Is big data course difficult to learn?
Because of the often technical requirements for Data Science jobs, it can be more challenging to learn than other fields in technology. Getting a firm handle on such a wide variety of languages and applications does present a rather steep learning curve.
Is data science easy to learn?
Like any other field, with proper guidance Data Science can become an easy field to learn about, and one can build a career in the field. However, as it is vast, it is easy for a beginner to get lost and lose sight, making the learning experience difficult and frustrating.
How much time does it take to learn big data?
I have seen people coming up with good knowledge in 30 days. You need to practice a lot on hadoop cluster. Ideally, it will take 2–3 months to come up with a good personnel in Big Data. If you are core developer on database or Java, it may take bit less time.
How can I become proficient in big data?
Becoming proficient with big data analytics platforms such as Hadoop, Spark, R and Python will help you gain insight into how best to leverage code to solve your problems. (For a good primer on the variety of programming languages available for big data, see this blog post from last year’s DataWorks Summit.)
Do you need to learn programming to master big data?
Programming for insight. Mastering big data technology requires problem-solving skills that often require programming chops. An awful lot of analysis projects boil down to “write some code” — whether you’re wrangling XML or constructing models using machine learning libraries.
How long does it take to reach the beginner level?
It takes a few hours to reach the beginner level. From beginner to intermediate level, it takes days, and from intermediate to expert level, it takes months. Let me tell you my story. When I started working on big data, I was working on a project where data volume was rapidly increasing.