Most people believe that becoming a data scientist is hard. Why so? You must be acquainted with different soft and hard skills such as mathematics & statistics, programming, and storytelling as well as communication skills to become a data scientist.
Reports and studies believe that data science is one of the coolest fields to choose from in 2022. However, if there’s a demand for data scientists, getting jobs in the domain might not be easy. Also due to all the stories available out there on the internet, people are afraid to learn all the technical skills.
People often complain that if they aren’t good with mathematics and statistics, how can they become data scientists?
Well, this blog will help you gain proficiency with all three aspects, and you can make an informed decision.
Mathematics and Statistics
People often complain that they used to score fewer marks in mathematics and statistics in school. And if they couldn’t score good marks, how can they become data scientists?
However, scoring fewer marks in school can be because of two reasons: either your teacher wasn’t competent enough or you were not good at studying.
But how can you get better at Mathematics and Statistics? Some great online resources can help you with the same.
You can find great learning resources that can help you learn vector mathematics and vector addition intuitively. They will use great real-life examples such as a plane flying in a particular direction with some velocity, which is considered one of the vectors. The wind speed also has a direction and some speed which can be considered the second vector. The resultant direction of the plane is obtained by adding both vectors.
Even for other concepts like matrix multiplication, you can find other resources that include easy-to-understand examples, which make the learning process fun. Through those resources, you will realize that mathematics is fun to learn.
After that, you will also find other YouTube channels and resources that you can use for learning mathematics and statistics simply and intuitively.
We have found these resources extremely useful, and you can also refer to them for gaining proficiency with the subject.
Programming
Programming is another essential skill required to enter the data science industry. Programming empowers data analysis. Learning Python programming language is a popular first choice for many programmers in data analysis. Libraries like NumPy and Pandas are essential for data manipulation.
For the same, look for online resources that are useful to explain all the concepts simply and intuitively. You will find resources that cover all the concepts, right from the basics like Variables, Numbers, Strings, Lists, etc.
Once you learn the basics of Python programming, you can move toward advanced concepts such as iterators, generators, set and frozen sets, etc. This playlist helped me a lot in learning Python programming and
Valuable resources can guide you in the right direction. There are two types of people: left-brained people and right-brained people.
Left-brained people tend to be more analytical and methodical. On the other hand, right-brained people tend to be more creative and artistic. Therefore, it’s upon you to decide which side you would prefer to be at.
However, there is one essential thing that you must know now. In the data industry, you will often come across jargon, and you will be afraid of them. But you must know that jargons sound technical, but they aren’t. For a simple concept like data cleaning, you will get complex terms like data munging, etc.
Therefore, don’t repel the subject or industry just because you come across jargon.
Also, you have other options apart from becoming a data scientist. In the data industry, you can also become a data analyst or data engineer.
Data Engineer
If you are not very proficient with maths and statistics but have an edge with programming, you can opt for the role of a data engineer. If you think that you love details, you can prepare raw pipelines to turn data into actionable insights, you should opt to be a data engineer.
Data Analyst
On the contrary, if your maths, statistics, and programming skills are below average but you possess great domain knowledge, you can think of becoming a data analyst. A data analyst is always involved in number crunching and uses data to prepare insights for all the key stakeholders. Moreover, you will find plenty of online resources that can teach you all the essential skills required to be a data analyst.
So, these are the other two possibilities you can look forward to exploring.
To conclude, these are some essential skills and requirements for becoming a data scientist. The answer to the question of whether becoming a data scientist is hard lies in your dedication. If you are just interested in becoming a data scientist, you might find it hard. However, if you are committed to the process and are ready to put in your effort, you can become a data scientist. Especially with access to great resources, you can refer to structured material that helps you learn everything intuitively and effectively. For Readers!
