Is it too late for an almost 40 year old jock to become a data scientist?

Question

Is it too late to start learning Data Science. I am currently 40 years old.

Answer 1

Further, in this Data Science training in Bangalore, you will gain proficiency in R statistical computing, create a movie recommendation system, build a recommendation engine for eCommerce, and deploy market basket analysis in the retail sector. So, register for this Data Scientist course today!

Answer 2

There are a lot of professionals who are really late in the game and they are from diverse backgrounds. That doesn’t mean they aren’t doing well in the field. Aspiring Data Scientists with no prior knowledge or experience in the field are also easily able to get into the domain. Many training institutes have designed and curated their Data Science course to cater to novices and beginners. They also have training courses in Python programming as well. 

 As a matter of fact, Intellipaat offers a FREE foundation course on Python for Data Science and also has a well-designed Data Science course in Bangalore, which is in collaboration with IBM. The course includes all necessary modules like: 

• Data Exploration

• Data Manipulation

• Data Visualization

• Statistics

• Machine Learning

• Logistic Regression

• Decision Trees and Random Forest

• Unsupervised Learning

• Association Rule Mining and Recommendation Engines

The course also offers 24/7 online learning support as well as provides placement assistance and training.

But, before enrolling in full-time classes, I would advise you to check out all the online resources like youtube tutorials, blog tutorials, free demo courses, etc. Self-learning with these resources can be a very good way to get started for beginners such as yourself so that you can get an edge when you eventually start training under professionals. Here is a really comprehensive video tutorial by Intellipaat on Data Science - 

Another crucial point to note is that only rigorous training and practice will help you along the way. The more you work on real-time projects, the more hands-on experience you will earn.