Introduction
With several data science project ideas swarming the internet, budding data science professionals often get confused about which project to choose. Before you choose a project, you need to understand where your passion lies or have an idea of which industry you are looking to contribute to as a data scientist. For instance, if you aim to contribute to improving data handling tasks in the healthcare field, you need to choose a project which is related to handling patient data in the hospital. Here are a few aspects that you need to consider before choosing a data science project.
When you start your research, ensure that you select a data science project idea that is relevant to your goals and interests. The project that you choose should also be compatible with your skill set and expertise. Ensure that the project you choose has access to high-quality datasets and enables you to perform meaningful analysis with maximum insight. Many professionals select a task which lacks depth and practical application in the current industry; just make sure that you do not make that mistake. Here are some quick tips on choosing the project.
- ● The project needs to have a scope to explore your creativity and sharpen your skills
- ● It must not be too simple and bland
- ● It should be compatible with different software and tools (cross-functional capability and AI integration)
- ● It should be scalable
- ● Focus on exploratory data analysis to be aware of patterns before you start modelling
Prerequisites for Starting a Data Science Project
- ● Problem definition: Define the problem that you need to solve through this project (Whom does it benefit?)
- ● Prepare the data for analysis
- ● Explore the data and look for relationships
- ● Install relevant data analysis tools, machine learning, and deep learning libraries
Here are 9 beginner-friendly projects that help you kickstart your career in data science.
Credit Card Fraud Detection
Did you know that banks use software powered by data science and artificial intelligence technologies to help in detecting credit card fraud? In this project, you need to use R or Python language and gather a dataset on credit card transactions. Here, you will be analyzing the customer’s spending behavior and mapping the location of the spending to detect malicious transactions from the genuine ones. Ingest the data set into artificial neural networks, decision trees, and logistic regression. The system will automatically increase the accuracy once you feed it more data. This project will help you land a job in BFSI and IT.
Storytelling Data Visualization on Exchange Rates
In this project, you will create a storytelling data visualization on foreign exchange rates. Gather the dataset on the foreign currency exchange rates and use Python and Matplotlib to analyze historical exchange rate data between a specific years. This can help you identify key trends and events that shape the INR-USD relationship with ease. Here, you can apply data visualization principles to clean data and develop a narrative around any fluctuations in the exchange rate. Doing this project will help strengthen your capability to convey complex data insights in a crisp and concise manner. This project will land you a job in BFSI, foreign exchange agencies, and reputed MNCs.
Detecting Parkinson’s Disease
Diagnosing certain rare diseases can be done easily with the help of data science, machine learning, and gen AI. Gather UCI ML parkinson datasets and use Python as a programming language to help detect Parkinson's disease. As Parkinson's is a neurodegenerative disorder, the patient's history and lab results can be analyzed to detect any anomalies and shortlist patients who are prone to developing Parkinson’s in the future.
System that Recommends Movies
As you know, algorithms drive the click-through rate and viewership for all OTT platforms. In this project, you will be using R language and gather the dataset like metrics, age, previously watched shows, genre, and watch frequency. You can now feed all this information into a machine learning model, through which you can build a recommendation system that is either content-based or collaborative. This project can help you land a job in the media and entertainment industry.
Analyzing Employee Exit Surveys
If you are looking for a fairly simple project that is easy to execute, choose the employee exit survey analysis project. In this project, you can use a sample dataset and implement Python and Pandas to clean data and combine datasets. This can help in gathering insights regarding the resignation patterns and looking into factors like years of service, age groups, dissatisfaction, and other relevant information. You can learn data cleaning and exploratory analysis through this project. This project will help you land a job in leading IT companies and talent acquisition agencies.
Exploring Car Sales Data
Start off by analyzing a dataset of used car listings from a retailer or second-hand car dealer and cleaning the data using Pandas and Python. This project’s objective would be to explore listings, uncover insights on user car prices with regard to the popular brands and analyze the relationship between different attributes. This project will help you become stronger in data analysis and provide valuable experience in working with messy datasets. You can also implement data science with machine learning concepts in this project. It will help you land a job in e-commerce and IT organizations.
Speech Emotion Recognition
Use RAVDESS dataset and Python to analyze emotions behind speech. In this project, you will identify and extract emotions behind speech by extracting emotions from various sound files of speech. Through this project, you can land a job in learning IT and legal/judiciary firms.
Fake News Detection
With a lot of fake news swarming around the internet, PR agencies and other organizations are looking for a solution to help in detecting fake news. You can showcase your expertise as a data scientist by using the news.csv data set and Python to build a model for separating fake news from authentic news.
Customer Churn Analysis
The number/percentage of customers who stop using a company's products/services for a specific time period is known as customer churn. Use the data set on demographic information, customer account details, and other relevant data to determine the customers who are likely to leave. With Python and gen AI integration, you can also suggest ways to retain such customers. Drive this project by using Scikit-learn to create a decision tree that helps in predicting customers who are likely to leave after getting trained on churn data. This project will help you land a job in any service/product-based company.
Now that you have a fair idea of how to go about your first data science project, you may need some guidance on which project to choose and how to implement it. That is where Eduinx can help you. At Eduinx, our mentors have over a decade of experience in data science and generative AI. They will give you the right guidance to perform a capstone project. By learning generative AI with data science, you can stand out from the competitors and suggest different data science solutions for clients and organizations. Learn data science with generative AI at Eduinx and boost your career.
