challakarthik9/learning-ds-everyday

learning-DS-everyday

Data science can be an overwhelming field. Many people will tell you that you can't become a data scientist until you master the following: statistics, linear algebra, calculus, programming, databases, distributed computing, machine learning, visualization, experimental design, clustering, deep learning, natural language processing, and more. That's simply not true It’s not easy to break into a new field, especially one as complex and multi-faceted as data science. We’re living in a weird time where even the definition (and expectations) of data science changes from company to company. What a data scientist used to do, used to need to understand, and the types of companies that need to hire data scientists are in a state of rapid evolution.

Now i'll start contributing to open source organizations! Make some meaningful contributions to organizations on GitHub. GitHub has a section devoted to projects that are great for new contributors! You can search for projects that are tagged specifically for first-timers or are beginner-friendly.