Best AI tools for< University Student >

LearnFast AI Physics Solver is an advanced AI-powered application designed to provide instant and accurate solutions to physics problems. It offers real-time physics solutions accessible anytime, anywhere, with support for text input, image uploads, and file formats. Users can benefit from free daily problem-solving, continuous upgrades for AI models, and a user-friendly interface. The application is suitable for high school students, university physics students, tutors, educators, lifelong learners, and physics enthusiasts.

EssayGet is an AI tool designed to assist users in writing academic papers by providing features such as humanizing text, ensuring plagiarism-free content, generating in-text citations, and creating comprehensive outlines. The tool utilizes advanced algorithms to refine and rephrase writing, making it undetectable by top AI detectors like Turnitin, GPTZero, and Originality.ai. EssayGet aims to help students maintain the authenticity and originality of their work effortlessly, trusted by top university students for its reliable services.

ScholarRoll is the first of its kind scholarship search tool that smartly matches you to millions of $'s in niche scholarships based on relevance and winning chances. Manage your entire scholarship journey in one secure platform with our comprehensive upto date database, Al powered search, tracking tool, and timely reminders.

Gizmo is an AI-powered learning application designed to make studying easy and enjoyable for students of all levels. It offers A.I. quizzes that help users learn and retain information effectively. The app is created by Cambridge alumni and has gained popularity among students for its innovative approach to learning. With features like spaced repetition, active recall, and the ability to turn study materials into flashcards, Gizmo aims to enhance the learning experience and improve academic performance.

Hiree365 is a comprehensive campus recruitment platform that connects universities, students, employers, and governments to improve graduate employability. It offers a range of features to help universities manage campus recruitments, employers attract better candidates, and students find jobs related to their university courses. Hiree365 also provides AI-powered job screening and matching technology to help employers find the perfect match for any job posting.

Elements of AI is a free online educational platform that offers courses on artificial intelligence for non-experts. Created by MinnaLearn and the University of Helsinki, the platform aims to demystify AI by providing theory, practical exercises, and a comprehensive understanding of AI concepts. With over 1 million students from 170 countries, the courses cover topics like Introduction to AI and Building AI, encouraging a broad audience to learn about AI's impact on society and how to create AI methods.

Northwestern Now is the official news source for Northwestern University. It provides coverage of the University's people, programs, and research. The website includes stories on a wide range of topics, including science and technology, culture and politics, health and medicine, and campus and community life. Northwestern Now also features expert viewpoints, student voices, and announcements and news.

Studyquick is an AI-powered tool designed for students to streamline their learning process. By uploading university scripts, lectures, videos, and audio recordings, users can benefit from AI-generated study notes, practice exams, podcasts, and a virtual AI tutor. Studyquick aims to revolutionize the way students prepare for exams by providing personalized and efficient study materials tailored to individual needs. With features like KI-generated study notes, personalized study assistance, and quick access to study materials, Studyquick offers a comprehensive solution for students looking to enhance their learning experience.

Paper Interpreter is an AI application developed by Daichi Konno, a medical doctor and neuroscientist at the University of Tokyo. The application allows users to input a PDF or URL of a research paper and receive a simplified explanation generated by an AI assistant. It gained significant popularity shortly after its release, ranking 6th globally and 1st in Japan in terms of usage. The tool aims to make academic research more accessible and understandable to a wider audience.

The Harvard Crimson is a renowned university newspaper established in 1873, providing daily news, opinion pieces, arts and culture coverage, blogs, multimedia content, and sports updates. The publication covers a wide range of topics related to Harvard University and its community, including faculty news, student activism, campus events, and academic developments. With a focus on diversity and inclusion, The Harvard Crimson aims to inform and engage its readers with insightful and thought-provoking content.

Artificial Intelligence: Foundations of Computational Agents, 3rd edition by David L. Poole and Alan K. Mackworth, Cambridge University Press 2023, is a book about the science of artificial intelligence (AI). It presents artificial intelligence as the study of the design of intelligent computational agents. The book is structured as a textbook, but it is accessible to a wide audience of professionals and researchers. In the last decades we have witnessed the emergence of artificial intelligence as a serious science and engineering discipline. This book provides an accessible synthesis of the field aimed at undergraduate and graduate students. It provides a coherent vision of the foundations of the field as it is today. It aims to provide that synthesis as an integrated science, in terms of a multi-dimensional design space that has been partially explored. As with any science worth its salt, artificial intelligence has a coherent, formal theory and a rambunctious experimental wing. The book balances theory and experiment, showing how to link them intimately together. It develops the science of AI together with its engineering applications.

Carnegie Mellon University's School of Computer Science (SCS) is a world-renowned institution dedicated to advancing the field of computer science and training the next generation of innovators. With a rich history of groundbreaking research and a commitment to excellence in education, SCS offers a comprehensive range of programs, from undergraduate to doctoral levels, covering various specializations within computer science. The school's faculty are leading experts in their respective fields, actively engaged in cutting-edge research and collaborating with industry partners to solve real-world problems. SCS graduates are highly sought after by top companies and organizations worldwide, recognized for their exceptional skills and ability to drive innovation.

The Institute of Computer Science at the University of Würzburg is a leading research and teaching institution in the field of computer science. With 29 professors and around 200 employees, the institute offers a wide range of study programs, including bachelor's, master's, and teaching degrees. The institute's research focuses on four main areas: Computing, Systems and Networks; Artificial Intelligence and Data Science; Human-Centered Computing; and Aerospace and Robotics.

Duckietown is a platform for delivering cutting-edge robotics and AI learning experiences. It offers teaching resources to instructors, hands-on activities to learners, an accessible research platform to researchers, and a state-of-the-art ecosystem for professional training. Duckietown's mission is to make robotics and AI education state-of-the-art, hands-on, and accessible to all.

Bethge Lab is an AI research group at the University of Tübingen focusing on Neuro AI - Autonomous Lifelong Learning in Machines and Brains. They develop machine learning tools for neural data analysis and draw inspiration from the brain to address key problems in machine learning. Their research includes representation learning, probabilistic inference, generative modeling, behavioral data analysis, and neural data analysis. Additionally, they explore AI sciencepreneurship and collaborate with startups. Bethge Lab aims to advance the understanding of autonomous learning and develop economically feasible solutions for long-term human needs.

The Visual Computing & Artificial Intelligence Lab at TUM is a group of research enthusiasts advancing cutting-edge research at the intersection of computer vision, computer graphics, and artificial intelligence. Our research mission is to obtain highly-realistic digital replica of the real world, which include representations of detailed 3D geometries, surface textures, and material definitions of both static and dynamic scene environments. In our research, we heavily build on advances in modern machine learning, and develop novel methods that enable us to learn strong priors to fuel 3D reconstruction techniques. Ultimately, we aim to obtain holographic representations that are visually indistinguishable from the real world, ideally captured from a simple webcam or mobile phone. We believe this is a critical component in facilitating immersive augmented and virtual reality applications, and will have a substantial positive impact in modern digital societies.

Shadowing AI is an interview practice platform that provides users with continuous feedback. It is designed to help individuals improve their interview skills by simulating real interview scenarios and offering personalized feedback. By using this platform, users can practice answering common interview questions, receive feedback on their responses, and enhance their overall interview performance. Shadowing AI aims to boost users' confidence and readiness for job interviews through its interactive and user-friendly interface.

Jesse Zhang's personal website showcases his background in engineering, particularly in web development, AI/ML, and mathematics. He highlights his education at Harvard University and internships at renowned companies like Citadel, Google, and Intel. Zhang also mentions his entrepreneurial ventures, including founding Lowkey, which was acquired by Niantic, and his current work on a new company. The website features various projects he has worked on, such as real-time multiplayer implementations of Camel Up and Bananagrams, a financial data visualization tool, and a demo of Zero-Knowledge proofs in the game Mastermind. Additionally, Zhang shares his interest in writing math contest problems and his involvement in angel investing through Sequoia Scouts and Neo.

Integrail is an AI tool that simplifies the process of building AI applications by allowing users to design and deploy multi-agent applications without the need for coding skills. It offers a range of features such as integrating external apps, optimizing cost and accuracy, and deploying applications securely in the cloud or on-premises. Integrail Studio provides access to popular AI models and enables users to transform business workflows efficiently.

TEAMCAL AI is the world's most advanced team scheduling software powered by AI. It simplifies coordination with third parties, across companies, teams across time zones, and applications effortlessly. The application offers features like AI scheduling in seconds, multi-team collaboration, seamless integration with existing workflow tools, and integrated solutions designed for specific business use cases. With various pricing plans catering to different business needs, TEAMCAL AI aims to optimize team scheduling, reduce manual errors, and enhance productivity.

EduChat is a large-scale language model-based chatbot system designed for intelligent education by the EduNLP team at East China Normal University. The project focuses on developing a dialogue-based language model for the education vertical domain, integrating diverse education vertical domain data, and providing functions such as automatic question generation, homework correction, emotional support, course guidance, and college entrance examination consultation. The tool aims to serve teachers, students, and parents to achieve personalized, fair, and warm intelligent education.

This repository contains slides, notebooks, and data for the Machine Learning University (MLU) Responsible AI class. The mission is to make Machine Learning accessible to everyone, covering widely used ML techniques and applying them to real-world problems. The class includes lectures, final projects, and interactive visuals to help users learn about Responsible AI and core ML concepts.

This repository contains course materials for T81 559: Applications of Generative Artificial Intelligence at Washington University in St. Louis. The course covers practical applications of Large Language Models (LLMs) and text-to-image networks using Python. Students learn about generative AI principles, LangChain, Retrieval-Augmented Generation (RAG) model, image generation techniques, fine-tuning neural networks, and prompt engineering. Ideal for students, researchers, and professionals in computer science, the course offers a transformative learning experience in the realm of Generative AI.

MediaAI is a repository containing lectures and materials for Aalto University's AI for Media, Art & Design course. The course is a hands-on, project-based crash course focusing on deep learning and AI techniques for artists and designers. It covers common AI algorithms & tools, their applications in art, media, and design, and provides hands-on practice in designing, implementing, and using these tools. The course includes lectures, exercises, and a final project based on students' interests. Students can complete the course without programming by creatively utilizing existing tools like ChatGPT and DALL-E. The course emphasizes collaboration, peer-to-peer tutoring, and project-based learning. It covers topics such as text generation, image generation, optimization, and game AI.

This repo contains official implementations of **Coach AI Badminton Project** from Advanced Database System Laboratory, National Yang Ming Chiao Tung University supervised by Prof. Wen-Chih Peng. The high-level concepts of each project are as follows: 1. Visualization Platform published at _Physical Education Journal 2020_ aims to construct a platform that can be used to illustrate the data from matches. 2. Shot Influence and Extension Work published at _ICDM-21_ and _ACM TIST 2022_ , respectively introduce a framework with a shot encoder, a pattern extractor, and a rally encoder to capture long short-term dependencies for evaluating players' performance of each shot. 3. Stroke Forecasting published at _AAAI-22_ proposes the first stroke forecasting task to predict the future strokes of both players based on the given strokes by ShuttleNet, a position-aware fusion of rally progress and player styles framework. 4. Strategic Environment published at _AAAI-23 Student Abstract_ designs a safe and reproducible badminton environment for turn-based sports, which simulates rallies with different angles of view and designs the states, actions, and training procedures. 5. Movement Forecasting published at _AAAI-23_ proposes the first movement forecasting task, which contains not only the goal of stroke forecasting but also the movement of players, by DyMF, a novel dynamic graphs and hierarchical fusion model based on the proposed player movements (PM) graphs. 6. CoachAI-Challenge-IJCAI2023 is a badminton challenge (CC4) hosted at _IJCAI-23_. Please find the website for more details. 7. ShuttleSet published at _KDD-23_ is the largest badminton singles dataset with stroke-level records. - An extension dataset ShuttleSet22 published at _IJCAI-24 Demo & IJCAI-23 IT4PSS Workshop_ is also released. 8. CoachAI Badminton Environment published at _AAAI-24 Student Abstract and Demo, DSAI4Sports @ KDD 2023_ is a reinforcement learning (RL) environment tailored for AI-driven sports analytics, offering: i) Realistic opponent simulation for RL training; ii) Visualizations for evaluation; and iii) Performance benchmarks for assessing agent capabilities.

The 'Dive into Large Language Models' series programming practice tutorial is an extension of the 'Artificial Intelligence Security Technology' course lecture notes from Shanghai Jiao Tong University (Instructor: Zhang Zhuosheng). It aims to provide introductory programming references related to large models. Through simple practice, it helps students quickly grasp large models, better engage in course design, or academic research. The tutorial covers topics such as fine-tuning and deployment, prompt learning and thought chains, knowledge editing, model watermarking, jailbreak attacks, multimodal models, large model intelligent agents, and security. Disclaimer: The content is based on contributors' personal experiences, internet data, and accumulated research work, provided for reference only.

rLLM (relationLLM) is a Pytorch library for Relational Table Learning (RTL) with LLMs. It breaks down state-of-the-art GNNs, LLMs, and TNNs as standardized modules and facilitates novel model building in a 'combine, align, and co-train' way using these modules. The library is LLM-friendly, processes various graphs as multiple tables linked by foreign keys, introduces new relational table datasets, and is supported by students and teachers from Shanghai Jiao Tong University and Tsinghua University.

Sorrentum is an open-source project that aims to combine open-source development, startups, and brilliant students to build machine learning, AI, and Web3 / DeFi protocols geared towards finance and economics. The project provides opportunities for internships, research assistantships, and development grants, as well as the chance to work on cutting-edge problems, learn about startups, write academic papers, and get internships and full-time positions at companies working on Sorrentum applications.

LearnHouse is an open-source platform that allows anyone to easily provide world-class educational content. It supports various content types, including dynamic pages, videos, and documents. The platform is still in early development and should not be used in production environments. However, it offers several features, such as dynamic Notion-like pages, ease of use, multi-organization support, support for uploading videos and documents, course collections, user management, quizzes, course progress tracking, and an AI-powered assistant for teachers and students. LearnHouse is built using various open-source projects, including Next.js, TailwindCSS, Radix UI, Tiptap, FastAPI, YJS, PostgreSQL, LangChain, and React.

2025-AI-College-Jobs is a repository containing a comprehensive list of AI/ML & Data Science jobs suitable for college students seeking internships or new graduate positions. The repository is regularly updated with positions posted within the last 120 days, featuring opportunities from various companies in the USA and internationally. The list includes positions in areas such as research scientist internships, quantitative research analyst roles, and other data science-related positions. The repository aims to provide a valuable resource for students looking to kickstart their careers in the field of artificial intelligence and machine learning.

A massive list including a huge amount of products and services that are completely free! ⭐ Star on GitHub • 🤝 Contribute # Table of Contents * APIs, Data & ML * Artificial Intelligence * BaaS * Code Editors * Code Generation * DNS * Databases * Design & UI * Domains * Email * Font * For Students * Forms * Linux Distributions * Messaging & Streaming * PaaS * Payments & Billing * SSL

The Conversational Azure OpenAI Accelerator is a tool designed to provide rapid, no-cost custom demos tailored to customer use cases, from internal HR/IT to external contact centers. It focuses on top use cases of GenAI conversation and summarization, plus live backend data integration. The tool automates conversations across voice and text channels, providing a valuable way to save money and improve customer and employee experience. By combining Azure OpenAI + Cognitive Search, users can efficiently deploy a ChatGPT experience using web pages, knowledge base articles, and data sources. The tool enables simultaneous deployment of conversational content to chatbots, IVR, voice assistants, and more in one click, eliminating the need for in-depth IT involvement. It leverages Microsoft's advanced AI technologies, resulting in a conversational experience that can converse in human-like dialogue, respond intelligently, and capture content for omni-channel unified analytics.

Awesome AI is a curated list of artificial intelligence resources including courses, tools, apps, and open-source projects. It covers a wide range of topics such as machine learning, deep learning, natural language processing, robotics, conversational interfaces, data science, and more. The repository serves as a comprehensive guide for individuals interested in exploring the field of artificial intelligence and its applications across various domains.

A collection of papers related to knowledge distillation of large language models (LLMs). The repository focuses on techniques to transfer advanced capabilities from proprietary LLMs to smaller models, compress open-source LLMs, and refine their performance. It covers various aspects of knowledge distillation, including algorithms, skill distillation, verticalization distillation in fields like law, medical & healthcare, finance, science, and miscellaneous domains. The repository provides a comprehensive overview of the research in the area of knowledge distillation of LLMs.

This repository aims to promote global equality for individuals pursuing a PhD in NLP by providing resources and information on various aspects of the academic journey. It covers topics such as applying for a PhD, getting research opportunities, preparing for the job market, and succeeding in academia. The repository is actively updated and includes contributions from experts in the field.

The 'llms' repository is a comprehensive guide on Large Language Models (LLMs), covering topics such as language modeling, applications of LLMs, statistical language modeling, neural language models, conditional language models, evaluation methods, transformer-based language models, practical LLMs like GPT and BERT, prompt engineering, fine-tuning LLMs, retrieval augmented generation, AI agents, and LLMs for computer vision. The repository provides detailed explanations, examples, and tools for working with LLMs.

Awesome-Embedded is a curated list of resources for embedded systems enthusiasts. It covers a wide range of topics including MCU programming, RTOS, Linux kernel development, assembly programming, machine learning & AI on MCU, utilities, tips & tricks, and more. The repository provides valuable information, tutorials, and tools for individuals interested in embedded systems development.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

I assist in crafting essay introductions for university students.

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Guides students through university applications, with a focus on essays and interviews.

Your world-class Economics tutor, powered by students and instructional material from the University of Chicago's highly-ranked Economics program.

City University of Hong Kong Virtual Assistant

A university-level paper grader and advisor, specialized in APA format

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Expert on International Business lectures, using specific course material for detailed responses.

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A guide for developing university-focused digital startup accelerator programs.

Research-backed AI on hallucinogens, offering insights from university studies and expert opinions.

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Carrefour d'innovation et de pédagogie universitaire de l'UQAM