当前位置:网站首页>How to grow at work
How to grow at work
2022-04-23 06:06:00 【New ape and horse】
Catalog
2 Take the initiative to help others
6 The highest level of employment is to use the boss
What is the Dreyfus model ?
Dreyfus is a professional competency growth model , This model assumes that all professionals need to experience 5 It's a growth stage , Any skilled practitioner needs to experience Novice 、 Advanced novice 、 Competent person 、 The master 、 Experts 5 Stages .
What is a novice ?
Unable to work independently , Must be guided by experienced colleagues , Learn relevant skills , Finish the work . Skills refer to :
Tools : What tools are used for development 、 What framework is used for development , How to develop .
Collaboration : How to hold a meeting , How to write a weekly report , How to collaborate with colleagues .
Business : Know the business , Knowledge of business areas .
What is advanced novice ?
You don't need someone else to guide your work , Able to work independently , Lack of thinking about tools and frameworks , Can't solve new problems at work .
What is a competent person ?
In work and study , Understand and feel the principles behind the use of tools and frameworks , Initiative in work and study , Will try to solve new problems with new technologies .
What is a master ?
Have the ability to improve yourself , Take the initiative to learn and improve , Take the initiative to do a lot of reading and training . With reflective spirit and overall thinking , Can make a self breakthrough , Looking for a new way out . Proficient people know that the most important thing in work is not rules , But the understanding of the scene .
What is an expert ?
Experts combine past experience , Then form an intuition , They intuitively know how things should be done , Then use the most direct 、 The easiest way to solve the problem .
How to grow at work ?
1 Take responsibility
Only when you are responsible for the results , Under pressure , You will see through the essence of things , Will grasp the core and key of Technology , Can let you learn technology well , Use the technology , Take on the core technical responsibilities in the team and produce their own technical influence , And consolidate their technical position .
2 Take the initiative to help others
When team members encounter technical problems , Even if it's not your scope of work , It can also help them to solve problems , On the one hand, build your own technological influence , On the other hand , Get faster technology growth and insight by solving problems .
3 Maintain skills in practice
follow 1 The law of ten thousand hours ,1 Ten thousand hours programming time is not repeated programming , But constantly surpassing yourself , Self challenging training , Only in this way can we make continuous progress , In order to have higher technical ability and technical cognition .
4 Focus on problem scenarios
Technology is not everything , When we can solve problems without sophisticated tools and methods , It's not far from experts , That is, at this time, you will realize the method 、 technology 、 These tools are not the most complex , What's really complicated is the scene of the problem , Is how we understand the problem .
5 Don't think of a solution as the definition of a problem , And ignore the real problem to be solved
6 The highest level of employment is to use the boss
At work , If you encounter a jam , I can't push myself , You can ask your boss to help promote . When reporting risks to your boss , Please also give the corresponding solutions , Give multiple solutions at the same time , Just need the boss's consent . As long as the boss makes a decision , So the boss is standing with you , Help you solve the problem .
版权声明
本文为[New ape and horse]所创,转载请带上原文链接,感谢
https://yzsam.com/2022/04/202204220533487842.html
边栏推荐
- RedHat6之smb服务访问速度慢解决办法记录
- Fundamentals of digital image processing (Gonzalez) II: gray transformation and spatial filtering
- Pytorch learning record (XI): data enhancement, torchvision Explanation of various functions of transforms
- Software architecture design - software architecture style
- JDBC operation transaction
- 编写一个自己的 RedisTemplate
- Pytorch learning record (XII): learning rate attenuation + regularization
- Font shape `OMX/cmex/m/n‘ in size <10.53937> not available (Font) size <10.95> substituted.
- 治療TensorFlow後遺症——簡單例子記錄torch.utils.data.dataset.Dataset重寫時的圖片維度問題
- 编程记录——图片旋转函数scipy.ndimage.rotate()的简单使用和效果观察
猜你喜欢
图解numpy数组矩阵
Pytorch learning record (V): back propagation + gradient based optimizer (SGD, adagrad, rmsporp, Adam)
开发环境 EAS登录 license 许可修改
JDBC connection database
Denoising paper - [noise2void, cvpr19] noise2void learning denoising from single noise images
String notes
Understand the current commonly used encryption technology system (symmetric, asymmetric, information abstract, digital signature, digital certificate, public key system)
Comparative study paper - [Moco, cvpr2020] momentum contract for unsupervised visual representation learning
Practical operation - Nacos installation and configuration
線性代數第二章-矩陣及其運算
随机推荐
Chapter 4 of line generation - linear correlation of vector systems
图解numpy数组矩阵
解决报错:ImportError: IProgress not found. Please update jupyter and ipywidgets
Unsupervised denoising - [tmi2022] ISCL: dependent self cooperative learning for unpaired image denoising
Pytoch learning record (x): data preprocessing + batch normalization (BN)
DBCP usage
Class loading and classloader understanding
Fact final variable and final variable
Gaussian processes of sklearn
Manually delete registered services on Eureka
Chapter 3 of linear algebra - Elementary Transformation of matrix and system of linear equations
Reading of denoising paper - [ridnet, iccv19] real image denoising with feature attention
Rsync for file server backup
Pytorch learning record (IV): parameter initialization
图像恢复论文简记——Uformer: A General U-Shaped Transformer for Image Restoration
A general U-shaped transformer for image restoration
去噪论文阅读——[CVPR2022]Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spots
Pytorch learning record (III): structure of neural network + using sequential and module to define the model
JDBC connection database
Fundamentals of SQL: first knowledge of database and SQL - installation and basic introduction - Alibaba cloud Tianchi