Recently I saw a lot of blogs and their topics are about “You cannot be a data scientist after finished Bootcamp to online courses”. I cannot say the writers are wrong or right, but I can say that if you don’t learn new skills after you finished boot camp or online courses, you will never be a data scientist.
Most data science courses contain basic knowledge and skills. The datasets we used to analyze are not big enough. Of course, it is impossible to learn everything about data science in six months or four months. However, if you are eager to become a data scientist, then you need to do the following things:
1. Review
It is a “must” thing to do — reviewing. Even though you are already skilled at some data science skills, but it is not possible that you 100% understand what you have learned. We can strengthen our foundation and also explore new discoveries of old knowledge. Because a solid foundation can build a great castle.
2. Ask
After googling or searching stack overflow you still cannot find the solution. Then you really need to ask someone for help! Many people rarely ask questions because of their strong self-esteem. In fact, if you keep a humble and can-do attitude to explore data science; if you really want to be a data scientist; if you really love this field, your self-esteem should not prevent you from exploring data science but help you become the person you want to be!
It is better to know some people you might not know who are data scientists or data engineers to expand your network. It is better to ask people who already have jobs and real-world experience. Not only you can learn from them and grow your network, but also those people potentially might help your career in the future.
3. Google, Stack Overflow, Online courses (Edx, Udemy, and Coursera, etc)
Most people google their questions, which is good. During this process, you are learning how to search the keywords and the exact answer you look for. Initially, I even did not know how to correctly search questions based on the keywords or terminology. Repeating this process gives me an ability to learn how to search the question efficiently.
Besides, after boot camps or online courses, you still need to learn more about data science. I have analyzed most projects via Jupyter notebook locally, and the datasets that the data science classes offered are limited, nevertheless, the real-world data is huge and cannot be manipulated locally. So what we need to learn? The answer is AWS and GCP. Nowadays, ‘cloud’ is a very popular and useful platform for big scaled datasets, and big data (big scaled datasets and big data are different, for more information please google it). Besides, It is better to earn some certificates to polish your resume.
Next, this point is very important and vital — to explore the companies you like. For example, you like 1800 flowers and you want to work there, then you need to visit their website to figure out their products and what kind of technologies they are currently using. Since 1800flowers.com is an e-commerce company, they might use Google Analytics to track the webpage metrics and consumer behavior. Bingo! The first thing first is to learn Google Analytics and to get the free certificate. Also, you can do some projects which are related to consumer behavior. Here is an example! The main purpose of this part is to discover a project which is more functional and can meet the companies need.
If you don’t know how to do? Google it!
4. Being Persistent
I have to say persistence and creativity are very objective. Sometimes they really depend on individuals. Here is my own story. I do not want to show off but I just want to share my experience and give you some positive power. I am a new mother and I spent a lot of time with my daughter. She sleeps around 10 pm every day and I only have time to review old knowledge and learn new skills from10 pm to 2 am. It happens every signal day. I try to memorize most fixed usages such as the common python libraries and built-in functions so that I can save my time to avoid repeating to search. Because I believe that I may not be a data scientist even though I make a lot of effects, but I definitely will not be a data scientist if I don’t want to learn new skills.
Sometimes we need some inspirations to make projects creative. Those inspirations could be from different sources — your life, the people you love, your friends, the company you like, the course you are taking, or a book etc.
For example, one day I visited two companies — UPS and BOA, because I ordered some products online and I wanted to know if the company already charged money and to track my products. I saw UPS and BOA have chatbots, which are very efficient but I still think that those chatbots still need to be improved. Then I got an idea — create an AI chatbot!! During this project I have learned a lot of skills that I did learn from school.
I am always optimistic, because I understand that the opportunities always go to those who are always prepared! Reviewing, asking, learning and being persistent will help us to pursue our dream job!
