Can we learn data science in 3 months?

If you start your career there, you can work your way up to one of the bigger companies or even start your own data science business. I’ve divided this curriculum up into three months: Month 1 focuses on data analysis. Month 3 we’ll learn production grade tools like that data scientists use in the real world.

How many months it takes to learn data science?

I know for a fact that no one can master data science in 1 month. In fact, my personal estimation (based on students I worked with) is that from zero to the junior level the learning process will take ~6-9 months. (More about that in this free course: How to become a data scientist. Learning data science is hard!

Is 6 months enough for data science?

Since six months is a concise period, it is advisable to go for a full-time course. Although, someone with a job in hand can dare to go for the online courses. An aspirant must be able to dedicate more than 8 hours a day in order to learn data science and even after doing that, one might fall short.

How long does it take to learn data science using Python?

Below is a Day-by-Day plan to learn Data Science using Python, this plan spans 100 days and it is required to spend at least an hour each day Just ensure that the required tools are installed and you become comfortable with the tool you are going to use for the next few weeks/months.

How to learn exploratory data analysis in data science?

In any Data Science project, about 80\% of the time is spent in this activity so it is best to spend time learning this topic thoroughly. In order to learn the Exploratory Data Analysis, there isn’t a specific set of functionalities or topics to be covered but the dataset and the use-case would drive the analysis.

What should I learn to become a data scientist?

The actual truth one needs to know just enough of the above topics to become a successful Data Scientist or to get hired as a Data Scientist. To become a Data Scientist one needs to learn just enough from the below topics If you choose Python then libraries like Pandas and Numpy Visualization libraries like ggplot, Seaborn, and Plotly.

How to learn supervised learning in 10 days?

Spend the first 10 days in knowing some of the key algorithms in Supervised Learning, understand the math behind them, and in the next 10 days focus on learning by developing a project. Some of the Algorithms that should be covered in this period are,