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Mary Sinaida Omukami
Mary Sinaida Omukami

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How to become a data scientist in 2023/24.

Who is a data scientist?

This is someone who uses data to understand and explain phenomena around them and help organizations make better decisions.
A data scientist has to have hard and soft skills. The hard skills include Python, R, SQL, statistics and math, data visualization, machine learning, big data and cloud computing. While the soft skills include communication, storytelling ,problem solving and critical thinking.

As a beginner you can follow the step highlighted below if you want to become a Data Science:

1. Learn how to code if you don't.

Traditionally, data science roles do require coding skills. Python and R are the most common languages used in the data field due to their versatility. Data is stored in data bases and SQL being a popular language so learning it would benefit one when they happen to interact with them.

2. Practice on your math and machine learning skills.

Math is an important part of data science because of machine learning algorithms and making insights. One would need to cover on areas of linear algebra, calculus and statistics. You'll will interact with probability, regression modelling, matrices and vectors so studying those topics could help you understand the real life data science applications better.

3.Understand databases.

Since data scientist work with data. Most organizations store their data in data bases. You will need to design, create, and interact with databases on most of the projects you will work on. It's important for a data scientist to have an understanding of data bases and also how to connect and interact with data by using programming languages like python.

4.Learn how to wrangle data, visualize it and make reports.

To make sense out of data for your understanding and others one needs to wrangle which involves cleaning and organizing of raw data into data that one can work with.
In order to present your data for others to understand your analysis you'll need to make good reports and visualization.

5.Do lot's of practice and get some experience.
Practice by working on projects and developing data science skills by solving real world problems. Take an internship to be able to showcase what you've learned and applied on your projects.

6.Engage with the tech community.
For those working in the field of data science, they can offer insights on how the industry is and how to maneuver. Through various resources like blogs, articles, webinars, and online courses.
Participate in challenges and also learn what is knew in your respective field.

Alternatively, there is the route of doing a degree or a post graduate degree on data science.

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