How should I prepare so I can take part in Data Science hackathon with confidence ?

Also I have around 4-5 months with me. What else should I do to get an Internship in DataScience ?

# How should I prepare to participate for Data Science Hackathon?

**tpssoni**#1

Hey

Assuming that you have sufficient basic knowledge about Data science, you can start solving the practice problems given on the datahack page. Solving any of them will help you learn many new techniques. Take any problem, and follow the basic pipeline required to solve it. Check the data, gain insights, draw visualisations, preprocess it. This should take up 80% of your total time. After completing these processes, study which all algorithms can be used to solve such problem. Study them via the articles mentioned on the website. Find which one of them would work best for this problem and Why. After building the basic model, try to optimise it and analyse the metrics like accuracy. It is an iterative process and would take time. You can also find many open source datasets online for practice. In the process of solving these problems, you will be introduced to many new techniques which helps in building a better solution. Once you are confident enough, you should take part in the competitions and see where you stand.

You can post any query/doubt which you face during learning on the portal and the data science community would love to help you.

Happy Learning.

**Blackberry**#3

Hi Gurchetan,

What about if i collect most of the knowledge about statistics then jump into machine learning. I found to understand mostly about predictive modelling there need to be expert in EDA which is more handy if we know good statistics, then interpreting predictive model parameters and outcome which is also more easier to understand if we know statistics

Thanks

Hey

As I mentioned in the above reply, I assumed that you know the basics well and what I meant with basics is Statistics. Statistics is like a stepping stone for Data science. Most of the techniques and algorithms are based on statistics. Proper understanding of statistics will help you significantly in the overall process.