Data scientists play a dynamic role in an organization; no two days are the same for them. If you want to be a data scientist, your job will be to stay on your toes and always think out of the box. An organization contains heaps of data that they’ve collected over time in various formats and from multiple sources. And they want to hire someone whose main aim is to solve their problem. That is what makes your role as a data scientist so exciting and unique.
However, anything that gains momentum quickly becomes the talk of the town. And, the more people talk about it, the more myths and misconceptions pile up. Data Analytics and Sciences are one such domain that is on the rise, and along with it, associated myths are also increasing.
We’re going to debunk some of these misconceptions and myths revolving around the data science certification. Here are the myths regarding data science certifications that you should be aware of:
Myth #1: One needs to be an expert in statistics or have a Ph.D. in Mathematics, or at least a master’s in Statistics to pursue a career in Data Science.
If you are a person with a strong academic background in any of the fields mentioned above, data science as a career path would be a natural choice for you. You can choose to work in any of the roles as per your interests. However, having no such expertise does not mean that you won’t be successful in data science. There are roles such as Data Engineer and Data Analyst, where you don’t have to be Ramanujan or Aryabhata of maths and statistics.
You just need to have a basic understanding of business & data and skills related to excel and coding in python or spark or R. You can easily gain knowledge through courses available online. You can learn machine learning and stats concepts online and get data science certification and switch your career towards being a data scientist.
Myth #2: Data Science is all about analytical tools and coding
You don’t need to learn or work on analytical tools such as Kafka or SAS. Data science is not always about coding in languages such as R and Python. All you need is to have business acumen, problem-solving mindset, interpretation skills, ability to be creative with data, communication skills, and presentation skills. You will be working on tools and coding as a part of your job.
As a data scientist, you should be able to understand the problem related to business and innovatively solve it. You should also be good at presenting things and observations to non-experts so that you can understand the complexity of things very easily.
Myth #3: Learning Data Science can take years
Another myth that is associated with data science is that it takes time for a person to learn data science. However, you can learn without any hassles and be a data scientist with the help of courses available online. It is easy, take few months of your life, and you can pursue it while still doing your job. You can get your data science certifications from reputable institutions and reach new heights in your career.
Myth #4: You need to be a hardcore programmer to excel in data science
People have this false assumption that being a data scientist involves loads of code writing and algorithms. However, there is no significant coding required there. Most of the methods or algorithms are available ready-made; you just need to tweak a bit. However, to do these things, you need to have a logical bent of mind.
You should be aware of the myths and misconceptions mentioned above so that you can leave these misconceptions behind you and pursue a fruitful career in the field of data science.
Also, getting data science certification from reputable institutions such as Jigsaw academy will work as a cherry on the cake and will only enhance your skills. You can learn new skills languages, which will only get you to a better job position.