How to Become a Data Scientist in 2023 | In a Short ..!
Data science has become an extremely popular topic in recent years, with more and more people looking to get into the field and master the craft.
To make things even more confusing, there’s no clear-cut road map that you can follow to get your data science knowledge from zero to hero. What are the key topics that you need to master? Which topics should you learn first? How long will it take before you see real results?
What is Data Science?
Data Science is the art and science of learning from and analyzing data. Data Science is an interdisciplinary field that uses techniques and theories from mathematics, statistics, computer science, information technology, pattern recognition and knowledge discovery, among others.
The goal of Data Science is to extract knowledge and insights from data. These insights are then used as the basis for further decision making or predictive modeling.
Data Science can be applied in both commercial and non-commercial settings as well as across many different industries including finance, healthcare, retail, education, and government.
Mathematics
Data Science is an exciting field that has been gaining more traction in the past few years, especially with the growing availability of data. The first step in becoming a Data Scientist is obtaining an undergraduate degree in mathematics, statistics, or computer science.
Students who have these degrees will have a lot of opportunities for employment after graduation.
It is also important for aspiring Data Scientists to learn more about data science and programming languages like Python and R.
Learning how to work with databases, process large amounts of data, and create visualizations will help give students the foundation they need when it comes time for graduate school.
Once you’re ready to enter graduate school, you’ll need solid experience either through internships or part-time jobs in order to be competitive against other applicants vying for spots at top universities.
How You Can Learn About Applied Statistics and Mathematics
In order to become a data scientist, you should start by learning about applied statistics and mathematics.
You can do this by taking courses or reading books on the subject. You may also want to take courses in programming, computer science and data analysis.
A degree is not necessary for becoming a data scientist, but it will help you get your foot in the door of companies that are hiring.
Start learning
Not all data scientists come from the same backgrounds. Some are computer programmers, some are statisticians, and some have more general STEM degrees. When you’re learning how to become a data scientist, think about what your background is and then start reading up on the skills you’ll need for your specific career path. Use these resources to learn:
- What kind of degree do I need? — How much math do I need? — What languages should I know? — How can I make the transition from another job into this one? — What’s my first step after graduation or certification?
Learning About Programming or Software Engineering
There are many paths that lead to becoming a data scientist and the one you should take will depend on your interests, strengths and passions.
Learning about programming or software engineering is an important part of preparing for this career because it is necessary for building machine learning models.
There are many ways you can learn programming such as teaching yourself through books or classes, attending hackathons or taking online courses. It is important to note that no matter which path you take there will be difficult parts but the journey will be worth it once you have succeeded.
Set some goals
I would like to become an intermediate data scientist by 2018. I would also like to be proficient in Python and SQL by 2020. I want to be able to analyze large sets of data by 2022. By the year 2023, I want my goals for the future of data science are twofold:
- I would like to be able to work with large sets of high-quality unstructured data;
- I want to publish at least one research paper in a peer-reviewed journal.
Choose your focus
There is no single road map for a career in data science. Some people work as statisticians or software engineers while others are content being a business analyst.
A major factor in choosing your focus will be your skill set — if you know a programming language, you might want to focus on the technical side of the field.
If you excel at understanding human behavior, then you may want to focus on marketing or economics-related positions.
If you’re interested in all aspects of the field, then consider working as a research scientist at an institute or university. You’ll likely need an advanced degree such as a PhD or MS for this type of position.
Conclusion
Data science is an evolving and expanding field that will only continue to grow. In the next ten years, data scientists will be more sought after than ever, but it can be hard to know where to start.
The best way to begin your journey towards becoming a data scientist is by learning the basics of python, R, and SQL.
Once you’re comfortable with these languages, you’ll want to look into acquiring foundational knowledge of machine learning algorithms.
Next, take some time and learn about how different types of data are stored and how they can be interpreted for insights.
