Data science is one of the most important in-demand skills nowadays. If you are reading this post, It is very likely that you are looking for resources to get into data science. In this blog, we will discuss different ways with which you can learn to code and acquire other essential skills to become a data scientist without having a data science or computer science degree.
What is a Data Scientist?
In simplest terms, a Data scientist is a person who has significant knowledge about how to find patterns and insights in a data-set. A data scientist is also responsible for presenting the patterns and insights in such a way that it can be used for assisting business critical decision making processes.
With every click on our phone or PC while surfing websites, we are creating a huge amount of data. Businesses collect this data and try to use them to derive insights for better decision making. Being a data scientist, you will be responsible for organizing the data in such a manner that it becomes useful for the business.
A data scientist is also responsible for communicating and explaining the data to team members and stakeholders through visuals and graphs. On the other hand, you will have to turn business problems provided by the team members and stakeholders into data questions so that the problems can be solved using data driven decision making.
Can you become a data scientist without a degree?
A BIG YES. Nowadays, Companies have started giving preference to skills over degrees. If you have the required skills to become a data scientist, you can easily get into it.Getting into data science requires you to have some knowledge in mathematics, statistics and programming languages. You will have to learn the basics of linear algebra, calculus, statistics, and probability before starting with data science. You can also learn python or R as a preferred programming language for data science.
Let us now discuss a few steps with which you can become a data scientist without a degree.
Steps to become a Data Scientist without a Degree
Learn the programming languages
Most of the data is stored in big databases that can be accessed using database management systems like MySQL. For that, you will have to learn Structured Query Language(SQL). You will also learn how to handle big data with technologies like Hadoop and Apache Spark. On the other hand, You will need a programming language like R or Python to process the data. So, before getting started with data science, you will need to be familiar with these technologies.
Start with basics of Data Science
After getting your hands dirty with database management systems and programming languages, you can start with the basics of data science. For this, you will need to study statistics, linear algebra, calculus, discrete mathematics and other basic concepts. Then, try to get into steps of data processing such as extracting the data and its cleaning so that it can be in usable form.
After becoming able to transform data into a usable form, you will need skills to visualize the data. At the same time, you will need a good knowledge of machine learning algorithms so that you can analyze the data and extract useful insights from it.
After that, you will need to have good storytelling skills. This will help you to explain the data, outcomes and predictions to the stakeholders and your teammates.
You can choose online certification courses from websites like Udemy, Coursera, edX, etc to learn all these skills.
Start working on projects
Once you have the required skills for a data scientist. You can start working on real data. This will help you in mastering your skills. You can also contribute to projects on websites like Kaggle and GitHub if you are able to solve real time problems. Doing good projects will brush up your skills. On the other hand, it will also help you in getting a good job as a data scientist.
Get an internship
Internships are one of the best ways to acquire knowledge while getting paid. You can apply for internships in data science roles and gain experience by working on real world projects. Internships will also help you to connect with other people working in the field of data science. You can ask for their guidance and help whenever you are not sure about which method to use on a data. This will help you understand the scenarios in a better way.
Build a portfolio
While you do projects, you should also maintain their GitHub repository so that you can show these projects to your employers in future. Alternatively, you can build a personal portfolio with details of all the projects that you have done. Sending your portfolio along with your application can help you get a job very quickly.
Participate in hackathons and contests
Nowadays, different companies organize hackathons in which you have to solve real world problems. You can participate in those hackathons. If you are able to win a hackathon, you can get a huge reward money. Companies even offer job opportunities for winners of the hackathons.
Hackathons can help you get better with your skills while earning money. Therefore, you should try to participate in the hackathons and contests.
Conclusion
Data science is an ocean. It requires all the skills that are required for a machine learning engineer, a data engineer, a data analyst, a database engineer, etc. You can start with a single profile like data analyst and keep acquiring the skills to broaden your area of expertise.
Always remember that mastering data science can take you years. But you can start with mastering subsets of it while you are in your job. On another note, Becoming a data scientist is absolutely possible if you have the hunger to learn new skills. You can learn concepts online and follow the advice discussed in this blog to get better on your skills.
Disclosure of Material Connection: Some of the links in the post above are “affiliate links.” This means if you click on the link and purchase the item, I will receive an affiliate commission. Regardless, I only recommend products or services I use personally and believe will add value to my readers.
