20 Artificial Intelligence (AI) Project Ideas [2024]
Artificial Intelligence (AI) can greatly affect our everyday lives. Every time you visit Facebook, Twitter or Instagram you find a search engine that uses an algorithm. The Artificial Intelligence industry is projected to reach around US $ 126 billion by 2030.
AI is rapidly transforming various aspects of our lives, with its applications ranging from language processing to image recognition. As the AI industry continues to grow, it presents a plethora of opportunities for beginners to dive into exciting projects. Below, we present 20 AI project ideas categorized into beginner, intermediate, and advanced levels. We will continue to build on this list as well as share case studies and real-world examples.
AI project Ideas for Beginners
1. Translator App
When you want to get into language processing, you can create an app that is translated using a transformer. The transformer models extract features in sentences and determine their relevance. The transformer has both encode and decode components trained end-to-end. Build an AI translator application using this transformer. For this purpose the transformer has pre trained model that is loaded into Python. Transform text into a token, then send it to the training model. This is done using the GluonLP library.
2. Instagram Spam Detection
Have we ever heard of people posting comments on our blog? You open an iPhone app and are amazed that there’s an online bot that sells a shoe knockoff brand. Many Instagram posts are flooded with bot messages. These are usually unpleasant but can also be dangerous depending upon how you need them. You can use AI algorithms to detect spam by distinguishing legitimate comments. It could be difficult for someone finding the Instagram spam comments data, but it can easily be obtained by scouring the web.
3. AI Health Engine
AI has been called ” Agile health engines. It involves using algorithms and other AI techniques to analyze huge numbers of data pertaining to health and wellness to improve the health outcomes of patients, reduce costs and improve efficiency of healthcare care services. AI Health Engines will revolutionize the entire medical field with improved outcomes and personalized treatment options.
4. Fake News Detector Project in AI
Fake news is a misinformation which circulates in a news story. Sometimes people are unable to distinguish between fake or actual news and only after this situation has been discredited can we see it. The spreading of fake news is particularly dangerous during election periods. Faulty rumours and misleading information threaten the health and safety of people and the society. Fake news is necessary for the detection of the fake information and the prevention of its spread. In this very exciting project the fake news detector can be built using the fake data from Kaggle.
5. Building a Telegram Bot
Bots are computer software programs which you may use to either perform tasks or certain functions. In the most common sense, bots reproduce human behavior. How do you build a telegram bot using Python? The APIs are available from your BotFather Telegram account. BotFather is a simple Bot providing an innovative API to support bots. The next step is to add Telegram’s Telegram package. It’s simple and effective to start and run bot programs.
Telegram Bot Example
Here’s an example of a Telegram Bot, step by step, built by Gero, from the FullStackRemote talent network.
6. Heart Disease Prediction Project
It’s a useful project from a medical standpoint because the online service provides medical advice to patients affected by heart disease. Patients often complain they aren’t able to find the right doctor to help with medical problems and it becomes worse for them. This app helps prevent heart diseases. The proposed website would have an ai system allow the user/patient instant access to certified healthcare specialists who deal with heart problems. This application is designed to provide the user queries a thorough description and information about a wide range of cardiac conditions.
Intermediate/Advanced AI Project Ideas
Advanced artificial intelligence projects are not difficult but require advanced skills for creating and implementing your AI project ideas. Here are a list of AI project ideas for advanced technologists.
7. Animal Species Prediction
A similar computer vision technique can be used to forecast animal species from viewed photos. This is possible using the Animals10 data from Kaggle. The dataset is divided into ten different categories. It’s an interdisciplinary classification problem which you must predict on a single image in the data sets which reflects the classification of the animals. You may have an introductory model called VGG16 for these purposes. You can use Keras to create a Python model. VGG-16 is a convergent Neural Network (CNN) architecture developed with ImageNet and has more than 14M images.
8. Lane line detection while driving
It is primarily done in conjunction self driving cars with computer vision technology that detects and tracks road lane lines in a vehicle. The technology can be used for autonomous driving because it aids in keeping cars in their tracks while also preventing collisions. Identification along a highway faces several challenges, ranging from shifting lights to shifting roads markers and there are accidents. Therefore, the development of a reliable machine-learning model should provide the best possible solutions.
9. Handwritten Notes recognition
In this sense, learning ai method for reading handwritten texts is known as hand-written notes recognition. Optical character recognition technology can recognize and process handwritten text using computer vision techniques for such operations. Various algorithms and technologies are available for the development and operation of ai models of OCR technology for handwritten and emailed messages.
10. Personality Prediction System via CV Analysis
This is a great Artificial Intelligence project idea. It is difficult selecting the best possible applicant from a huge list of applicants. How can we analyze candidates’ personal traits? This makes selection much easier. This project aims to develop specialized software for CV ranking system. It’s a similar process to submitting applications on a job application website and submitting their application to the job board. Applicants can take online tests focused on personality traits and aptitude.
11. Age Detection Model
When observing someone else’s face, the most commonly identified age group. It is possible to see whether someone was younger, older, or a little older. This can be automated using Deep Learning techniques and age prediction models in this AI project. Many businesses use a variety of demographic information to improve the marketing of products and to define target audiences. But these data are not readily available. Firstly, on social media platforms, users sometimes say they are older than they were. Usually the information has been kept secret and never made public.
12. Customer Recommendation
Increasing numbers of people are turning their attention to technology. Best examples are Amazon Customer Recommendation software. This customer recommendations system greatly improves platform earnings, thanks to improved customer experiences. It could also be possible to create a user recommendations system for e-commerce platforms. It is possible to use the customer’s history to retrieve the information.
13. Stock Price Prediction
These are great AI projects ideas to learn from beginners. ML specialists like shares. It’s full of information. There are different sorts of databases available that you could use and you could immediately start to develop your work. Students who want to work in finance will love this program. The stock market has a short cycle in which you need to respond to your prediction. You can estimate price changes in stocks over six months by applying historical data obtained in the reports of the organization.
14. Fake News Detector
Fake News are inaccurate and misleading statements distributed as news. Usually, it is difficult to differentiate between fake and real news and it only comes to light when something terrible is discovered. The spread of false stories is particularly dangerous during election and pandemic situations. Fake news and misleading information threatening our society is a threat. Fake information must be found and prevented immediately. The very interesting project involves the building of a fake news detection tool.
15. Traffic Prediction and Analysis
Use traffic camera and sensor data to develop AI models for the prediction and optimal route planning of drivers. These projects are important to develop smart city initiatives as well as improve transportation.
16. AI-powered Search Engine
The AI-powered search engine uses AI technology to deliver personalised, targeted search results. This search engine uses specialized algorithms for the purpose of determining the search results and supplying the relevant results for users’ queries. A machine learning search engine delivers more detailed and relevant searches while giving users a customized search experience. They improve search efficiency and eliminate user modifications or the automatic sorting of unwanted results.
17. Price Comparison Application
Are there dresses in stores that offer lower costs? It is possible for AI users to upload pictures to a web app to make a sale. The app then scans several websites and finds out what is the most reasonable cost. It helps users to get better offers at a cheaper rate. The app is designed to be able to find images using algorithms. For example, the algorithms in the photo will determine which dress color and style are appropriate.
18. Improved Detection of Elusive Polyps
The AI program highlights Google’s use of machine learning to improve the effectiveness and accuracy of colonoscopy procedures to treat colorectal cancer (GIs). Breast cancer identification using Logistic Regression aims at developing deep neural networks for the GI system to detect polyp in the area where they are being monitored, thereby alleviating incomplete detection. It uses a model integrating time logic with an independent frame detector that delivers broader results. Several different Neural Network architectures are being developed – RetinaNET and LSTM-SSD.
19. Real-time Face Mask Detector
Since Covid-19 we have worn masks. Many public places, including shops, theatres and restaurants, do not accept people without masks or other clothing. The project aims at creating custom deep learning models that detect people wearing masks. To create facial masks object detection and model, use Github’s face masks dataset. The collection contains 1 376 photos divided by category masks and non-mask. This project demonstrates how to create and train a classifier to determine if someone wears a mask.
20. Earthquake Prediction Model
A major non-solved challenge for environmental studies is earthquake forecasting. This project demonstrates the use of the various machine learning techniques and the Python programming language and languages in developing earthquake models. The Python library that is used to build the data for the Python is pythhipy including the pandas Numpy and matplotlib. Explore earthquake data and create an object for these data features including dates, time, latitudes, longitudes and depths. Using this model, visualize data from Earth’s earthquake frequency map for an easy to read visualization.
Best Platforms to Work on AI Project Ideas
The tools are available for creating machine learning algorithms using pre-made data visualization software and enabling distributed computation. In addition to fostering development, there are many research groups whose research and development activities are aimed at supporting ongoing developments in data science and reinforcement learning. AI projects in the next few years will depend upon that technology.
When it comes to working on your AI project ideas, having access to robust platforms is essential for seamless development and collaboration. Here are some top platforms:
- TensorFlow: TensorFlow, developed by Google, is an open-source platform widely used for building ML models. It provides comprehensive tools and resources for both beginners and advanced users.
- PyTorch: PyTorch, maintained by Facebook, is another popular open-source ML framework known for its dynamic computation graph and ease of use. It offers extensive support for neural network development and experimentation.
- Kaggle: Kaggle is a well-known platform for data science competitions and collaborative projects. It offers datasets, kernels (code notebooks), and competitions to hone your ML and AI skills while competing with fellow enthusiasts.
- IBM Watson Studio: IBM Watson Studio is a comprehensive platform that facilitates AI development, data exploration, and model deployment. It provides a suite of tools for data scientists and developers to streamline the end-to-end ML lifecycle.
- Microsoft Azure Machine Learning: Azure Machine Learning is a cloud-based service offered by Microsoft that enables users to build, train, and deploy ML models at scale. It integrates seamlessly with other Azure services for enhanced functionality.
What are some future AI projects?
It is evident that AI is rapidly changing. There are plenty of possible directions that AI development may take. It is impossible to predict when and why AI projects fail – and this is going to happen. It’s also important to consider what, and when, to place guardrails on the technology. As with anything, AI needs to be regulated in a way that promotes responsible usage. One thing is certain – AI will continue revolutionizing our current world.
Conclusion
As we stand on the cusp of a new era in technology, the exploration and development of AI projects present an exhilarating frontier with endless possibilities! The array of AI project ideas discussed, from beginner to advanced levels, underscores the dynamic nature of this field and its potential to revolutionize how we live, work, and interact. Whether it’s through improving health outcomes with AI-powered engines, combating misinformation with fake news detectors, or enhancing our interactions online via sophisticated spam detection systems, AI is set to redefine the boundaries of what’s possible.
The projection of the AI industry reaching around US $126 billion by 2030 is not just a testament to its financial viability but also to its transformative impact on various sectors. The drive towards innovation, backed by robust platforms like TensorFlow, PyTorch, and Kaggle, is enabling creators and developers at all levels to contribute to this field.
However, the journey ahead is not without its challenges. As we embrace the vast opportunities AI presents, it’s crucial to navigate the ethical and societal implications responsibly. The future of AI projects lies not only in their technical excellence but also in their ability to enhance human well-being and operate within a framework of ethical guidelines.
The exploration of AI technology projects is more than just an academic exercise or a business endeavor; it’s a journey towards building a smarter, more intuitive world. By harnessing the power of AI, we are not just reshaping our present; we are reimagining our future. Let’s continue to push the boundaries, challenge the status quo, and contribute to an AI-powered world that is inclusive, ethical, and overwhelmingly positive for all.
If you’re eager to dive into the world of AI and contribute to this field, FullStackRemote is ready to support your ambitions. With a talent pool of over 500 engineers experienced in OpenAI technologies, alongside dozens of AI/ML experts, FullStackRemote is your ideal partner to bring your AI project ideas to life. Whether you’re just starting or looking to tackle advanced challenges, our community offers the expertise and collaborative spirit to help you make a significant impact. Let’s join forces to harness the power of AI, pushing the limits of what’s possible and driving positive change in our world.