We are using four criteria to evaluate the myth in Data Science learning.
We have estimated self-learning time for data science is about 6-12 months with a college degree in relevant math or statistics background, or with the good amount of industry experience. The average age of data science learners is from 28-55. You have the flexible schedule by self-learning. However, taking 4 hours a day for learning is very challenging because the subjects are also challenging, like Machine Learning and Python Programming. This estimate is under the condition in the lab where you are measuring yourself with a perfect situation. You even need to put more hours and hours when getting stuck.
The skill required for Datascienceareprograming skill like Python, R, Mathematical skill of statistics. You will also require knowing a query language like SQL and Data mining and data visualization tool like Metplotlib or D3.Js. Data Scientist is also expected to know some conceptual level understanding of Data Engineering tools like Big Data, Hadoop, Spark and Splunk. Learning these skills by yourself is quite challenging if you are not programmer or having relevant experience.
In self-learning mode, you will be required to buy lots of books and get a development environment to learn these tools. You are looking between $500- $1000 dollar investments.The total cost is somewhere between 4K-25K from Applied Labs.
If you are taking this a major in college you are looking at 35-85k minimum. We will not recommend going college and putting 2 years learning data science. We highly encourage to take Applied Labs in workshops format and spend remaining day mastering your subject.
As self-learner, you will miss lots of action and discussion which happened in data science community. The Data Science field is the target to solve the problem with a data-driven approach. Getting data from the web and in simulated environment is one of the challenging tasks of doing self-learning data science.
Founder/ Chief Data Scientist