Data Science At The Intern level
As Data Science holds the grand title of the sexiest job of the decade, the idea of pursuing it becomes still more uneasy, more to that there is the viral notion of “Data Science is the toughest to build a career in”, but it is much more sorted to become a part of it. All you need to have is smartness and consistency in your efforts. Switching the career to data science at the intern level is not too hard. Let us know briefly about it down in the blog.
The majority of Data science aspirants think that 75% of the data scientist working hours gets digested by data cleaning and filtering processes. It’s true that before analyzing the dataset, you need to clean your analytical set of data free from any bugs and invaluable trashes. The amount of data being so vast, it’s true that you need to dig up large amounts of data for cleaning purposes. But plenty of ML and AI tools are present that can handle such data clearing processes in a very short period.
A Data Scientist is not obliged to know all the programming languages that have ever existed, people think a data scientist must know everything, but it is too fictitious to be true. You will be asked to have expert knowledge in at least 2-3 languages and on the tools frequently used in the field, get confident with absolute knowledge in those concepts that you choose in the beginning, further get into other concepts slowly and steadily. Make sure you will attain absolute knowledge of the languages and concepts you start learning. They act as the foundation for your knowledge of the field.
All the insights given further are provided directly by Data Scientists in various interviews, merging all of the information we can understand the responsibilities, environment, and requirements in Data Science.
Data Science for interns
Getting into the field of Data Science
When asked about how to get into the field easily, a data scientist told me that there are many ways to do that by coming up with any one of the important processes of the field. All that is required is the right knowledge upon whatever process you choose and must be swift in pacing up with the levels of the processes. In addition, there are Data science courses available in various colleges and in education centres that will help you know the fundamentals of the field and support you in finding a deserving company.
But keep in mind, not all courses are designed for you.
Will you be happy if your first data science job offers you a lower designation? Certainly, your answer will be ‘no.’ So even you are stepping into the intern level of data science, still choose such courses and learning modules that will help you to restrain your level of working experience and domain knowledge.
Another significant point you need to remember is that even if you are still targeting an internship when you go for the permanent data science job role, your domain experience will get counted. Therefore, an internship will be considered as an additional experience certification.
Being an intern in Data Science
Because of the high popularity the field has gained, it would make nervous even the brightest scholar on the pressure of being the best, but all one must do is relax because the Data Science activity happens in a team and everything an intern would need is the absolute knowledge on the language and tools they have preferred. A Data Scientist explained how daunting it will be, especially as an intern, because no matter how many different languages they learn, the insecurity of other person is more talented than I would haunt now and then, maybe this is because of the dynamic behaviour of the field. Every Data Scientist will be put in a team for the sole reason of it is impossible for any individual to be skilled in all the programming languages.
If we interpret the importance of teamwork in a Venn diagram, there will be intersection and overlapping of various languages one among another. This way, one pack of the team will be knowledgeable of all the required languages but be always humble towards what you do not know; social etiquette is also necessary. As an intern, your focus must be on following the patterns of how the activity works, analyze which language will be appropriate to learn because one’s journey of learning Data Science does not end when one gets a job, but it starts from there.
Keep in mind, data scientist job position demands an extreme sharp level of soft skills, like internal and external communication, convincing power, acute critical thinking, multi[platform collaboration skills, brainstorming skills, time management skill, reporting skill, etc.
The reason for such lengthy lists of soft skill requirements in data science is that you need to communicate and collaborate with every department of your organization. Because you need to collect data from each department, besides, your analytical output will help different organizational departments to solve their business-related roadblocks. But before they use your analytical output with the maximum possible degree of effectiveness, you’ll be the responsible pro to explain the insights of your analysis. Hence to need to master communication and other relevant soft skills.
Ideal education background to become a Data Scientist
This is another issue seen among the aspirants of being from an education background that is nowhere related to the technical field. Addressing this issue, a Data Scientist revealed that there are so many data scientists from different background fields like biology, physics, psychology, business and are still triumphing through their way.
So even if you are from a technical background, you will still have to study Data Science because the concepts of it are different from any other technical field, there are specific concepts that must be learnt and practised, also since it is dynamic, the requirements and essentials will be changing regularly, so it is necessary to be well-groomed before stepping into the field.
For the people of domain or education background different to it must find themselves a training centre that will ease them into the field by providing knowledge of the concepts right from its beginning. Getting into the field is easy, but for sustaining in it, you will have to pace up your game by handling the toughness and by updating yourself according to the trend in the air.
However, if you ask me which educational background is advantageous for a data science career shift, my answer will be, ‘Statistics and mathematics background.’ Yes, while lack of technical knowledge can be compensated by mastering data science tools and applications, the significance of the in-depth statistical concept can be altered with any tools.
So, even if you don’t come with a statistical or applied math background, you need to own the determination of learning statistics from the foundation level.
If formulas and sequential algorithms of statistics make you bore, then a data science career may not be the best-fit choice.
Useful information by a Data Scientist of sources where you can learn Data Science easy and efficiently:
Podcasts: Data Skeptic
Blogs: Data Science Central
Books: Top 7 Books Every Data Science Aspirants Should Read in 2021
Where can you find a highly credible data science course with an internship opportunity?
If you are serious about the data science career transition, you can join the IBM Certified Masters program in Data Science and AI by Learnbay.
At learnbay, you will get a complete guidance package for your data science career switch. All of your learning modules are specially designed, keeping your domain knowledge and working experience in mind. Even if you do not know how to code, we have specialized add-on modules for candidates like you.
We help you learn data science from scratch and make you a smart data scientist, not a hardworking one. We cover extensive training for all the tools and applications that will help you to provide the best-fit output at the minimum possible time.
After completing your course, we offer internship opportunities to experience real-world data science problems and brush up on your practical knowledge, making yourself comfortable dealing with your first data science job responsibilities with adequate confidence.
Want to enrol on our course. Book telephonic counselling here.