Simple and Practical Data Science Topics for Your Next Academic Thesis.

 

If you’re a college student looking to find your college thesis topic and have a keen interest in data science, we got you covered. Here we discuss some of the easiest and simple data science topics for your thesis may it be schoolwork, college, or even for an academic publication and so on. Read till the end, and pick your pick out of the options and start off with your research and writing to meet your deadlines on time.

 

1. EDA (Exploratory Data Analysis) on Social Media Data:

 

Firstly, we have one of the quickest research based data science thesis paper you can work on with simply looking into the social media apps that you use daily.

 

●      Objective: With this project the goal is to understand patterns, trends, and sentiments of people scrolling through social media day in and day out.

 

●      Tools: To conduct this research you can make use of the simple to install and use Python (Pandas, Matplotlib or Seaborn).

 

●      Methods applied: To get started with the project, you can conduct simple analysis by opting to put a poll out on your social media page, and similarly find out what are the trending topics and then analyze the data received to visualize the engagement statistics.

 

2.   Linear Regression to Predict Model outcomes :

 

In this project your goal will be create a predictive model using the concepts of linear regression (‘a data analysis technique that predicts the unknown value of any data by using another related and known data value’).

 

Here,

●      The Objective: Develop a capable predictive model by using the concepts of linear regression.

●      Tools: Similar to the first project, you can use Python (Scikit-Learn) to help perform this project too.

●      Method applied: To start with creating a predictive model, you have to choose a data set that interests you, then perform feature engineering ( “Feature engineering is the process that takes raw data and transforms it into features that can be used to create a predictive model using machine learning or statistical modeling, such as deep learning.” ), then train the model and finally evaluate the model created.

 

3. Stock Price Forecasting by using Time Series:

 

If you are into the stock market, then this project may just be the one for you. Here, you understand and use time series analysis (“ a specific way of analyzing a sequence of data points collected over an interval of time.” ) to help predict future stock rates.

 

Here,

●      The Objective: The goal is primarily to help predict the future stock rates by using time series analysis.

 

●      The Tools: To perform this project you will need access and knowledge to Python tools like that of ‘Pandas’ and ‘Statsmodels’.

 

●      Methods Applied: In order to do this, you simply need to be know how to collect historical stock market details, organize and prep it, and then use the time series analysis models (like ARIMA) and check the accuracy of the predictions made.

 

4.  Spam Detection by using Text Classification:

 

Go through our mails is something everyone of us does everyday, weekly, monthly even, but how do you know if an email is spam or not? This project does exactly that, helps try to figure out if spam emails are spam or not.

 

Here,

The Objective: The objective of this topic for you would be to build a classification model that classifies text and is able to detect spam emails.

 

The Tools: To do this, one can use Python’s Natural Language Toolkit (NLTK) to help you.

 

Methods Applied: Here, basically you will preprocess the text data, make a classification model out of the preprocessed data and then see how it work.

 

5.  Data Analysis of Online Reviews and Web Scraping:

 

By performing this data science project you will be get data from multiple online sources and look into the reviews of customers.

 

Here,

●      The Objective: With this project the aim would be to get data from the many online platforms of your choosing and analyze the customer reviews of the platforms to understand customer engagement.

 

●      The Tools:  For this project, you will again use Python tools, the tools you can use are Beautiful Soup, Selenium to complete the project.

 

●      Methods Applied: By using the mentioned tools you are to gather data grom platforms, then proceed to sort and organize the collected data and then analyze the organized data to get an idea of how people feel about a product or service offered.

 

So there you have it, five data science projects that are creative, interesting and can be performed in simple ways. With these projects you get an insight into the working of data science professionals and to write a thesis out of the process. This not only helps you meet your academic deadline submissions in a timely manner but can also be added to your portfolio to help you secure a job in the data science field in the future.