• By  Junaid A    20-Jan-2023 
•   234

Here are a few suggestions for a final year project: Developing a machine learning model to predict the stock market trends. Building a chatbot that can assist with customer service inquiries. Designing a mobile application for tracking and managing personal health and wellness. Creating a recommendation system for personalized product or content suggestions. Developing a system for automated text summarization of news articles. Building a voice-controlled smart home automation system. Designing a virtual reality experience for education or training purposes. Developing a machine learning model for image or speech recognition. Building a web-based platform for online code collaboration and version control. Designing a game or interactive simulation to teach programming concepts.

Final  year project suggestions: Here are a few suggestions for a final year project:

1) Property Management Systems

A Property Management System (PMS) is a software application used by property managers and landlords to manage and maintain rental properties. A PMS can be used for a variety of tasks, including:

Rent collection: Automating rent payments and tracking late payments
Tenant management: Keeping track of tenant information and lease agreements
Maintenance and repairs: Scheduling and tracking maintenance requests and repairs
Financial reporting: Generating reports on income, expenses, and occupancy rates
Marketing and leasing: Listing properties on rental websites and managing showings and applications
Some PMSs are designed for specific types of properties, such as residential, commercial, or vacation rentals. Other PMSs are more general and can be used for any type of property. Some PMSs are cloud-based and can be accessed from any device with an internet connection, while others are desktop-based and must be installed on a computer.

A final year project on Property Management System could be a web or mobile app that allows landlords to manage their properties and tenants, track rental income and expenses, and generate reports. It could also include features such as online rent payments, maintenance request management, and automated lease renewals and rent increases.

Please note that this is just one possible example, and you should consult with your advisor or mentor to ensure that your project is feasible and will meet the requirements for your degree program.

2) Price Comparison website

A price comparison website is a platform that allows users to compare prices for products and services across multiple retailers. These websites typically have a search bar where users can enter a product or service and view a list of results with pricing information from different retailers.

A final year project on a price comparison website could include the following features:

Web scraping: Retrieving product and pricing information from various online retailers
Search functionality: Allowing users to search for specific products or services
Price comparison: Displaying pricing information from multiple retailers side by side for easy comparison
Product reviews: Including customer reviews for the products
Filtering options: Allowing users to filter search results by price, brand, and other criteria
Product and retailer rating: Giving rating to the products and retailers based on the customer feedbacks
Personalization: Customizing the search results based on the user's browsing history and preferences
The website could be designed as a web application, and it should be visually appealing and user-friendly. The data collected and stored should be accurate and up-to-date.

Please note that this is just one possible example, and you should consult with your advisor or mentor to ensure that your project is feasible and will meet the requirements for your degree program.

3) Developing a machine learning model to predict the stock market trends.

Developing a machine learning model to predict stock market trends is a challenging and complex task that can make for a great final year project. There are many different approaches that can be taken when building such a model, and it will depend on the specific requirements of your project and the data that you have available.

Here are some steps that you could take to develop a machine learning model to predict stock market trends:

Collect and clean data: Gather historical stock market data, such as stock prices, trading volumes, and economic indicators. Clean and preprocess the data to ensure that it is in a format that can be used for training the model.

Feature engineering: Extract relevant features from the data that can be used to predict stock market trends. This might include technical indicators, such as moving averages and relative strength index, or fundamental data, such as company financials.

Model selection: Choose a machine learning model that is well-suited for the task of stock market trend prediction. Some popular models include linear regression, decision trees, and neural networks.

Training and evaluation: Train the model on the data and evaluate its performance using metrics such as accuracy, precision, recall, and F1 score.

Optimization and fine-tuning: Optimize the model's parameters and fine-tune its performance to improve its accuracy.

Backtesting: Test the model's performance on unseen data to evaluate its ability to generalize to new situations.

Deployment: Deploy the model in a live trading environment and monitor its performance.

It's important to note that the stock market is a complex and dynamic system, and it can be difficult to predict its trends with a high degree of accuracy. Additionally, it's always a good idea to consult with your advisor or mentor to ensure that your project is feasible and will meet the requirements for your degree program.

4) Building a chatbot that can assist with customer service inquiries.

Building a chatbot that can assist with customer service inquiries is a popular use case for natural language processing and can be a great final year project. Here are some steps you can take to build a chatbot for customer service:

Define the scope of the chatbot: Determine the specific customer service tasks that the chatbot will be responsible for handling. This could include answering frequently asked questions, troubleshooting technical issues, or providing information about products and services.

Gather training data: Collect and organize a dataset of customer service inquiries and responses. This data can be used to train the chatbot's natural language processing model.

Choose a platform: Decide on a platform to build the chatbot on, such as Dialogflow, Botkit, or Microsoft Bot Framework. These platforms provide a user-friendly interface for building, testing and deploying the chatbot.

Design the conversational flow: Create a logical flow for the chatbot's conversations, including the prompts and responses it will use. This can be done using tools such as flow diagrams or state machines.

Train the model: Use the training data to train a natural language processing model, such as a transformer-based model like BERT or GPT-3, to understand and respond to customer inquiries.

Test and evaluate: Test the chatbot on a small set of real-world customer service inquiries to evaluate its performance. Make adjustments and improvements as necessary.

Deployment and maintenance: Once the chatbot is working as expected, deploy it to the customer service platform and monitor its performance. Update the chatbot's knowledge base and retrain the model as needed to improve its performance over time.

It's important to note that building a chatbot for customer service requires a good understanding of natural language processing and

5) Designing a mobile application for tracking and managing personal health and wellness.

Designing a mobile application for tracking and managing personal health and wellness can be a great final year project, as it combines aspects of mobile app development with healthcare and wellness. Here are some steps you can take to build a health and wellness mobile app:

Define the scope of the app: Determine the specific health and wellness features that the app will provide. This could include tracking fitness activities, monitoring sleep patterns, or providing information on nutrition and mental health.

Research and gather data: Research best practices and current trends in health and wellness, as well as gather data on the specific health concerns of your target user group.

Design the user interface: Create wireframes and mockups for the app's user interface, including its layout, navigation, and visual design.

Develop the backend: Build the backend for the app, including the database and API for storing and retrieving user data.

Implement the features: Develop the specific health and wellness features of the app, such as tracking fitness activities, monitoring sleep patterns, or providing information on nutrition and mental health.

Test and evaluate: Test the app on a small set of users to evaluate its performance, gather feedback and make adjustments as necessary.

Deployment and maintenance: Once the app is working as expected, deploy it to the app stores and monitor its performance. Update the app with new features and fix any bugs as needed to improve its performance over time.

It's important to note that building a health and wellness app requires a good understanding of mobile app development, healthcare and wellness, as well as user experience and user interface design. Additionally, it's always a good idea to consult with your advisor or mentor to ensure that your project is feasible and will meet the requirements for your degree program.

It's important to note that these are just examples, and you should choose a project that aligns with your interests and skills. Additionally, it's always a good idea to consult with your advisor or mentor to ensure that your project is feasible and will meet the requirements for your degree program.

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