How To Create a Data Science Project

If you have completed a data science course your next step is probably to create your first data science project. A data science project should not look like a program or just a piece of code, it should look like a report where you show your analysis and your approach to solve a problem. So in this article, I will take you through how to create a data science project.

How To Create a Data Science Project?

Before you start with a data science project, you should know what you need to cover in that project. A data science project should cover the lifecycle of a data science task so that you can show most of your skills in working with data and it also means that you know the full lifecycle of a data science task. ‘a data science task. Below are the steps of the lifecycle of a data science task:

  1. Collect Data
  2. Data Exploration
  3. Data Visualization
  4. Feature Engineering
  5. Model Training
  6. Model Deployment

So these are the steps of the lifecycle of every data science task that you need to follow in every project you do no matter what problem you are solving and what tools you are using. In the section below, I will take you through the three most important steps you need to create your first data science project.

Steps To Create a Data Science Project

Step 1: Choose a Problem Statement

You can only follow the lifecycle of a data science task if you are having a problem to solve. The only reason why companies want to see some good projects in your resume is that they want to see how you approach to solve a problem. They want to see how you think so you have to wisely choose a problem to solve to create a data science project.

There are millions of problems that you can find on Kaggle along with the datasets. So choose a problem statement and then find the most appropriate dataset to solve that problem.

Step 2: Identify and solve the problem

The next step is to identify and solve the problem. Here you have to first identify what you are going to do with the dataset and then follow all the steps involved in the lifecycle of a data science task to solve the problem.

In a data science project, you have to show all the steps taken by you to identify and solve the problem so that you can easily explain all the steps taken by you at the time of your interview.

Step 3: Create an end to end application

When working as a data scientist, you are not responsible for creating any software or web application, but you must run your model in a web interface so that you and your interviewer can see how your model solves the problem.

Creating an end to end application was used to be a tough job earlier but now it is very easy by using a Python framework like Streamlit.

Summary

So these were the three main steps that you need to follow while creating a data science project. In short, you have to choose a task where you can your data science skills to solve a problem. In the process don’t forget to follow the lifecycle of a data science task. In the end, try to create an end to end application to show how your model solves the problem. I hope you liked this article on how to create a data science project. Feel free to ask your valuable questions in the comments section below.

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Aman Kharwal
Coder with the ♥️ of a Writer || Data Scientist | Solopreneur | Founder
Articles: 1054

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