Is data science a good option for freshers?

It is essential that you take up an entry-level job at least, it’s the best way to learn data science. Just acquiring skills and specialisation won’t suffice. Only on the job will you be able to get good experience and exposure to data science.

Is it good to start career in data science?

Today there are many reasons to pursue a career in data science: a high salary, relatively stable and growing job market even during a global recession, and exciting problems to solve across diverse industries.

Is data scientist a cool job?

Data science expertise is highly sought-after because it leads to tangible and measurable business outcomes. As stated in Harvard Business Review, “Companies in the top third of their industry in the use of data-driven decision making were, on average, 5\% more productive and 6\% more profitable than their competitors.”

How to get a job in the field of data science?

Anyone skilled in these disciplines, be it a fresher or a seasoned professional, can get a job in the field of data science if they build a strong resume. In this section, we discuss a few suggestions you should follow, to build the perfect resume.

What Coursera courses did I take to become a data scientist?

I enrolled in the Coursera’s University of Michigan Applied Data Science Course. It was a specialization which included 5 courses namely: Introduction to Data Science – where I was introduced to various Python data processing frameworks like Pandas and NumPy.

What does an associate data scientist at Gartner do?

Responsibilities: As an Associate Data Scientist at Gartner, you will be responsible for leveraging machine learning and data science algorithms to deliver client value and improve retention of the clients. You will be applying natural language processing and predictive modelling to understand the client’s search query.

What is data science and machine learning?

Data science blends the multiple disciplines of machine learning, algorithms, data inference, programming, mathematics, and statistics to extract useful inference from data and solve complex problems.