Useful Data Science Projects in 2022

Among all the technological advancements in the 21st century, the use of data has given rise to the most revolutionary field named Data Science. In this article, we’ll discuss the 3 most useful data science projects you should work on to get a high-paying job as a data professional.

The jobs in the data field have been seeing exponential growth for the past 5 years, and the salaries the company pays to the data professionals are more than satisfying.

The average salary for a data scientist in India is 11 Lacs INR. if you want to know the salaries of other designations in the data field, like data analyst, business analyst, data engineer etc., you can read our article: Data Scientists Salary in India

You’re reading the article useful Data Science Projects in 2022.

If you’re willing to pursue your career as a data professional and don’t know where to start, you can start by exploring these amazing certification programs by Console Flare:

1. Python For Data Analytics Certification Program

2. Masters in Data Science With Power BI

At Console Flare, you get to work on various capstone and live projects that are useful in improving your data analysis and data visualization skills.

Data Science Projects

Here are some of the data science projects you can work with to get an amazing job opportunity as a data professional. These projects are:

1. Covid-19 Data Analysis

2. Customer Journey Segmentation

3. Trip Duration Prediction

Now, we’ll explain what these projects are and how can you use them in your portfolio so that your profile becomes stronger.

You’re reading the article useful Data Science Projects in 2022.

1. Covid-19 Data Analysis: The pandemic has caused millions of viral cases and deaths all over the globe. You can create a data science project where you can create the datasets for the following:

a. Total cases worldwide

b. Total active cases

c. Total recovered cases

d. Total deaths worldwide

Using Pandas, you can analyse data from the official WHO website. To perform data visualization of total active cases, recovered cases, and deaths in the top 10 states of India, you can use Matplotlib & Seaborn libraries.

2. Customer Journey Segmentation: Tracking customer journey is a part of digital marketing, and many tools like Google Analytics exist to perform the same.

A data professional analyses all the data received from the digital marketing team and identifies the pattern of the users coming to your website and performing actions. You can take all the data and analyze how many customers visited your website, most viewed pages, number of users who added any product to the cart, number of users who made a purchase and total numbers of users who bounced off the website within 1 minute after entering.

Performing this type of analysis can help companies identify their strengths and weaknesses in terms of their digital presence.

Based on the analysis, companies can take decisions to grow their revenue.

You’re reading the article useful Data Science Projects in 2022.

3. Trip Duration Prediction: Companies like Uber & Ola use Google Maps on their app, and sometimes they have to tell the user the time duration for the arrival of their ride.

Using Machine learning, these companies add a beautiful user experience, and the users can plan their journey according to the app’s prediction. Silicon Valley giants like Uber often look for professionals who can work on projects like this and are good in Machine Learning.

To perform this prediction, you can explore this New York City Taxi Trip Duration dataset on Kaggle and portray this useful project in your portfolio.

While going for a data science interview, adding at least 2 to 3 data science projects can be more than beneficial for your profile and can land you an amazing salary package.

data science projects in 2022

To learn more about the data profession, you can browse through our blog to find useful information about data science that can ultimately help you start your career as a data analyst, data engineer, database manager, and data scientist.

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