Data Science Training in Bangalore

Gathering, analysing and solving a problem with the help of data and algorithms is the crude definition of data science. Just like any other branch of science, Data Science heavily consists of experiments, research and ground breaking findings. It is the intersection between Mathematics & Computer Science and given the IT boom the application of data science in today’s tech heavy world is endless. You can be sure that some of the major challenging problems in e-commerce, pharmaceuticals, banking, logistics, medicine, astrophysics etc. are being solved with the help of data science.

Turning award winner Jim Gray famously described Data Science as the "fourth paradigm of Science" with empirical, theoretical and computational being the first three.

That being said, now you may ask "What do you call the practitioners of this branch of science?" Well, just like the practitioners of physics are called physicists the practitioner of data science are called data scientists. A Data scientist is the person who asks the right question and have the right tools to solve a complex problem with the help of data. A data scientist assumes many roles in the course of solving a problem and toggles between those roles effortlessly. Given the application, challenge, high pay and demand there is no doubt that Data scientist has been coined as the sexiest job of 21st century.

A Data Scientist is a qualitative thinker and have mastered at least one programming language for crunching the data and knows one or more languages to mine the data out of the system. A data scientist’s core skill is his analytical thinking and the way he approaches a problem. He could break a complex problem in smaller chunks and can look at a single problem while shifting the paradigm so that no aspect of the problem remains unturned or untouched. And finally, a data scientist is skilled in devising strategies from the gathered observation while justifying those strategies with data and communicate them in ways that can be easily digested. Just like a great Storyteller the data scientist projects his work like a movie which is engaging at multiple levels and delivers a message which is understood and applied by the stake holder.

Although a certification adds value to your resume but some good capstone projects and an in-depth knowledge of the subject trumps any certification. So it would be fair to say that having certification is not a game changer if you can’t back that up with a knowledge and hands on experience. A recruiter would rather look for projects and experience to assess your skills as a data scientist and not for a certificate whose credibility on the rigorousness and content are questionable. It just does not make any sense for a recruiter to blindly believe that a certification can bypass knowledge that need to weigh before coming to a conclusion.

If you are a fresher an in depth knowledge of the projects that you have put in your resume and the link to your GitHub account should suffice the need, and if you’re an experience personal then in addition to aforementioned requirements you would be assessed on your domain and industry experience. If you are comfortable with your projects and have confidence in your skill set you would always have a competitive advantage over any certificate holder.

That being said, at Programink we do provide a ‘certificate of completion’ which reflects the fact that you have actively completed a rigorous course in data science. The Programink certificate of completion is only given to the students who have completed the entire course and have excelled in the programs quizzes, assignments and projects. What that means is even if the certificate slips through recruiters’ eye the wide portfolio of projects that you would have added in your resume and all the knowledge you would have gained while working on the assignments while completing the course will surly put you in the lime light.

The answer to the above question is subjective to your profile and willingness to learn.

For fresher’s, even if you start today you would need 3-4 months of dedicated learning to land an entry level job as Junior/Associate Data Scientist. If you put in more hours to gain the domain and industry experience you could even convert a Data scientist role opportunity directly. But for fresher it generally tougher because this position always demands an extraordinary combination of computer science, math, industry exposure, domain knowledge and corporate experience. All of these, for a fresher, is tough to bring on to the table for obvious reasons. But nevertheless, if you believe in yourself and are willing to put the desired work against your commitments then you will excel and would defiantly bypass all the social norms and at Programink we commit to walk this difficult path along with you so we can help you reach your career goals.

For an experienced personal it is comparatively easier as out of the required prerequisite the experience of the personal brings in the domain knowledge, industry exposure and the corporate experience by default. Rest of the skills like mathematics, computer science and hands on projects could be gained over 4-5 months of rigorous training in the subject while working on some complex problems which would help reshape your profile. Even if you’re experienced in domains which does not directly translates to data science or information technology we at programink guarantee you to guide you in path which would help you make this shift in career a cake walk. So sum things up for an experienced professional, apart from the evident advantages you would get from your work experience if you could add the required Mathematics and projects to your arsenal than you would be ready to enter the race.

Now as we have said that the years and work required to become a data scientist is subjected to many criteria’s so we would urge you take the free career counseling we provide at programink. After understanding your current skills and experience we would be able to chalk out a personalized career approach for you which would be realistic and achievable. Please check out the contact section to get touch with us.

Programink adheres to the philosophy that "Learning should never be a financial burden for the students". This philosophy is deeply hardwired in us and has helped us designed courses and facilities which ease the financial burden on students shoulders.

First approach is for all the courses above 20,000 you can avail a study loan of up to 80% with minimal rate of interest. That takes off any additional pressure of finances that students might had to face otherwise. You can now easily invest in your learning with balancing your monetary commitments.

Another approach adhering the philosophy was to bundle the courses in smaller chunks and priced them accordingly. This will help the students to take up the learning journey without shelling out a huge lump of amount.

Then we have tie ups with many MNCs and SMEs who want to shell out money to anyone who can solve some of their data related problems. So if the students can take up the challenge and deliver the satisfactory results then programink would credit the students with majority of the quoted amount. Further we also provide internship opportunities which would help a students to earn while they learn.

The fact that 90% of all the data available today was generated in the past 3 years vouch for the insight that human resources needed to handle and analyze the data is only going to grow in the coming decade. The cost of storing the data and cost of computing & crunching the data has fallen dramatically there by empowering even SMEs along with giant MNCs to get insights with help of data scientists from the massive data warehouses which were previously untouched.

Approximately 1 Lakh analytics jobs are stilled required to be filled in India which is 45% more than last year (2019). The fact that India only contributes to 6% of the Data Science job openings worldwide & the growth of the demand of data scientists worldwide was higher than India tells us that Indian market is just warming up to get into the world wide data science race. Further, companies like Accenture, Amazon, KPMG, Honeywell, Wells Fargo, Ernst & Young, Hexaware Technologies, Dell International, eClerx Services & Deloitte including their offices in India were the leading organisation with most number of Data science and analytics opening. To all the above mentioned facts if we add the insights that an analytics position on an average remains open for only 45 days we can easily infer that the world is increasingly demanding more data muscle to push itself in this age of information.

Banking and Financial services are the top Leader in the worldwide industry to apply data science in their business and other industries like energy & utilities, Pharama & Health care, E-commerce, Media & entertainment, Retail & CPG, Automobile, Telecom, Travel & hospitality etc. are still in their nascent stages when it comes to taking data backed decisions. As we enter this new decade we would definitely see how these industries would leverage data science to take data backed decisions. When they inevitably do so, they would need an army of data scientists.