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5 Things Every Data Scientists and Machine Learning Engineers should Know
This article is about the fundamental truth every data Scientist and Machine Learning Engineers should know irrespective of your level either as a beginner or expert even if you are an aspiring data scientist or machine learning engineer.
- Join a Data Science or Machine Learning Community
Joining a community as a Data Scientist or Machine Learning Engineer cannot be over emphasized. Joining a community gives you an edge over others because of the things that are being shared in that community or other activities. A quote from Martha Goedert says “If you want to go fast , go alone , if you want to go far, go together” speaks volume of the value of joining a community. There are a lot of data science and machine learning communities such as Kaggle, Zindi, DSN etc. Kaggle is the largest community for data scientist and machine learning in the world. They host competitions that usually attracts data scientists and machine learning engineers all over the world to compete to provide solutions for different industries in different sectors. This competitions provide opportunity for data scientist and machine learning engineers to practice to enhance their skills. This community also provide learning resources including short courses. Zindi do host competitions and provide learning resources. You can go to there website to join and you will not regret it especially if you are looking for opportunity to improve your skill or gain experience. While DSN is a community based in Africa. These are just a few of community out there. There are a lot LinkedIn , X and other platforms.
2. Build Personal Projects
This involves building personal projects for the the purpose of building your portfolio to show case your skills and to attract recruiters. It is not to enough to get certification, you must build something to demonstrate your skills. This is very essential if you are in a job search. It will tell recruiters what you are capable of doing.
3. The Act of Continuous Learning
The world of data science and machine learning demand that you learn continuously to fit in remain valuable in this field. Knowledge in this field are changing continuously. In fact knowledge generally are changing fast compare to many decades ago. You must develop and positioned yourself in such a way to have the ability to learn, unlearn and relearn to be more valuable in this century. Of cause , data scientists and machine engineers are not exempted. Therefore continue to learn to remain valuable in this field. Read data science and machine learning books, listen to podcast, watch you Tube videos, attend conferences, attend workshops, attend bootcamps and buy online courses
4. The Beauty of Domain Knowledge
AI can be virtually applied in all fields. Irrespectively of your background as a data scientist or machine learning engineer, you can use such knowledge to enhance you building of AI models. Let say you are building an AI model that will predict solar power energy from a given features, as a data scientist or machine learning engineer with engineering background can create new features from the existing features to optimize the model. This refers to feature engineering. Your background knowledge will also help you to have better understanding of the given features. Therefore your background knowledge is plus as a data scientist or machine learning engineer.
5. Do I Need a Degree, Master Degree or a PhD to Become a Data Scientist or Machine Learning Engineer?
This question has attracted different opinions from people. If you are going for research purpose as a data scientist or machine learning engineer you will need Master or PhD degree to accomplish this other than this you don’t really need a degree to become a data scientist or machine learning engineer. However you still need some level of knowledge of mathematics such as calculus to understand some in depth concept when study machine learning algorithms. This should not scared you as a beginner. Some of the mathematical concept were thought at high school or it is something you can learn yourself.
Thank you for reading. Any question , don’t hesitate to reach out to me
Reference
[1]www.blog.unmc.edu