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How to Self-Learn Data Science
A Project Based Approach to Get Started in Data Science
As someone who don’t hold a degree in data science, I am truly passionate about this field and decided to experiment on building my own curriculum to learn data science in spare time. I would like to share my experience and hope to bring some insights if you want to share the same journey.
Project-based learning is a good starting point for people already have some technical background, but also want to dive deeper into the building blocks of data science. A typical data science/machine learning project comprises the lifecycle — from defining the objectives, data preprocessing, exploratory data analysis, feature engineering, model implementation to model evaluation. Each phase requires different skillsets, including statistics, programming, SQL, data visualization, mathematics and business knowledge.
I highly recommend Kaggle as the platform to experiment with your data science projects and Medium as the platform to gain data science knowledge from professionals. With plenty of interesting datasets and a cloud based programming environment, you can easily get data source, code and notebooks from Kaggle for free. While several popular data science publications (e.g. Towards Data Science, Analytics Vidhya) from Medium allows you to learn from others…
