9 Data Science Projects For a Resume That “Woos” The Recruiter in 2021

Rapid advancements in data science have opened up new opportunities. Thus, people are flocking toward data science jobs.

Data science jobs pay well. It is because professionals who are skilled in in-demand technologies are highly valued. 

That being said, it is important to build an excellent resume so that you can stand out from the crowd. 

Without any experience in working on projects, a candidate’s resume holds a much lesser value.

Independently working on projects shows that a candidate is able to practically apply the concepts that they grasp from various online sources. 

Let’s see the Data Science Projects that are secrets of Many Successful Data Scientists.

Data Science Projects to Boost your Resume

Here is a set of twelve projects of varying difficulty levels, to help those who want to build their data science profile. 

1. Chatbot Project

Chatbot is the software that can interact and perform activities like humans.

These are very useful in instant customer interaction and on social networking sites for marketing.

This project is developed using deep learning techniques. Chatbot is trained on dataset having intents, patterns and responses.

Based on the input from customer, random response is given.

The project is developed using NLTK, Keras, Python, etc.

Source Code: Chatbot project in Python

2. Detection of Fake News

Thanks to the power of the internet and social media, the creation and spread of fake news have become a menace.

There have been instances where the situation has gone out of control because people acted without verifying the authenticity of the news. 

The project uses Tfidf vectorizer. Tfidf is a product of two terms TF – term frequency and IDF – Inverse document frequency.

TF refers to the number of times a term appears in a document. IDF measures the relevance of the term to a particular document. 

Next, the Passive-Aggressive classifier algorithm is used to detect fake news items.

This algorithm is called so because it is passive in case of correct classification and is aggressive if there is a miscalculation. 

3. Road Lane Line Detection

Detecting the lane line is critical for self-driving cars. To detect the lane we have to detect the white markings on both sides on the lane.

Using computer vision techniques in Python, we will identify road lane lines in which autonomous cars must run.

This is must as self-driving cars should not cross the lane to avoid accidents.

This is possible with the help of Frame Masking and Hough Line Transformation.

Source Code: Real-time Lane Line Detection in Python

4. Brain Tumor Detection

There are many famous deep learning projects on MRI scan dataset.

One of them is Brain Tumor detection.

You can use transfer learning on these MRI scans to get the required features for classification.

Or you can train your own convolution neural network from scratch to detect brain tumors.

5. Image Caption Generator Project

Identifying images is easy for humans.

When it comes to computer, the same task appears tedious.

But now with the help of Data Science libraries and frameworks, computers can also easily identify images and generate captions for them.

This project uses deep learning techniques where Convolutional neural network (CNN) with Recurrent Neural Network( LSTM) are used to build the image caption generator.

6. Detection of Credit Card Fraud

When there is a technological innovation, some of the first things that tech geeks look for is its application in curbing the anti-social elements. 

In this machine learning project, we use R to create a classification model to detect fraudulent credit card transactions.

Several powerful machine learning algorithms such as logistic regression, decision tree classifier, artificial neural network and gradient boosting are used to create the model and enhance its accuracy. 

7. Music Genre Classification

This is a classification problem.

The project takes a dataset of audio files and automatically classifies it into the appropriate genre using features like frequency and time domain. 

The project uses GTZAN dataset which contains short audio clips from ten different music genres.

The classification is done using the K-nearest neighbour algorithm as researches have proved that this approach provides the best accuracy. 

Source Code: Music Genre Classification Project

8. Movie Recommendation System

With the advent of AI and ML, people have started experiencing personalized recommendations in all forms – their shopping accounts, the music they listen to and the videos they watch. 

Personalized movie recommendations would help viewers save time as the algorithm identifies their favorite genres and presents them with corresponding movies. 

The algorithm uses collaborative filtering.

It is a system where the watch histories are compared, and those having similar histories would receive each other’s preferences as recommendations.

The user’s personal watch history is considered too.

Finally, one can visualize the various trends in movies using visualization tools in R.

9. Gender and Age Detection in OpenCV

OpenCV is short for Open Source Computer Vision. It is an ML library that is useful to process images and videos.

The project falls under a branch of AI called computer vision. This branch involves analysing digital images to extract data of various forms from them.

The algorithm can detect if the face in a given image belongs to a male or female.

But when it comes to age, it can be quite difficult to pinpoint the exact age of the person.

Thus, 8 different age bands are there. The face is classified into one of the age ranges. 

Source Code: Gender and Age Detection with OpenCV

Summary

The tools used in data science projects are quite versatile.

They are useful to build simple games and display windows.

On the other hand, they can also analyse large amounts of data and return valuable insights or perform predictions and classifications.

Thus, find a project in your area of interest and start working on the implementation.