teaching videos from major websites. They recommended and bought many books, but less than one-third of them were actually read. It was a waste of time and inability to learn.
As everyone knows, if you want to do good work, you must first sharpen your tools. If you want to successfully become a talent in the field of artificial intelligence, you cannot do it without appropriate learning resources.
To this end, during the Global Artificial Intelligence Technology Conference (GAITC) from May 19th to May 20th, the conference, in conjunction with the NVIDIA Deep Learning Institute (DLI), launched a highly Authoritative, scientific and practical "deep learning" training courses. Through the two-hour course experiment, learners have the ideas and ability to use deep learning technology to explore and solve industry problems.
In response to many people's problems in learning artificial intelligence technology, such as not knowing how to get started, not knowing how to advance, lack of expert on-demand, difficult to understand the latest cutting-edge applications, lack of practical environment, etc., DLI's five core advantages help you easily set foot on artificial intelligence road.
Top artificial intelligence experts teach in person, and the courses cover all stages from introductory to advanced
NVIDIA Deep Learning Academy is a collaboration between NVIDIA and Google, Facebook, Amazon and other world-leading deep learning customers and partners, as well as senior experts in the field of deep learning, to provide developers with training on the latest artificial intelligence technologies. Relying on the world's most advanced deep learning research and exploration, the training content covers different stages from entry to advanced. Among them, the basic course adopts the reinforcement learning mode. Beginners can learn and practice based on the trained neural network. It is specially designed for students who want to learn the basics of deep learning. Last year, DLI trained more than 10,000 people worldwide.
Get hands-on with the complete workflow of deep learning
Traditional artificial intelligence teaching focuses on theory and research, but for developers or employers, training programs that can quickly get started and devoted to production are actually more needed. But operating under the guidance of a DLI instructor, you can experience the full workflow of deep learning, including data management, model design and training, application optimization, and deployment, through hands-on labs. For example, you will know how to utilize Deep Neural Networks (DNNs), especially Convolutional Neural Networks (CNN), in a deep learning workflow to solve real-world image classification problems with the NVIDIA DIGITS and MNIST handwritten datasets on the Caffe framework.
Practical-oriented, application-oriented for specific industries and specific scenarios
Many of DLI's courses combine the application of specific industry-specific scenarios. For example, in the medical and health courses, there are vertical application courses such as medical image analysis, leukocyte chromosome status analysis through radiomics, and genome analysis, which are specially aimed at a wide range of application scenarios. In the field of media and entertainment, learn how to use generative adversarial networks to create content, such as special effects in videos, movies, or advertisements. In the fields of medicine and robotics, one of the lab courses involves genomics.
No need to write code, excellent open source tools improve learning outcomes
Although there are many deep learning development frameworks on the market, learners often spend a lot of energy on the code debugging of the framework. DLI provides a super simple and easy-to-use deep learning platform tool DIGITS, the most advanced abstract encapsulation of the existing deep learning development framework. The platform allows you to easily implement tasks such as image classification, target detection, and segmentation based on deep learning models by simply modifying a few parameters, and display them in a graphical interface. At present, DIGITS can already support Caffe, Torch, Tensorflow, etc., and more deep learning frameworks will be supported in the future.
Specific groups of people, teach students in accordance with their aptitude
Although the target group of training is technical experts in vertical industries, if you are a senior technical manager of an enterprise and do not need to understand the specific code implementation, DLI also provides a one-hour quick training course for you, mainly to help you better understand AI and let you know more about AI. You know how AI can work in your business.
Currently, DLI has launched a series of more than 30 hours of training. The course content not only covers general basic knowledge such as generative adversarial networks, image processing, target detection, and neural network deployment, but also includes the development of AI applications in specific industries such as finance, medical care, robotics, and transportation.
"It's very difficult to find courses in deep learning applications and understand the latest technologies in universities now, which is why NVIDIA has established a deep learning academy. We hope to bring leading deep learning and AI technologies to the entire developer community", NVIDIA Greg Estes, vice president of developer programs, said so.
Specific training schedule
Students can start from zero basics, learn the latest AI framework, deep learning software and GPU technology, and can also practice the complete workflow of deep learning and complete a certain application task, so as to have the idea of using deep learning technology to explore and solve industry problems and ability.
Specifically, the course schedule and content are as follows:
schedule:
Part 1 Deep Learning Demystification and Applications Duration: 1 hour
Part 2 Image classification with open source software DIGITS without writing code Duration: 2 hours
Course Introduction:
●Deep learning secrets and applications
Level: Beginner | Prerequisites: None
Industry: All | Frameworks: Caffe, Theano, Torch
This lab will introduce the rapidly evolving GPU-accelerated deep learning technology. This course is designed for students who want to learn the basics of deep learning.
You will learn:
* Concepts of deep learning
* How advances in deep learning will enhance machine perception tasks, including visual perception and natural language capabilities
* How to choose the software framework that best suits your needs
After completing this lab, you will have a basic understanding of accelerated deep learning.
●No need to write code, realize image classification with open source software DIGITS
Level: Beginner | Prerequisites: None
Industry: All | Frameworks: Caffe
This lab will show you how to leverage Deep Neural Networks (DNNs), especially Convolutional Neural Networks (CNN), in a deep learning workflow to solve real-world image classification problems with the NVIDIA DIGITS and MNIST handwritten datasets on the Caffe framework .
You will learn:
* Build deep neural networks running on GPU
* Manage data preparation, model definition, model training and troubleshooting process
* Use validation data to test and try different strategies to improve model performance
After completing this lab, you will be able to use NVIDIA DIGITS to build, train, evaluate, and improve the accuracy of convolutional neural networks in your image classification applications.
Preparation before class:
●Open the NVIDIA Deep Learning Institute (DLI) course experiment website account: Register an account at https://nvlabs.qwiklab.com/.
●Bring a computer to participate in the training, and need to install IE 10 (or above), or Chrome 59 (or above) browser.
On the occasion of the Global Artificial Intelligence Technology Conference, the conference, in conjunction with the zero-based introductory course of deep learning offered by the NVIDIA Deep Learning Institute, will open the door to artificial intelligence technology for you. I wish you a smooth entry into the ranks of AI talents.
For enquiries, registration and more course information, please visit: https://www.bagevent.com/event/1227464?bag_track=oscbk