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Here's a look at the latest data:
▲ (salary table) The latest data in 2018:
Python, big data, artificial intelligence practitioner salary
Why are salaries in the AI industry so high?
Whether it is scientific research institutes, business giants or start-ups, all walks of life are vigorously developing or introducing artificial intelligence. Due to insufficient reserves, there is now a huge gap in artificial intelligence talents.
According to the global AI talent distribution map released by LinkedIn today, China's current AI talent gap exceeds 50,000.
The supply of talents is in short supply, which leads to the rise of salaries for positions in the field.
Many people, especially fresh graduates and programmers who have just started working, want to stand out with their strength and resumes in this AI boom. However, many people are brushed off by HR at the first level, let alone technical.
I guess everyone knows why.
At present, there is no in-depth AI major for undergraduates in artificial intelligence. After all, these directions belong to high-level knowledge and require a certain foundation. Although due to the current AI boom and the strong demand for talents in this field in the industry, some universities have begun to offer AI and data science majors, but the skills these students have after graduation and the talent standards required by enterprises are not right. wait.
Like the artificial intelligence department of BAT; artificial intelligence research related work in colleges and universities; star startups, such as Four Little Dragons, SenseTime, Mining World, University of Science and Technology, etc. If you have only studied computer science, it is not so easy to enter these companies or institutions, because you do not have practical projects, and you do not have overall and in-depth control and learning of artificial intelligence.
And if your school background is not tough (Tsinghua University, Peking University, Chinese University of Science and Technology, etc.), don't expect offers from these companies.
But does that mean you have no chance?
Do not. At least you still have the right and ability to learn.
You can learn on your own or with an expert tutor in this area.
For the question of getting started with artificial intelligence, many students are eager to try it. In fact, the core of artificial intelligence is machine learning (Machine Learning) and deep learning. And their foundation is programming (Python/c++, etc.) and mathematics (advanced mathematics/linear algebra/probability theory, etc.).
另外，AI是逻辑算法的执行，底层架构是大数据。所以人工智能如何变厉害？就要喂它“吃”大数据。大数据就像人工智能的食物，跟人类一样，吃进去的食物愈新鲜、愈干净，人工智能就愈健康。
所以你想要进入这个领域，需要至少经过以下五个阶段的学习。
第一阶段：数学
高等数学／线性代数／概率论
第二阶段：编程
python工具库实战／python网络爬虫
第三阶段：机器学习
机器学习入门／机器学习提升
第四阶段：数据挖掘实战
数据挖掘入门／数据分析实战
第五阶段：深度学习
深度学习网络与框架／深度学习项目实战
几百个课时的学习是基本，但若想真正学明白，至少需要一些时间，当然根据每个人基础不同会有所差异，也不能排除你很短时间就能搞定。
如果你想投入 AI 的怀抱，但却苦于不知如何下手。而当你准备自学机器学习和深度学习时，又被外面那些贵的要命的培训课程吓得不行时，你还可以选择成为本次万门大学人工智能专业的学员。
划重点：纯免费
本次培训我们设置了300个课时，完全覆盖以上五个阶段。
专业课程特色：
（1）重基础／系统化
（2）从最小例子出发循序渐进的阐述
（3）具体课件代码逻辑清晰，内容详尽
（4）注重与前沿应用和科技的接轨，整合了很多人工智能研究者的心得
我们将一步步教你如何从基础小白进军AI，直接免去大几千几万的培训费。
由于课程开发精力有限，所以本次课程我们只招收300名学员。
如果你按照我们的课程步骤一步步扎实学习的话，相信你最终一定在人工智能方面小有成就，学完找到这类工作也会容易得多，而且薪水不会低。
为什么我们有信心开设这次人工智能专业学习课程？
一切归属于强大的导师团。为了开设人工智能课程，我们专门挖来了巴黎高师、以色列理工大学和美国数据应用学院的资深大咖来教授这门专业课程。
数学：
Tong Zhe: President of Wanmen University. In high school, he was recommended to the School of Physics of Peking University for the first place in the physics competition in Fujian Province. During the summer vacation of his junior year, he was admitted to the Ecole Normale Supérieure de Paris, France, and studied physics in France. After obtaining the M1 degree of the Paris Normal University + the Paris Normal University Master's degree, he returned to China and founded Wanmen University, which was recognized by 8 million users.
Python and artificial intelligence:
Xu Tie: PhD student in machine learning at the Technion-Israel Institute of Technology, master's degree in theoretical physics and complex systems at École Normale Supérieure, founder of cruiser, and author of papers in well-known neuroscience journals.
Data mining:
Data Application Academy (DAL) Lecturer: North America's premier Data Bootcamp core team. Chen Xiaoli-DAL, co-founder of the Data Application Academy (DAL), Ph.D. from the University of California, recommended to the Department of Mechanics of Peking University for mathematics competitions, and has many years of machine learning teaching experience.
▲Mr. Chen Xiaoli's offline get out of class "overcrowded"
You must know that in artificial intelligence training, the most difficult thing is to find suitable data. In the course, we cleverly used all kinds of public data and data generated by ourselves to solve the problem of insufficient data. The computing power is not easy to solve, but we will use the basic data of simple production, so that students can bypass the problem of computing power at the beginning, understand the core of machine learning and deep learning, and then cooperate with stronger computing power to easily solve the problem. difficult question. That's the beauty of these mentors.
They are among the top 1% in the field of artificial intelligence and big data. If you can learn the whole process, you still have the opportunity to get our big factory promotion opportunities. Major manufacturers such as Toyota and Huawei have a certain number of places. Many of our former students are from big factories, and you also have the opportunity to hook up with them.
One last thing. In 2017, the country's per capita disposable income was 25,974 yuan, ranking 69th in the world. You can find this data quickly on Baidu. By 2017, the penetration rate of higher education was only 38%. This is our society, and we really have a lot of opportunity.
hope you are like me
I also believe in the phrase "learning changes destiny".
See below for how to register for the course