ai project topics and ideas for freshers and beginners detailed guide
Home Project Ideas Top 20 AI [Artificial Intelligence] Project Ideas In 2024

Top 20 AI [Artificial Intelligence] Project Ideas In 2024

Feb 1, 2024 3.5K Reads

Educational courses and formal training in the specialisation of artificial intelligence (AI) has become quite a popular choice of IT enthusiasts and students in recent times. A technical domain such as AI requires significant hands-on practice for practical skill development, due to which the importance of projects are paramount for students and learners developing AI skills. This is even more crucial for beginners in AI as it helps in putting newly learnt concepts to practice and explore the field to discover their area of interest. 

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But choosing a topic or idea for an AI project can be daunting, especially if the project is a part of the mandated curriculum in a degree/diploma/certificate. Through this blog, we have brought forth a number of AI project ideas for students (especially freshers) to try their hand on along with tips for selection of a topic and other pertinent details. 

So continue reading to explore a few of the trending and manageable project ideas and topics in artificial intelligence for freshers and beginners. 

What is Artificial Intelligence? 

In its essence, artificial intelligence or AI refers to the task of creating machines, specifically computer programs that can understand and consequently mimic human intelligence to perform tasks and analysis of information to produce human-like decisions and solutions to problems. AI technology goes beyond understanding and exploring the biological mechanisms through which human intelligence works to develop and enhance its own intelligence and capabilities beyond. 

Artificial intelligence integrates aspects like complex datasets, computer science technology, machine learning and deep learning to enhance decision-making and problem-solving capabilities of machines and computer softwares. 

With newer technologies driving growth and innovation in AI, there have come up a number of significant breakthroughs in the field ranging from robust generative AI models, natural language processing models (NLP), weak AI models designed for nuanced performance in specific domains and strong AI with multimodal capacities.

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AI softwares and systems work by reading and analysing large datasets, which are usually labelled training data sets, which is further analysed to find correlations and patterns, which are then used by the AI software to produce solutions to problems. With a focus on a number of cognitive functions in humans such as learning, reasoning, creativity, self-improvement and so on, the depths of understanding AI can be extremely fascinating for learners. 

Top 20 Project Topics and Ideas in Artificial Intelligence 

Find 20 of the trending and interesting project ideas in the domain of AI that you can consider taking up if you are a beginner in AI. These project topics come with a combination of worthy exploratory scope and manageable difficulty level. 

1.  Stock Price Prediction Application


A stock prediction application is an AI project that has a manageable difficulty level for students who have just begun their journey in learning about artificial intelligence. This project includes coding in a dynamic language as Python and includes a CSV dataset. The stock prediction application uses training datasets of historical stock records to analyse the patterns of share rise and fall and make predictive analysis based on available data, providing a well-researched supportive framework to stock enthusiasts. Certain key details and an open source code for preparing such a predictor application have been provided below.

2.  AI Chatbot

AI chatbots have become a raging software/tool for use which utilise the generative AI principles. AI chatbots are not only highly useful for users seeking conversational opportunities, making enquiries or seeking informational support but also quite interesting to design as AI projects for AI students. The programming language of Java or Python can be used to prepare a simplistic AI chatbot by a beginner. Training data and datasets for AI chatbots include question-answer datasets which are read by the bot and used further to identify patterns of word usage in human conversation and use the same to generate responses that mimic human conversational language. Further details and a source code for reference to prepare an AI chatbot project have been given below.  

  • Language: Java/Python
  • Data Set: Question-Answer Datasets
  • Source Code: Alan-AI

3.  Loan Eligibility Prediction

A loan eligibility prediction software/application is based on an AI model that can read and analyse large datasets of borrowers, their loan applications and the status of loan approval. It is quite a useful AI project which can find significant utility in the banking sector to provide informational support to loan approvers based on large sets of data. The project includes Python programming, along with measures of cybersecurity and privacy for the data accessed by the predictor software. Further details and a source code for creating an AI project on loan eligibility have been provided below. 

4.  AI-Powered Search Engine


An AI-powered search engine is a smart search engine that is specially equipped with AI technologies to provide more individualised services and relevant searches to users by evaluating the intent of the user’s search based on machine learning and NLP capacities. This can be quite a fitting AI project for a beginner as it has moderate difficulty level and involves a dynamic programming language like Python for creation. Validation datasets are mainly used for this project. Find below the further details about an AI project on AI-powered search engine. 

  • Language: Python
  • Data Set: Validation Datasets
  • Source Code: AI-Search

5.  Consumer Sentiment Analysis

A consumer sentiment analysis is based upon a model which can analyse content related to emotional expression, whether on a social media platform, a review platform or in general textual inputs to identify words and expressions related to sentiments and emotions and further analyse the underlying sentiment being portrayed in the input. These softwares are highly useful for ease of collecting and summarising feedback on products and services from consumers and accordingly improving services. Python is a convenient programming language for developing this project. More details have been provided below for creation of a sentiment analysis model. 

6.  Customer Recommendation

A customer recommendation model or software is an AI-powered tool that makes advanced and smart suggestions about products based on a number of pertinent factors. AI-powered customer recommendation softwares are highly useful in e-commerce platforms that make product suggestions to customers based on filters such as brand, product pricing, warranty/guarantee factors, product specifications etc. in addition to suggesting additional products to buy based on algorithms set in the suggestion software. Further details about the project have been provided below. 

7.  Voice-Based Virtual Assistant


A voice-based virtual assistant is a smart assistant software that can perform a variety of digital tasks  and operations based on the inputs of the user in a voice format. Such an assistant is equipped with NLP capacities that can understand voice commands as well as be connected and synced across devices. Voice based assistants are designed to be accessible across operating platforms and various devices. Such a program can be prepared with a programming language like Python. However, this project includes a certain level of proficiency in key domains of AI principles and machine learning and hence may be comparatively a little complex for beginners. However, with sufficient practice and exposure to AI development, it can be mastered with ease. Key details and an open source code for the voice-based virtual assistant project are provided below. 

8.  Facial Recognition Software 

A facial recognition software is an extended and nuanced application of deep learning principles of artificial intelligence that can be tapped into by a student of AI. A facial recognition software uses deep learning principles to spot faces among a crowd and further identify/recognise the face based on datasets fed into the system of the model. Facial recognition softwares include the use of labelled faces in the wild (LFW) datasets and can be prepared through Python. A source code that can be used in the development of a facial recognition software has been provided below. 

9.  Plagiarism Checker Application 

A plagiarism checker application is an important domain where AI capabilities can make massive contributions. For instance, with a large number of paraphrasing tools available to evade plagiarism, students or professionals often get away with unduly plagiarising others’ works by changing sentence structures while retaining the essence of the work. In such a case, developing a plagiarism checker and detection program that is equipped with AI technologies that can identify plagiarism despite basic changes in sentence structure can be an innovative breakthrough. Python can be used for developing such a program along with a CSV file for datasets. Such a program can utilise text mining technologies to provide a metric for percentage of plagiarism in a piece. A few key details related to the creation of a plagiarism checker application have been provided herein.

10.  Real-Time Translation Application


Real-time translation tools and applications are highly useful in a number of cases, especially those involving interactions with individuals speaking an unknown language, as is the case of many tourism agencies, international businesses or accessing textual content in unknown languages. A real-time translation tool uses machine learning and NLP advancements to convert text in one language to another language in real-time settings. Such a project can be prepared for a niche translatory use in any given two languages by a beginner, or at a more advanced level in translations across multiple languages. Further key details about creating this project have been provided below. 

11.  Applications of NLP

This a theoretical and review project that involves research about a variety of AI models rather than creation of an AI model itself. A project that analyses the applications of Natural Language Processing (NLP) in a variety of models of AI and its usage in various use cases comprises the essence of this project idea. Natural Language Processing (NLP) is a field that brings together the functionalities and applications of human linguistics and computer technologies to enable machines and computers to mimic human language (both in terms of production and analysis). A detailed project, especially a review-based research on the various applications that NLP technologies finds in the field of AI as well as a comment on the strengths, weaknesses and further developments needed in the field can be a useful contribution surrounding research in AI that can be an attractive and valuable addition to one’s resume. 

12.  Lane Line Detection for Driving


Lane line detection in driving is an important aspect having implications for the field of automatic driving, which is expected to drive future breakthroughs in traffic management. Lane line detection softwares can effectively identify the lanes in which a vehicle is currently driving using GPS and computer vision systems as well as ensure that the given vehicle stays in its lane while driving. Although it is easy to deploy such an AI model by integrating machine learning technologies with AI principles, the project is a high stakes one due to the safety issues associated with it. Hence, the AI model being prepared must be done with sufficient attention. The student must ensure creating an all-round machine learning equipped model that can handle adjustments and aspects related to driving such as traffic, presence of other vehicles in the lane, light adjustments and so on. Find some more details related to building a lane driving detector AI model. 

13.  AI Health Engine

Managing and analysing vast amounts of health data can be a tedious task in a country like India that runs short of available medical and healthcare professionals at the frontline. To address such circumstances, an AI enthusiast/beginner can create an AI health engine that can effectively read, analyse and manage vast datasets pertaining to health records and medical records of patients. Such a tool can have an added feature of summarising and drawing smart insights from such health-related datasets and suggesting healthcare options and suggestions for diagnosis. However, the stakes of such medical advice and health suggestions being quite high, the model should be prepared with due ethical considerations and all-round training for providing closest to accurate suggestions. Python can be used to create such a project and a sample source code has been provided herein that can be referred to for working on it. 

14.  Spam Identification Software 


Another quite useful and hands-on project to try for skill development is to develop a spam identification software that can detect spam content on platforms like social media and review platforms. Such software can be prepared through the use of APIs of social media platforms such as Instagram, Facebook, YouTube spam collection etc. as datasets, which can be integrated with machine learning and filtering algorithms for identification of spam comments, reviews, content, accounts etc. on such platforms. This project is a mix of fascinating and effective skill building exposure for beginners as it combines the search for datasets and integration of machine learning technologies to build an AI model with huge utility in the present digital space. Find key details about the project including a source code to create the model given below. 

15.  AI Art Generator Tool 

Preparing an art generator tool can be an interesting as well as enriching experience with respect to the exposure to AI technologies it provides. An AI art generator tool can include various features such as basic templates for the format of artwork desired, input channel to receive prompts for art generation by the user and other related specifications. An art generator model works by integrating deep learning principles with algorithms and dataset and stacks. Python can be a dynamic and helpful programming language to develop such an application. An Art by AI dataset can be used for creating the model for this project. Although a slightly more advanced project domain for a novice, this project can provide excellent exposure to the vast avenues of AI and help the student in skill building as well as exploration of their interests. 

16.  Smart Textual Summarisation Software

A textual summarisation tool is a niche tool that can be developed using AI and related technologies to address the “too long didn’t read” problem faced by many students, researchers and professionals. A smart textual summarisation model can have many utilities for students as well as working professionals for summarising research articles, textual coursework, meetings, class notes etc. Such a model or software can be created by the use of JavaScript and can effectively address the concerns of summarising texts and other formats of verbal data by not only analysing their superficial content but also inferring the implications and implicit meanings of texts, an area that AI can vastly contribute to. Find more details and a source code for creating a text summary tool with AI-powered technologies as given below. 

17.  College Placement System 

An interesting project to work on using AI technologies is to develop a software for college or campus placements for a higher educational institution (HEI). Such software should be designed to address the placement needs of students, the administrative needs of the college and the hiring/recruiting needs of partner organisations. Accordingly, the AI-powered software can be prepared to incorporate various algorithms and ML and deep learning technologies for it to effectively analyse student profiles, organisational profiles, posted job descriptions and so on to align them and provide the best-suited suggestions for placements to the organisations and students. Such software requires the use of a programming language like JavaScript, HTML or CSS for frontend development whereas backend development can be done through the use of MySQL. Find certain key details and an open source link for this project given below. 

18.  Doctor’s Appointment Booking System


A doctor’s appointment booking system is an AI-powered software, much like a virtual assistant, that is programmed and trained to manage the appointments, set appropriate reminders, provide dates and timings for appointments, manage the calendars of the doctor and so on in a synced fashion. Such an application can be developed using Java (or Python/HTML/MySQL etc.)  and using MySQL or Django for the framework of the model. A doctor’s appointment booking system must also include aspects like safely protecting the privacy of patients’ entered details as well as taking inputs from patients trying to book an appointment with the doctor about their preferred timings and matching them with the medical professional’s schedule effectively to prevent scheduling clashes. Find more details about the project and an open source code for preparing it as provided below. 

19.  Traffic Sign Recognition Software 

A traffic sign recognition software is a software that can be installed in automobiles to detect traffic signals and provide the information to the driver. It also has implications for effective signal detection at road crossings for automatic vehicles. Such a project can utilise a GTSRB dataset combined with programming in Python to provide an all-round service and feedback loop powered by AI. A sample open source code for the project has been provided herein.

20.  Smart Music Recommendation Software


An AI model or software that can smartly assess the musical preferences, choices, and dislikes of a person can be created by using AI powered technology that analyses past musical choices and histories in a platform to provide individualised suggestions. Such AI-powered technologies are already being utilised by many musical streaming applications, and can provide good exposure to a student of AI in related domains. This project would involve the deployment of CNN algorithms and use of platforms like Django and MySQL in addition to Python as the programming language for the model. A song describer dataset or an OpenCV or Dlib library can be used for working on the project. An advancement in such song recommending software can further be a song recommendation algorithm that can effectively detect the facial expressions of a user to suggest songs. Further details about the project along with an open source code for creating it have been provided below for reference.

Why is an AI Project Important & How to Select the Right Project Topic?

An AI project, like any other project for a course, can be a highly valuable channel for progressing growth and developing working skills in the domain. There are a number of benefits and positive sides to pursuing a project in the domain of AI, a few of which have been delineated herein. 


  • Adds Value to Portfolio

A primary benefit of indulging in a project in the domain of AI is the value it contributes to your portfolio. Having an appealing and impressive portfolio outlining your major projects and practical endeavours in AI can add a significant value to your profile for the future and provide a competitive leverage to you for future career opportunities. Working on portfolio building from the initial years by taking up meaningful and interesting projects in AI can contribute to the skill growth and profile building of the student. 

  • Important for Hands-On Skill Building

Another major advantage of taking up projects in AI is the exposure it provides to the learner to develop their hands-on working skills, which are extremely important to support a successful career in a technical domain such as IT and AI. Taking up projects that match the proficiency levels of the learner can help them practise learnt skills and motivate them towards further exploration and development of innovative projects. 

  • Application of Learned Knowledge

As has already been emphasised upon, thriving in technical fields like IT and AI do not suffice with merely gaining academic knowledge of the field. Developing practical skills and utilising the learnt concepts in actual practical implementation in projects is highly important to test one’s learning against actual practical practice. 

  • Fostering Skills of Creativity & Innovation 

Working on projects and creating one’s own AI softwares and programs can be highly enriching experiences to foster creativity and innovation. Technology, especially AI, is a domain that requires constant innovation to achieve breakthroughs and devise new pathways to further human progress. Hence, projects can provide a useful outlet to channel one’s creativity and experiment with their skills as well as explore newer arenas pertaining to AI.

  • Excellent Training for Future Career Opportunities

The result of engaging in meaningful projects that help in skill development is that the student, by the period of course completion, gains proficiency in a number of domains within AI and has a leverage over competitors. Having honed working skills in various domains of AI programming can be quite useful for career ventures and exploring appealing job opportunities in the future. 

  • Gaining Deeper Understanding of Ethical Implications

This is another lesser explored aspect of pursuing projects in AI. The introduction of AI technologies since their inception have been associated with the importance of making ethical considerations for impact on humans, concerns for safety of users, protection against cyberthreats and so on. Practising AI skills through projects can provide students and learners the opportunity to identify the potential ethical considerations that their project/application/software may entail. 

Thus, it can be seen that engaging in projects in the domain of AI can be personally enriching and beneficial for professional skill development as well. 

However, despite the various benefits associated with taking up a project in artificial intelligence, the process of selecting the right topic or project idea is challenging for most students. But a consideration of certain key aspects and concerns can help make a more informed choice for students and end up with a project that is both motivating to conduct and is beneficial for skill building. A few of these tips have been mentioned below.

  • Carefully assess your interest areas and major areas of focus in the domain of artificial intelligence. Choosing a topic that is congruent with your academic interests would help you stay motivated through the period of completing the project and bounce back from setbacks. 
  • Assessing the novelty of the idea you are interested in is also important–merely replicating a sufficiently explored area of AI or a project may not be very conducive for skill growth. Coming up with a project idea that is novel or unique in some aspect and contributes to the overall field of AI is quite essential for portfolio building. 
  • One must evaluate the difficulty level of a given project topic based upon their proficiency and grasp over various programming languages and dataset processing associated with the creation of the project. Taking up a project that matches your level of proficiency with AI tools and softwares will help in starting with a realistic goal and keeping oneself engaged with the learning process. 
  • Most importantly, assessing a topic’s alignment with your future career goals is important for effective portfolio development and gaining skills which would be fruitful for career progression. 
  • Consult with your peers and faculty about the topic of your interest as such reviews and consultation can provide a fruitful channel for discovering further ideas and innovative AI topics for projects as well as realistically assess the utility and originality of the project.  

Thus, although selecting the project topic can be a tough task, keeping these tricks in mind can help make the student a more directed and focused decision about the project topic they wish to go with. 

Best Platforms to Develop AI Projects 

Listed below are a few of the top platforms to use for developing AI projects as per latest trends and advanced features. 

  • Google Cloud AI Platform: Offered with the options of integrating one’s models with TensorFlow and Scikit-Learn, the Google Cloud AI Platform allows for end-to-end AI model development in the Google Cloud ecosystem. This software is useful for training and deploying machine learning models. 
  • Microsoft Azure ML: This is a cloud-based machine learning model that allows for integration with Azure services and can be used for functions such as building AI models and further training and deploying them. 
  •  IBM Watson: The AI building platform for IBM, Watson, is specifically designed to allow the building and deployment of AI applications and comes with a number of APIs for incorporation of AI features into developed applications. It has features to support computer vision, natural language processing and data analytics. 
  • TensorFlow: TensorFlow is one the primary and nuanced platforms for building AI projects that was introduced by Google. It is suitable for use for creating various machine learning and in-depth learning models (including neural networks) and can be used effectively for creating and training AI models by both experts and beginners. 
  • PyTorch: PyTorch is an open-source framework that provides an efficient network of community and extensive documentation. It is a platform introduced by Facebook’s Artificial Intelligence Research lab and is well-known for its suitability for research and experimentation with AI projects and models. 
  • Keras: This is a highly advanced API suitable for advanced neural networks and experimentation with neural architectures. It can be used for rapid prototyping and in integration with various other platforms such as TensorFlow, Theano, or Microsoft Cognitive Toolkit (CNTK).
  • FastAI: This is an AI platform built to suit the needs of beginners with respect to accessing and training deep learning AI models. It simplifies the training of high quality models by offering easy-to-use prebuilt architectures. 

Some other prominent platforms available for use to build AI projects include those like H2O.ai,  Scikit-learn, OpenNN, Infosys Nia, Google Cloud Console etc. 


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As can be seen, there are a number of innovative and interesting project ideas that you can consider taking up as a fresher or beginner in the AI domain. There are a number of projects ranging from an easy to a high level of difficulty that can help the student to complete or develop their own AI model for curricular or extracurricular purposes. Pursuing projects in AI regularly can be quite fruitful for hands-on skill development and portfolio building. Additionally, taking such projects up would foster innovative and creative thinking and help the student explore newer avenues in AI. 

FAQs (Frequently Asked Questions)

Some of the best AI project topics include those like a stock price prediction application, AI chatbot, a consumer sentiment analysis model, plagiarism checker application etc. 

Some of the easy AI project ideas include building a house price predictor, a stock price predictor, making a chatbot, a simple customer recommendation application etc. 

You should consider taking up AI projects since they are quite helpful in hands-on skill building, practical exposure, exploration and innovation as well as effective portfolio building for future professional prospects. 

Depending on the complexity of the project and the proficiency level of the student, an AI project can take anywhere between 1 month to 6 months to complete, as a beginner. Further time may be needed for more complex projects.

While AI projects require significant programming and model building, with adequate practice as well as ready to use source codes and architectural models available, one can master creating AI models and projects within a short span of time. 

Some of the prominent platforms to use for creating AI projects include TensorFlow, Google Cloud AI Platform, Microsoft Azure ML, Keras etc. 

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