Artificial intelligence (AI) is a very in-demand and lucrative field. Major industries such as transportation, healthcare, manufacturing, and finance rely heavily on AI applications to speed up processes and minimize human error. However, the AI industry is highly competitive, and it takes continuous learning to be considered an expert in the field.
In this article, we show projects that can help you advance your skills in this thriving field, whether you are a beginner or an expert. We also highlight the key skills that you need to focus on and give you tips for organizing your digital portfolio.
5 Skills That Artificial Intelligence Projects Can Help You Practice
AI uses sophisticated software and advanced hardware technology to create systems that mimic the decision-making process of the human mind. To complete the AI projects included in this article, you will need specific computer and analytical skills, which we discuss below.
- Programming. Coding is a crucial skill in AI. Python is an industry favorite because it has packages for AI and machine learning. Other programming languages used in AI are C++, AIML, Perl, Lisp, Prolog, Smalltalk, STRIPS, Planner, and MATLAB.
- Data analysis. AI engineers deal with vast amounts of data when completing projects. To understand and process datasets, they should have a working knowledge of data analysis fundamentals and software such as Apache Spark and other data processing frameworks.
- Machine learning algorithms. To create functional machine learning projects, you need to understand basic machine learning algorithms such as logistic regression, linear regression, SVM, decision trees, Naive Bayes, KNN, K-means, and random forest.
- Unix-based tools. Data processing in AI is the conceptual basis of Linux systems. To grasp standard AI functions, you will need to learn Linux-based tools such as global regular expression print (GREP), AWK, and Sort.
- Artificial neural networks. Artificial neural networks are algorithms that mimic human brain functions. You need to gain a basic understanding of this computational system to resolve problems in AI applications for face, pattern, and handwriting recognition.
Best Artificial Intelligence Project Ideas for Beginners
As a beginner, the best way to learn artificial intelligence is to get hands-on experience through relatively simple projects. Below you will find some of the most popular project ideas for beginners.
- Artificial Intelligence Skills Practiced: Artificial neural networks
Handwriting character recognition applications convert raw handwriting to digital form. The computer recognizes and interprets different handwriting styles and mathematical symbols from touchscreen devices, photos, paper documents, and other sources.
Handwriting recognition has many practical applications that make administrative work faster, such as taking notes, reading filled-out forms, and authenticating bank checks. This project relies on the use of an artificial neural network.
- Artificial Intelligence Skills Practiced: Random forest regression
Predicting housing prices is challenging for many realtors because of the different variables involved. Factors at play include the dimensions of the house, number of rooms, location, the crime rate in the area, and real estate price fluctuations.
AI can help home buyers know the actual value of a house and aid realtors and developers in determining the price of a property. This is done by obtaining datasets and using a regression approach to create forecasts.
- Artificial Intelligence Skills Practiced: Python programming
Online retail shops, websites, and other online service providers use chatbots in customer service. Chatbots help personalize the user experience by showing visitors how to navigate a site more effectively and answering common inquiries. To develop these programs, developers commonly rely on the Python programming language.
AI novices can learn a lot by developing a simple chatbot as this project will put their programming skills to the test. Once a basic version of the chatbot has been created, it can be upgraded with more advanced features.
- Artificial Intelligence Skills Practiced: Python programming, machine learning
When Enron, the infamous energy giant, went bankrupt in 2001 following a scandal involving fraudulent business practices, it left behind a large collection of emails and messages. In total, 150 emails and 500,000 messages were made available to the public with the goal of unveiling more of the financial crimes committed by company executives.
If you are interested in programming and machine learning techniques, you can use this dataset for training in network analysis, investigation, and anomaly detection. The challenge is to use the data to develop models and systems that can be employed in finding persons of interest.
- Artificial Intelligence Skills Practiced: Programming, artificial neural networks, machine learning, data mining
Product recommendation systems are commonly used in ecommerce to drive profits, increase conversion rates, improve the user experience, and boost customer loyalty. These systems rely on an algorithm that uses customer search queries, location, past purchases, and viewing history.
Creating a recommendation system will allow you to practice skills like machine learning, data mining, programming, and neural networks. Python, R, and Java are some of the languages commonly used to build these systems.
Best Intermediate Artificial Intelligence Portfolio Ideas
Once you’ve completed a few beginner AI projects, you can move on to more complex programming endeavors. Some of the intermediate projects below require specialized knowledge in industries like finance or medicine. For many of them, you will need an understanding of machine learning and, specifically, deep learning techniques.
- Artificial Intelligence Skills Practiced: Machine learning algorithms
The stock market is very volatile and prices are notoriously tough to predict. However, you can analyze market-related data to find patterns and spot trends. Data scientists do this to come up with better trading strategies and ways of beating the market.
AI learners who are interested in finance and stock trading should look into these types of projects. The challenge is to predict how the stock market will behave in the coming months using the given datasets and their data analysis skills.
- Artificial Intelligence Skills Practiced: Machine learning, Python programming
Most bank chatbots are Android applications used to answer common questions. They save banks money by reducing personnel costs. These bots use AI algorithms to understand client inquiries regarding loans, accounts, or credit cards. Creating a banking bot is a great project for beginners and intermediate-level learners. You will practice machine learning techniques and programming languages like Python.
- Artificial Intelligence Skills Practiced: Data mining, artificial neural networks
This project involves creating an application that can diagnose heart-related problems based on information entered by the patient. Patients can use this application as a free online consultation of sorts. Once the patient enters their information and is given a diagnosis, the app can connect them to a doctor that specializes in their specific heart condition. This project is ideal for those interested in creating AI-based medical equipment to improve healthcare services.
- Artificial Intelligence Skills Practiced: Machine learning, deep learning, artificial neural networks
Machines can now interpret images, which has enormous benefits in medical imaging, gaming, surveillance, and law enforcement. With image processing techniques, AI applications can enhance photos, restore quality, change colors, and compress image sizes. AI-based image processing uses machine learning frameworks and deep learning models.
- Artificial Intelligence Skills Practiced: Machine learning
The goal of this project is to create a system that automatically classifies different music genres in audio files. To create this application, you will need a dataset of audio tracks, such as the GTZAN genre classification dataset, which consists of 1,000 audio files.
There are different methods and approaches to complete this music genre classification project. You can use convolutional neural networks, K-means clustering, K-nearest neighbors, or multiclass support vector machines.
Advanced Artificial intelligence Project Ideas
Once you can comfortably complete the projects above, it is time to move on to more advanced endeavors. The projects below delve deeper into the world of AI and will help you master the Markov Model, Bayesian networks, and the Lempel-Ziv and Word2Vec algorithms.
- Artificial Intelligence Skills Practiced: Machine learning-deep learning, convolutional neural networks, artificial neural networks
Building a facial emotion detection or facial recognition system is a great way to practice deep learning. Deep learning, a subset of machine learning, is a revolutionary technology that imitates human intelligence. It is widely used to create virtual assistants, driverless cars, and facial recognition applications. This project is all about creating a program capable of reading human facial expressions and classifying them.
- Artificial Intelligence Skills Practiced: Programming, machine learning
Plagiarism detectors have numerous benefits. Content creators can use them to check if someone is using their work without authorization, and editors can use one to determine if a writer has submitted stolen work.
In this project, you will build a Python Flask app that finds plagiarized content using Pinecone, a vector database. Building a plagiarism checker is a great way to advance your programming skills.
- Artificial Intelligence Skills Practiced: Machine learning, deep learning, programming
This project uses Python and deep learning to build a license plate detection and recognition system. The application recognizes the numbers in a license plate and records them using Python Pytesseract and OpenCV. This project has useful applications for security systems and traffic violation monitoring.
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- Artificial Intelligence Skills Practiced: Machine learning, programming
Popular streaming platforms like Netflix and Amazon Prime have a movie recommendation system that suggests titles based on the user’s viewing and search histories. This is indeed a very popular service, so developing skills in this area can benefit you dramatically from a professional standpoint. Also, consider taking on this project if you want to strengthen your skills in R, machine learning, and data science.
- Artificial Intelligence Skills Practiced: Machine learning, artificial neural networks, natural language processing
This Python project aims to create a model that can recognize emotions from a person’s voice. These types of models are commonly used by call centers to improve the customer experience. This project in particular uses the Librosa, Sklearn, and Soundfile libraries to analyze sound and music. You will also use the Ryerson Audio-Visual Database of Emotional Speech and Song dataset.
Artificial Intelligence Starter Project Templates
Artificial intelligence professionals, data science enthusiasts, and programming experts are a generous bunch. They share project instructions, source code, and other materials you can use to hone your AI skills. Below, you’ll find popular starter projects that are easy to follow.
- Fake News Detection Project. This project uses Python to build a model that determines whether news articles are real or fake. It uses Python’s Sklearn machine library to create a tfidfvectorizer, a prediction algorithm that converts raw data into a matrix. It also uses the PassiveAggressiveClassifier algorithm to run the data.
- Sign Language Recognition Project. This project creates a program that interprets sign language captured on camera. It uses Python’s OpenCV and Keras to create a sign detector. The project consists of three steps: creating the dataset, training the convolutional neural network on the captured dataset, and predicting the data.
- Gender Classification Model. This classification model can differentiate gender through fingerprint patterns using deep learning and convolutional neural network techniques as well as a dataset of 55,000 fingerprint images. With an accuracy of 99.72 percent, this model can be helpful in criminal investigations and biometric security.
- Contact Tracing Using Machine Learning. Contact tracing is used to identify the people that a person infected with a virus has come in contact with. It is a crucial technique when it comes to stopping the spread of viruses and infectious diseases. In this project, you will create a model for contact tracing using a density-based data clustering algorithm with the JSON dataset.
- Weather Prediction. This project helps you predict weather conditions with 99 percent accuracy. It uses a dataset of global temperatures taken from a prestigious research university.
Next Steps: Start Organizing Your Artificial Intelligence Portfolio
Including these projects in a digital portfolio is an excellent way to demonstrate your skills to employers. AI jobs are very much in demand. This means that getting a job in AI can be difficult and competitive. Here are some tips to help you create a portfolio that will stand out.
Highlight Your Specialization
In the world of AI, employers often look for a specific skillset. It is always a good idea to choose a specialization, whether that is machine learning techniques, computer vision, or data analytics, and to build your portfolio around it. This will give you an edge over candidates that dabble in multiple areas of AI but have no clear focus.
Include Only Your Best Work
Your portfolio shouldn’t include every project you have ever completed. Experts suggest it should consist of your five strongest projects. There may be projects that you are proud of that don’t make the cut. If this is the case, you can mention those projects to the hiring manager during your interview.
Blog About Your Projects
One way to show employers that you have the knowledge and skills needed for the position is to document your projects and experiments in a blog. A blog can act as a window into who you are as a professional, and employers can use it to learn about your skills and successes.
Artificial Intelligence Projects FAQ
Good AI projects for beginners are those that allow you to build systems with practical applications or that make a job more manageable. Good examples are handwriting recognition, voice recognition, and revenue forecasting systems as well as chatbots. These are all good projects to master the basics of machine learning and other key AI topics.
Some of the most common products around you that rely on AI are streaming services like Netflix, voice assistants like Alexa and Cortana, and self-driving cars.
You can start learning artificial intelligence and machine learning by yourself. There are many resources online to help you learn the fundamentals. You can also consider enrolling in an online course, or, if you are serious about a career in the field, attend a top coding bootcamp or artificial intelligence bootcamp.
The five big ideas of AI are perception, representation, reasoning, learning, and natural interaction. These five divisions are currently the guidelines for teaching the basics of artificial intelligence.
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