Data Science is a rapidly growing field that combines statistics, mathematics, computer science and domain knowledge to extract insights from data. As a data scientist, skills are purposeful to solve complex problems and make better decisions in a variety of Industries.
To learn, it is very key to start with the basics. This includes learning about the different types of data, how to collect and clean data, and how to use programming languages to analyze data.
To know how to handle data, it's advisable to even begin with what is termed to be used by data analysts a lot i.e.: Understanding Excel, Spreadsheets and SQL which is a Structured Query Language for managing and manipulating data stored in databases.
The essential skills that then you build onto include learning a programming language in this case Python or R. Python is a general-purpose language well known for its simplicity whereas R is a statistical language.
From there, a visualization tool would help. Besides working with Python or even R for data manipulation, adding a set of tools such as Tableau, Power Bi is essential. These tools allow you to create interactive and visually appealing charts, graphs and dashboards to communicate your data insights.
Deep into data Science after getting comfortable with the essentials, it's when you dive into statistics as this is crucial for data mining. Here you get to learn about machine learning algorithms and how you can build predictive models. Basically, Machine learning would be allowing computers to learn from data without being explicitly programmed.
Advanced topics of a data Science career would include:
Deep Learning, Big data and Natural Language Processing.
Gaining hands-on experience with data science projects is the way to get to learn about this exciting field.
IT'S DATA ALLDAY, EVERYDAY
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