What are the essential skills to become a data scientist? And can you develop these skills through self-learning? According to MIT professor of computer science and engineering, Anant Agarwal, learning this skill without prior experience is possible and beneficial. He argues that the best way to learn data science is through self-learning. Learning data science skills is easier than you think. This article will establish that Data Science skills can be self-taught and give you tips for achieving your goals.
Opportunities for data science skills
The opportunities for data science skills are almost endless. Data scientist roles have a wide range of options and educational requirements. The median salary for data scientists in the United States is over $107,000 annually, with companies like Facebook (Meta) paying up to $155,000[1]. Data science and related jobs are also highly sought after by top employers. The demand means there will always be opportunities for people with these skills. If you are looking for new career opportunities, then data science could be an excellent option to explore.
How hard is it to learn data science?
The idea of learning data science without any previous experience has caught the attention of many people. It raises the question, how hard is it to learn this skill? Answer: It is easier than you think. Let’s understand why.
Firstly, there are two main types of skills for data science: technical and non-technical. Technical skills like python are easy to learn [2]. The only challenge is that they require more time and practice. Non-technical skills like design thinking, critical thinking or collaboration, are what you develop with experience.
Given the above information, it would be safe to say that someone with no prior experience or training in data science can learn this skill once they complete their education. However, it will take a little more patience and effort than someone who already has experience in other fields, as they have some transferable non-technical skills.
Can you teach yourself data science?
Self-learning is not a new concept. People with no prior background have learned software engineering and programming skills. This approach is the best way to pick up data science since many ideas need to be understood before analysing data.
Agarwal believes the best way to learn data science is through self-learning. If you are a motivated individual you want to learn data science, the best way is to get started. There are many free and paid resources available on the Internet.
Tips to guide self-studying data science
There are many ways for you to learn about data science. While the best way is through self-learning, it is helpful for you to access a data scientist and ask them questions, read blogs and articles, watch training videos, visit online courses, and check out textbooks. As a self-taught Data Scientist, these are my three tips to guide your studies.
1. You need to start. Anywhere – but start!
“Procrastination is the thief of time. Collar him.” ― Charles Dickens
The most important is for you to start. Data science is an essential field of study that is increasing. More and more people are becoming interested in the subject, making it vital for students to have good data science skills.
Understand your goals and find ways to help you reach those goals. You could take courses in math or statistics to learn how they can help. You could also take courses on Python and R programming as a way of getting started with data science without any prior experience. Follow tutorials on YouTube, and check out exciting work on Kaggle.
2. Learn a programming language
Before you decide to learn data science, you might pick up a programming language. Data science is a skill that requires programming languages such as Python, R, and SQL.
My recommendation is to learn one or two of these languages because it helps understand how data science works. You can choose either R or Python, but SQL is crucial. Don’t just watch the videos. Practice! The best way to learn any new skill is by doing.
Self-learning will allow you to learn at your own pace, find your voice and develop those skills, which will help you to be successful with data science.
3. Learn and understand the tools and skills you need
Learning platforms like DataCamp, Coursera and Udacity make it easy to learn the tools. You can use them as resources to become a data scientist.
The most important skill is the ability to think conceptually. You have to find patterns and use them in your work. You will also need to program because every algorithm requires some coding behind it.
Another essential skill when learning to be a data scientist is critical thinking. This skill helps you figure out what is best for your company by asking the right questions and analysing all possible solutions for your algorithm problems. To do this, all you have to do is ask yourself why certain things happen, what would happen if certain things happened, and what is likely to occur in the future.
Conclusion
Data science can be rewarding and is a highly sought after skill. It might not be easy to learn by yourself, but it is possible. Learning data science is a great way to start a career in data science. It’s important to know that you need to start, learn the tools and skills you need, to learn data science independently. Remember that learning data science is about the process, not necessarily about where you start, so feel free to design your programme to suit your learning needs.
Next week I will discuss the minimum viable tools (MVT) you need to learn to get your first Data Science job.
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See you next week. Thank you.
Bibliography
1. LinkedIn data.
2. Learning Data Science Skills Is Easier Than You Think.
3. 7 Learning Tips for Data Science Self-Study.