Sachin had reached a stagnated phase in his career as a Marketing Manager. Despite being a great performer, there was nothing that enticed him on his marketing job anymore. He wanted to desperately make a career change into something more challenging; something that could be a great turning point in his career. Sachin was aware of Data Science being touted as the hottest career of the 21st century, and the various mentions about the data scientist job role on social media, news websites, and job portals had fascinated him. He was good at math and numbers and also possessed excellent analytical skills as a marketing manager. However, he was not from an IT background and this deadened his spirit of becoming a data scientist.
Just like Sachin, many candidates might have this hesitance. However, this fear is far from reality. At times even very little inhibition and hesitance can create a wide gap between us and our dreams. So we suggest you put these fears to rest and look at things objectively.
Learning data science starts with a lot of key questions, including this one –
“Do I need to know programming to become a Data Scientist?” Another common one is “What are the pre-requisites to learn data science?” Understanding the pre-requisites to learn data science is a vast topic, but we’ll cover all you need to know about programming as a nice-to-have and not need-to-have skill to get started with data science.
A long-standing myth that many individuals believe is that data science is only for people who are programming experts. Though it is true that a number of programming geeks choose to pursue a career in data science, learning data science is not just reserved for only those with programming knowledge. There are many great enterprise data scientists who began their career in data science without any prior programming experience. We are here to debunk all the myths of the data science industry – and explore what’s really important to become a data scientist.
Are you sitting down in front of your PC? Great. I am going to tell you something that may shock you.
You don’t need to be an expert programmer to become a data scientist.
According to DJ Patil, the Chief Data Scientist of the United States, a “desire to go beneath the surface of a problem, find the questions at its heart, and distill them into a very clear set of hypotheses that can be tested” is a must-have for any aspiring data scientist.
The lack of programming skills should not prevent individuals from considering a career in data science. There has been an apprehension lately that for someone to become a data scientist, he/she must be a great programmer. This is just like saying that to swim in the sea, you must be a fish. There are several other creatures that can swim and are not fish. Any organization looking to hire a data scientist requires someone with a diverse skill set and not just programming.
No doubt, programming is an essential skill for a data scientist job but that does not mean that you have to be a die-hard programmer to pursue a career in data science. It is acknowledged by industry experts that anybody who is comfortable and understands the basics of programming such as loops, functions, if-else, and programming logic can become a successful data scientist. Being a good programmer is a highly preferred skill for a data scientist but not mandatory. Then, what about folks like Sachin who never learned to programme during their school days or graduation. Is there no way they can become data scientists?
With the demand for data scientists across the globe on a rapid rise and 97,000 available data science and analytics jobs in India alone, a lot of people are interested in becoming data scientists but do not have any idea about programming. We have a piece of good news for you. There is a way for non-IT experts also to become data scientists, irrespective of their level of programming skills. If you have the love for probability and statistics and are comfortable enough learning any new programming languages using the resources available on the Internet – you can become a “Data Scientist Superhero”.
A data scientist identifies a business problem, works on the given dataset, analyses it from different perspectives, build machine learning models to visualize and predict outcomes and weaves a story to convey the insights to the stakeholders. So, we can see that the job role of a data scientist involves mainly modeling skills, communication skills, business acumen, and analytical skills all of which rank above the technical programming skills.
The only important and mandatory skill that one must have to become a successful data scientist is the ability to analyze data and glean meaningful insights out of it. This is not to say that programming isn’t a useful data science skill to learn. Knowing how to write a Python or R script or understanding how SQL queries work will definitely help you in your data science career. However, the lack of programming skills should not put a full stop to starting a new career in data science.
What basic data science programming languages should I pick up first?
The programming skills you require depend on what area of analytics or data science you are likely to work on. For any help deciding on the ideal path within data science, I recommend talking to one of our career coaches who will help you make the right decision.
Many large multinational companies use SQL throughout their operations and adopt a data strategy requiring you to possess legacy skills such as SQL if you want to manage databases. You might also want to expand your SQL skills with a focus on other data skills such as collecting, storing, and managing data in case you want to do a lot more with the data you are collecting and you already have.
Tips for Non-Programmers Learning Data Science
- Learn to use GUI based tools
If you don’t love programming or are not an expert programmer, then the foremost thing that you can do is to master the usage of GUI tools. There are many GUI driven data science tools (starting with the humble Microsoft excel to sophisticated tools like Rattle, Auto-Weka, or Tableau) that rule out the programming aspect and provide a user-friendly interface that helps anyone with basic knowledge of algorithms. The tools are pretty simple to use to build high-quality machine learning models without coding. Most of these GUI tools are available for free and let you analyze and present data through graphs, charts, and other special graphics. One need not possess excellent programming abilities to effectively use these tools but rather having a knick-knack of visualization helps.
- Become a Great Story Teller
“Numbers have an important story to tell. They rely on you to give them a clear and convincing voice.” –Stephen Few
If you are of the thought that critical business decisions depend on data and other quantitative factors, you’re wrong. Even after a machine learning model is built and analysis is drafted by individuals experienced in programming, someone has to convey the outcomes to the stakeholders who neither understand the claptrap of statistical models or programming languages. There needs to be a story woven around the insights to persuade stakeholders faster. You can become that person with excellent storytelling skills even if you lack programming skills.
- Build your Credibility with Business Acumen
Are you an expert in insurance or have extensive experience working in the Retail industry? You have a reason to rejoice. You definitely have knowledge about the tricks and elaborateness of the business than any other expert programmer. If you are a skilled expert in any specific domain (Insurance, e-commerce, Retail, Healthcare, etc), then you will be a highly valued resource for any organization. No degree of expert programming knowledge can beat the business acumen in a specific domain for a long time. Make the best use of your domain experience and skills and become the data science magic wand.
Today, the success mantra to landing a top gig as a data scientist in any organization is, “ The More You Know, The Better It Is.”. Though organizations appreciate professionals with specialized knowledge in programming, they are more inclined towards hiring candidates who bring in a diverse skill set. A marketing manager with good business domain knowledge, excellent grasp of math and numbers, statistical knowledge, and extraordinary marketing skills will definitely be preferred over a candidate with only specialized expert programming skills. So, if you are non-programmer looking to pursue a data science career there are several reasons to rejoice even though you do not have specialized programming skills. Develop a diverse set of skills mentioned above to become a successful data scientist. Like I mentioned at the beginning of the article, to swim you need not necessarily be a fish. To become a great enterprise data scientist, you need not be a hard-core programmer.
When mapping out a rewarding career like a data scientist job, you should look for advice from industry experts or career coaches about knowledge, skill set, available job roles, and any other valuable information. Having gathered the required information estimate and create a timeline of what programming languages you aim to learn, and how to get there. Looking for a well-designed career path to learning data science? Check out Springboard’s Data Science Career Track that gives you all the basic data science skills required to get your foot through the data science door.