How to transform AI engineer by ordinary programmer

Ai field talent is scarce, hot AI professional fresh annual salary 300,000 start, AI graduates basic need not find work, have been early booking companies.

Ai talent is how scarce. According to the Tencent Research Institute "global Artificial Intelligence Talent white Paper" report data, the current global AI field talent only about 300,000, the world 367 have AI research direction of the university, the annual graduate AI field students only about 20,000 people, this data even far from the domestic 5 million AI talent needs, Not to mention the global AI talent gap.

Not only is the shortage of talent, the market for AI Talent's white-hot thirst, the 2016 country from the strategic level will include AI and other High-tech personnel training to a new height. From the market, national government policies and other manifestations, it is not difficult to see: Now we are in the key bonus period of AI technology.

The vast majority of programmers are not AI trained, how to grasp the best new technology bonus period.

Today, we are going to share an advanced learning system advanced by an AI expert who has been lecturing to the teacher.

Specifically, this course:

Domestic entire network first from the beginning to the depth of the study of Intermediate Engineers teaching Program:

will help programmers, through three months (all weekend) focus on learning, complete 41 engineering experiments, 58 core high level knowledge points, getting started in transition to learn intermediate engineers, advanced to reach the general depth of learning engineer about 1 years level.

Responsible for the results of teaching guidance:

Over 85 points for final evaluation

Direct Insurance Employment

No work for a full refund within six months

A year after the annual salary is not 30w+, a full refund

Two test 75 points or more

Direct internal push

Actual combat projects include (but not only):

Full Convolution network image

CNN face recognition, Image style transformation

R-CNN Target Detection

Speech synthesis

Chinese chat robot

Rnn realizes composing robot

Confrontation learning realizes human face generation

Gcgan playing chess

Unreal Play games

Who is suitable to enroll in this course:

We will ensure that the students enrolled in the completion of the course of more than 80% of the successful transition rate, so will apply for the students to audit, suggested that students:

More than 1 years experience in programmer engineering

The mathematical basis should be in the undergraduate and above, the study of differential, linear algebra

Basic mastery of a computer language

Want to change, advanced depth study

0 enrollment of the risk to listen to the promise

Registration needs to apply for review, after the approval, support to listen to study for half a month, every time to study, if not satisfied, support the full return of the class

When is the class scheduled?

The course will commence on January 27, 2018, with live webcast scheduled for every Saturday Sunday.

For nearly 3 months, you will be under the leadership of the instructor to study all the actual combat projects, live after the playback of the video, the validity of support at any time to watch.

Learning on the way, encounter problems, have the exclusive students answer questions for you, have the exclusive class teacher to follow up the progress of your study.

Who is the instructor of the course?

High-lift

Data scientist/AI expert, now chief data scientist for a start-up company.

Former gathering time senior large data expert, is responsible for the gathering time direct seeding the deep study landing related research.

Jinshan software has been a large data architect.

Has many years of server-side development experience (years of working experience in Japan and Australia), years of large data architecture design and data analysis, processing experience. Good at traditional machine learning, depth learning, data modeling, relational database application, and large data framework applications.

"Vernacular large data and machine learning", "vernacular depth learning and TensorFlow", "Data Scientist Nurturance Handbook" and other book authors; rich experience in sharing and teaching, adept at imparting obscure technical skills in an understandable way. Has opened the "depth of study, from the beginning to the mastery of actual combat" series of professional courses, widely praised by students.

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