Can One Start a Data Science Career with No Background or a Degree?June 28, 2021 2021-09-22 11:30
Can One Start a Data Science Career with No Background or a Degree?
Can One Start a Data Science Career with No Background or a Degree?
Data scientists are some of the most coveted professionals in the digital economy. Besides crunching data to extract insights, data scientists are crucial in artificial intelligence projects and advanced medical research. Even the private sector now hires data scientists to help the organization break down data for decision making.
Unfortunately, becoming a data scientist isn’t very easy. Although about 25% of data scientists have a Bachelor’s degree or less, the majority have at least a Master’s degree.
However, this isn’t a reason to give up. If you’re truly interested in becoming one, you can start a data science career with no background or degree in computer science. You just need to be prepared to work your way up the ladder.
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What is Data Science?
The simplest definition of data science is a multidisciplinary field concerned with breaking down data to uncover patterns and extract insight. It involves several processes, including collecting, storing, cleaning, and analyzing data.
Thus, a data scientist is a professional who collects, cleans, and analyzes large data sets to solve problems, run experiments, build algorithms, and present findings to stakeholders in an easy-to-understand manner.
You’ve likely heard about other data professionals such as data engineers, data miners, and data analysts. Data scientists is a broad term that covers all these subcategories. Thus, all data miners, data analysts, data engineers, etc., are data scientists.
What Do Data Scientists Do?
Data scientists use programming and mathematics to collect, clean, and explain data. Their primary responsibility is to use mathematical and statistical tools to model data and interpret the results to create actionable plans for companies and organizations.
In other words, they help organizations make sense of the massive amounts of data they collect each day.
A typical day in the life of a data scientist involves;
- Turning formal business problems into questions so that they can use data to solve the problems.
- Selecting the right tools for data analysis and modeling and applying the tools (and selected techniques such as machine learning and artificial intelligence) to find insight.
- Communicating technical data points to stakeholders and less technical team members through data visualization.
What Skills Do Data Scientists Need?
Even though it’s possible to start a data science career with no background or degree, it depends on many factors, including the hiring organization, the industry, and so forth. However, nearly all data scientists need the following skills.
- Math: You must be excellent at math if you want to become a data scientist. That’s because 90% of the data scientist’s work revolves around equations and algebra.
- Calculus: Data scientists should also be excellent at calculus, though you’re good to go as long as you fully understand the basics. Knowing derivatives is more important down the line.
- Linear algebra: We’ve already mentioned the need to be good with algebra. Specifically, you need to understand linear algebra perfectly.
- Statistics and probability: Finally, the best candidates for data science are also excellent statisticians. You must also be good with probability.
Data Science Programming Languages
Data scientists are essentially programmers. So, you need a strong background in programming. Some of the most important programming languages for data scientists include;
- Python: Python is a general-purpose programming language used for data manipulation and task automation. It is very common even among other computer science disciplines, including web design.
- R: R is a programming language created specifically for graphics tasks and statistical programming. It isn’t as common as Python. However, it’s critical for data scientists.
- SQL: The structured Query Language (SQL) is designed for managing data in relational database management systems. Data scientists use it to extract data for analytics and reporting purposes.
- Hadoop: Hadoop is a programming language per se. instead, it’s a suite of technologies used for managing data and executing programs in a cluster. A “cluster” in computer programming refers to a collection of computers that run within a data center.
- Spark: Data scientists also need a basic understanding of Spark – a system (rather than language) for writing parallel programs to run in clusters.
Finally, data scientists also need to good grasp of machine learning. Machine learning is a branch of artificial intelligence that seeks to create intelligent computer systems that can learn and adapt without following explicit instructions.
How to start a data science career with no background or degree in 2 easy steps
As we mentioned earlier, there are two broad ways to learn the required data science skills without a degree or background in computer science.
Self-teaching is hard, which is why most people don’t do it. However, it is also the most affordable way to break into data science without a degree. You’ll need to be extremely disciplined, though. More importantly, you must make sure you’re learning the right skills. You don’t want to waste time learning skills you don’t need in a data science role.
Fortunately, there are many free courses and resources online and offline for anyone wishing to learn data science. Some of the best resources to consider are;
- Introduction to Data Science from Alison
- Learn Python, R, and SQL for Data Science by Dataquest
- Free Data Science Bootcamp Prep from Flatiron School
Self-learning is very affordable and allows you at your pace. However, the major downside is that some hiring organizations may not recognize it.
Data Science Boot Camps
If you want a more formal way to break into data science without a degree, then attending a data science bootcamp is the way to go. Many data science bootcamps are organized in collaboration with hiring organizations thus guarantee a pathway into leading companies. The bootcamps are also typically hosted by industry experts following a strict curriculum.
The main challenge of data science bootcamps is cost. A typical data science bootcamp costs $5,000 to $20,000. Additionally, since the sessions have defined timelines, you may not grasp all the concepts fully by the end of the bootcamp.
Anyone who wishes to become a data scientist can pursue that dream even without a degree or background in computer science. As long as you have the will and time, you can begin self-teaching today or register for one of the many upcoming data science bootcamps.
Ready to get into data science? Sign up for our data science career track now and get your journey going.