Best Data Science Project for Final Year Engineering Students

Here is the list of the Best Data Science Project Ideas for final-year engineering students in 2023. IT & Software Project Ideas for B-Tech, M-Tech & Ph.D. students.

The examination of large amounts of data using current tools and methodologies to discover previously unknown patterns, extract crucial data and make business choices. To create prediction models, data scientists employ complicated machine learning algorithms.

The goal of this essay is to quickly explain the top Data Science project ideas.

• CNN Traffic Sign Recognition System:

The user can upload a picture to the system for it to identify and recognize traffic signs. The technology is capable of recognizing and detecting uploaded videos.

To begin recognizing real-time traffic signs, the user must switch on their device’s camera and click on the camera button.

• Collaborative Filtering Tour Recommender App:

In this system, an individual can arrange his/her day by picking from a list of venues based on his food and place preferences.

There may be an unlimited number of plans, and all locations are retrieved by utilizing Google Place API and sorted by highest rating. The Plan took into account the total amount of hours contributed so that it could compute your trip time + time spent at a certain site.

The user may manually sort the final locations or use automated sorting to determine the best path. Based on the plans of other users, the system will recommend locations where and when they are needed.

• Smart Contracts in a Blockchain-based Loan Management System:

The administrator can access the system by logging in and out. They have the power to examine, approve, block, and remove clients, as well as manage their loan requests.

The admin may examine a list of all clients who have sought permission, and a contract will be formed.

The loan money might also be transferred to the consumer. The system will email the administrator a list of all clients who have successfully obtained loans and their payback information. Customers may see all of their transactions.

• Chest X-Ray for Pneumonia Detection:

The essential aim of this project is to create a facial recognition-based attendance management system for workers employed in an organization to improve and enhance the present attendance systems to make them more efficient and effective than previously.

 The employee should be in a well-lit place so that the detection may be done clearly.

• Using Decision Tree to Anticipate Home Values:

The Housing Prices Prediction System forecasts home prices using multiple Data Mining approaches and picks the models with the greatest accuracy score.

The administrator can connect to the system using a username and password with this system. The admin can manage the training data and can add, amend, remove, and inspect data. The administrator can examine the list of registered users and their details.

• Google API Text Translation App:

The Translation Application makes use of the Predictive Text API to translate input text or messages into the language of your choice. For example, if the user enters content in English and the translation language is set to Hindi, the Google Translation API will convert it into Hindi.

The Google Translation API’s recognition engine for the Neural Machine Translation (NMT) model covers over a hundred languages. Language code parameters are used within a recognition request to define various languages.

• AI-Powered Image Translation App:

To detect the item, the system employs Object Detection from Google Cloud Vision API, which is a component of Machine Learning (ML). Similarly, for Text, we use Text Detection from Google Cloud Vision API to detect the Text, which is also part of ML.

• Flutter NLP Mental Health Check app:

In this system, the individual will be able to engage in conversation with the bot and will get specific questions to which they will monitor how the operator is responding by a set of categories created with the use of Google NLP the emotional states are detected and AI will recommend to the user with a video link to yoga, workouts, inspirational videos to enhance him/her and assist in creating their psychological state healthier from the current mood.

• App for Predicting Heart Disease on Android:

This Heart Disease Prediction Mobile Application was created to assist users in evaluating their cardiovascular health.

This system makes a forecast about the ailment that the user may be suffering from based on a variety of characteristics such as the user’s age, gender, sugar levels, lipid profile, blood pressure, and so on.

Aside from checking their cardiovascular fitness, users may also get contact information for numerous doctors on this app. The user may look for physicians by filtering them by expertise.

• Detection and Prognosis of Knee Osteoarthritis:

This online program determines the severity of the condition in addition to assisting with early identification. The patient can register and fill up his information. He must provide his name, username, an x-ray photo, a guardian photo, his photo, an identification photo, a license photo, and other information.

We can have persons with the same name, but not with the same username. As a result, there will be no mismatch. Each person will be assigned a unique username as well as a specific detection, complete with symptoms and a cure.

• App for Doctor Appointments & Disease Prediction:

The administrator may control or examine the details of physicians, patients, and diseases in this system, as well as get comments from patients. It also controls all of the doctor’s scheduling information, doctor fees, and appointments.

The doctor can communicate directly with the patients to stay on top of their health situation. Patients can estimate the condition by inputting the characteristics they are experiencing, and they can also stay up to speed on emerging diseases and their symptoms.

If indeed the user/patient is experiencing any of the ailments, they can schedule an appointment.

• Neural Networks for Facial Emotion Recognition:

This system will identify a user’s live emotions by comparing the input to training data of known emotions to discover a match.

Different emotion types are recognized by combining data from facial expressions, bodily movement and gestures, and voice. The technology is thought to have aided in the development of the so-known emotive or emotive Internet.

• Naive Bayes Prediction for Cancer:

Users in this system receive rapid advice on their Cancer sickness via an innovative online system. The Cancer Disease Diagnosis web application is a project for end-user assistance and online consultation.

The program is given numerous details as well as the Cancer illness connected with the stored data. It enables users to communicate their Cancer-related concerns. It then examines the user’s individual information to look for cancer diseases that may be linked to the user’s inputs.

• App for detecting anomalies in time series data using Azure Cognitive Services:

The detection of anomalies is the discovery of unusual occurrences, things, or observations that are suspicious because they deviate dramatically from typical behaviors or patterns from the surroundings.

In this system, the user must register to log in with their basic information for access. The user can manually enter a sequence of numerical data or upload an excel file to the system and pick a column.

The system will display the data in a graphical representation based on the automatically recognized spikes, dips, or deviations. All data can be saved by the user later.

• Higher Education Admissions Prediction Software:

This technique assists students in taking the entrance exam online and gives a college list based on their scores. The system’s primary goal is to give a quicker and more efficient way to take the exam, and it also offers results immediately following the exam.

Multiple-choice exams are used to present pupils with unique benefits that are not available anyplace else. This software program is designed to check objective solutions in an online test and provide points to the participant after the answer has been verified.

• Data Mining for Online Assignment Plagiarism Checker:

This plagiarism detector compares similar content and finds plagiarism. The internet has impacted students’ lives as well as their learning styles. It enables pupils to get deeper into their approach to learning, making their work easier. Many approaches are used to identify plagiarism.

• Android Chatbot for General Knowledge:

This system responds to the requests of the Users. The user only needs to type his question, and the system will evaluate the important phrases and respond.

The user may ask questions on many categories such as sports, education, health, and so on. The system will answer the user’s inquiry using a highly optimized algorithm.

• CV Analysis Personality Prediction System:

This approach will make it easier for the HR team to shortlist candidates depending on the CV rating policy.

This approach will concentrate not only on qualifications and experience but also on other crucial factors that are necessary for a certain employment role.

This method will assist the human resources department in selecting the best candidate for a certain job description, resulting in expert manpower for the firm.

• Data Mining for TV Show Popularity:

The primary objective is to locate the evaluations. Nowadays, most television shows are centered on dance, singing, and acting. Many shows are shown on various stations.

There are several methods for determining the number of views.  And to figure out which program has the best grade and is the most watched. Data mining principles will be used in this case. To pre-process the data, use Natural Language Processing (NLP). The ratings are predicted using Machine Learning techniques.

• Personality Classification Using Data Mining:

The system analyses several user attributes and behaviors and records its user attributes trends in a repository depending on the patterns seen. The technology now anticipates new user personalities based on the personality data stored from earlier user categorization.

This approach can help social networks and other ad-selling web networks classify user personalities and sell more pertinent adverts. The technique is also beneficial for government organizations to observe and anticipate new user personalities on a wide scale.