内容简介：Get your hands dirty to learn.The first concrete step that I took in my data science journey was registering to an online certificate. It was going smooth and easy. I was just following through and learning the basics. After some time, I started to think t
5 Reasons Why You Should Do Projects Instead of Collecting Data Science Certificates
Get your hands dirty to learn.
The first concrete step that I took in my data science journey was registering to an online certificate. It was going smooth and easy. I was just following through and learning the basics. After some time, I started to think that it was easy to be a data scientist. I would just get a few of these certificates and start looking for jobs. I did collect those certificates in no time. Then guess what?
Welcome to the real world!
Certificates are good at teaching you the basics. They get you familiar with the field of data science. However, they are definitely not a game changer.
It is worth noting that I’m talking about the certificates received by completing MOOC courses. The ones that require you to pass a comprehensive exam like AWS certificates are on some other page.
Going back to our discussion, I have listed my 5 reasons why you should work on projects rather than collecting numerous certificates.
1. Certificates do not offer enough “active learning”
Certificates do not challenge the learners. If you pay attention to the lectures and read through the materials, you can easily pass the graded exams. They don’t push you hard enough to actually make you absorb the topics. If you don’t think hard enough and push yourself, the information will stay in the short-term memory and be forgotten.
As stated in this article by Nick Dam, “changes in neural connections, which are fundamental for learning to take place in the brain, do not seem to occur when learning experiences are not active. Many research studies suggest that active engagement is a prerequisite for changes in the brain. Not surprisingly, just listening to a presentation or lecture will not lead to learning.”
Most of the time is spent on listening to lectures in MOOC courses. On the other hand, doing projects is a great example for active learning. They challenge you to actively engage in the entire process.
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算法概论
Sanjoy Dasgupta、Christos Papadimitriou、Umesh Vazirani / 钱枫 注、邹恒明 注 / 机械工业出版社 / 2009-1 / 55.00元
《算法概论(注释版)》源自加州大学伯克利分校和加州大学圣迭戈分校本科生的算法课讲义，以独特的视角展现了算法设计的精巧技术及魅力。在表达每一种技术时，强调每个算法背后的简洁数学思想，分析其时间和空间效率，运用与其他技术类比的方法来说明特征，并提供了大量实例。《算法概论(注释版)》以人类最古老的算法（算术运算）为起点，将各种算法中优美而有代表性的内容囊括书中，并以最前沿的理论（量子算法）结束，构成了较......一起来看看 《算法概论》 这本书的介绍吧!
