Courses

Learn how to create a cost-free AI research assistant using Ollama AI in this comprehensive 10-minute tutorial. Discover the process of searching for research articles, converting them into embeddings, storing them in a Quadrant database, and using a Large Language Model to answer questions. Follow step-by-step instructions for installation, setup, and coding to build a user-friendly interface. Gain insights into streamlining your research process, from article searches to obtaining specific insights, whether you're a beginner or experienced developer.

Explore the innovative applications of Human Language Technology (HLT) in research assistance during this 28-minute conference talk from #HLTCon 2018. Discover how Diffeo envisions software as a collaborative teammate, aligning with user goals to provide more than just efficient tooling. Learn about novel HLT implementations, including email response assistance, web browser tab management, and cross-surface interactions. Delve into the concept of a Research Assistant that organizes notes, facilitates sharing and collaboration, and generates relationship graphs and hierarchical clustering. Gain insights into user feedback integration and action recommendations, showcasing the potential of HLT to revolutionize productivity and teamwork in research environments.

Learn how Google DeepMind built Gemini Deep Research, a personal research assistant designed to streamline time-consuming research tasks that typically require hours and dozens of browser tabs. Discover the technical architecture and engineering decisions behind this AI system that transforms everyday research activities - from evaluating summer camps to conducting investment due diligence - into efficient, automated processes. Explore the development challenges, key learnings, and implementation strategies used by the Google DeepMind team to create an AI agent capable of comprehensive information gathering and analysis. Gain insights into the future vision for personal research assistants and understand how machine learning engineers approach building practical AI tools that enhance human productivity in research-intensive workflows.

Explore the development of an AI research assistant capable of interacting with ArXiv research papers in this 18-minute video. Learn how to create a chatbot using LangChain conversational react agents, OpenAI LLMs, and Pinecone vector database for retrieval. Discover the process of giving LLMs enhanced abilities, such as surfacing relevant information from ArXiv and interacting with an "ArXiv database." Gain insights into the fundamental components of building an AI research assistant, including code implementation, adding new papers to the database, and leveraging various AI technologies. Access provided resources, including GitHub repository, testing notebook, and community platforms, to further your understanding and engagement with this cutting-edge AI application.

This workshop recording from Stanford University explores the development of Genie, a public AI assistant designed to write comprehensive research articles with full citations. Learn how the Stanford Open Virtual Assistant Lab, with support from the Alfred P. Sloan Foundation and Stanford HAI, is revolutionizing knowledge access through AI. Discover how Genie simulates users with diverse perspectives to generate questions, retrieve information, review content, and facilitate deeper exploration of topics. The presentation showcases how Genie can produce complete articles from given corpora with proper references, demonstrating a more effective paradigm than traditional question-answering systems. Explore real-world applications using an internet subset and Semantic Scholar, which has already served over 300,000 users requesting 500,000 topics ranging from lifestyle to scientific research. Speaker Yucheng Jiang presents this groundbreaking work recorded at Stanford University on February 14, 2025.

Learn to build an AI-powered research assistant that intelligently searches the web, analyzes information, and provides comprehensive answers with proper citations in this 28-minute tutorial. Discover how to create a 'Perplexity-style' tool that rivals commercial AI search platforms using Exa and Cerebras technologies. Master the integration of web search capabilities with AI analysis to develop a sophisticated research tool that can gather, process, and synthesize information from multiple sources while maintaining proper attribution. Explore the technical implementation details for combining search functionality with AI-powered content analysis, enabling you to build a comprehensive research assistant capable of delivering well-sourced, intelligent responses to complex queries.

This video covers how to use the 'Discover Sources' feature in NotebookLM to find and import relevant web-based sources directly into your research project.

Learn how to build and deploy your own AI-powered research assistant using GPT models, Python, Streamlit, and GitHub. Automate deep research and reporting in a real-world app. Start building job-ready AI tools today.Design and script your own version of ChatGPT's Deep Research AI agent from scratchUse your AI tool to automatically create clean, polished research reports with citationsUse OpenAI tools to generate and process search results and check goal completion through structured feedback loopsBuild an interactive front end for your research with Streamlit and deploy your app for use in the real-world

Learn to build the control logic for a multi-step AI research assistant. Structure the main python script to manage input, control iteration, and orchestrate modules for query generation, relevance checks, context extraction, and report creation. Implement an LLM-driven workflow for iterative search and comprehensive report generation.

Learn Streamlit, a Python framework for building interactive web apps, by turning a CLI research assistant into a responsive interface. Master widgets, layout, and state management while connecting an AI research pipeline to a real-time front end. By the end, you'll have a fully interactive Python-powered research assistant.

Explore the process of building an AI assistant's ArXiv paper scraping component in this 15-minute video tutorial. Learn how to implement a graph approach where each paper's references become "children" in the graph, and discover how to utilize OpenAI's text-davinci-003 model to transform messy references into a clean format. Follow along as the tutorial demonstrates using Google search to extract paper information and focuses on developing a research assistant capable of helping with ideas and staying up-to-date on topics such as LLMs, AI, NLP, and vector search. Access the project repository, support options, and additional resources to enhance your understanding of AI-powered research assistants.

Explore the process of building a practical AI assistant using OpenAI GPT 3.5, Langchain, and Pinecone in this informative video. Learn about the development of an ArXiv "researcher" component designed to aid in researching ideas and staying updated on the latest developments in LLMs, AI, NLP, and vector search. Discover how the assistant can understand YouTube content and articles, and get a glimpse of its potential future capabilities. Follow along as questions are posed to the ArXiv database, and gain insights into the next steps, including scraping ArXiv for more comprehensive data.

Learn to build agentic AI systems for real-time business research using fragmented, fast-changing information in this 48-minute tutorial led by Frank Boucher, Developer Advocate at Reka. Master the Reka Research API to create AI assistants that search across multiple sources and generate grounded, traceable answers for dynamic business scenarios. Explore multi-source retrieval and synthesis techniques for company profiling, market analysis, and product comparisons. Discover how to handle rapidly evolving information landscapes while maintaining accuracy and traceability in your AI-powered research tools. Gain practical skills in developing intelligent systems that can navigate complex data environments and provide reliable insights for business decision-making.

This introductory course on watsonx Assistant is designed for anyone interested in exploring the latest advancements in Generative AI and how they can enhance customer and employee experiences through the creation of AI assistants.

Explore how to build a truly personal AI assistant that knows you as an individual in this 19-minute conference talk from the AI Engineer World's Fair. Discover why current large language models like GPT-4, despite their massive training datasets, cannot provide personalized assistance without significant user input. Learn about an innovative approach that creates a personal, private, and proactive AI assistant by downloading your transaction logs from major consumer platforms like Google, Facebook, Amazon, DoorDash, Strava, and Uber directly to your local device. Understand how implementing a RAG (Retrieval-Augmented Generation) system using this personal data enables immediate utility without requiring extensive user configuration. Gain insights into how a modest amount of powerful personal data can unlock the true potential of personalized AI assistance, moving beyond generic responses to truly individualized support.

Nursing Assistant Essentials is a beginner-level course designed to build the fundamental knowledge and skills to provide compassionate and effective patient care. Through these three lessons, students will learn how to support patients across various healthcare settings. In Lesson 1: The Workplace: Health Care Settings, students explore the diverse environments where nursing assistants work, including hospitals, nursing homes, and home care settings. Lesson 2: The Nursing Assistant Role delves into the specific duties of a nursing assistant, including patient interaction, assisting with daily activities and providing essential support to nursing teams. Students learn to communicate effectively with patients and other healthcare professionals, fostering a positive and supportive care environment. In Lesson 3: Daily Hygiene: Grooming, Bathing, Toileting, Oral Care, and Dressing, students gain hands-on knowledge of assisting patients with personal hygiene tasks. They learn the proper techniques for ensuring patient comfort, dignity, and safety while performing essential daily care routines. This course is unique in its practical, patient-centered approach, blending theoretical understanding with essential hands-on skills to prepare students for real-world healthcare roles.

यहकोर्सछात्रकोकौशल औरशिक्षाप्रधान करेगाताकि छात्र स्वयं नियोक्ता प्राप्तकर सकें।पाठ्यक्रम को पूरा करने के पश्चात,बिस्तरपर पड़ें रोगियों को घर पर ही उपचार उपलब्ध कराकर स्व: रोजगार प्राप्त कर पाएगा।•पंचकर्मा चिकित्‍सालय•आयुर्वेदिक हस्‍पताल•आयुर्वेदिक आहार केन्‍द्र•आयुर्वेदिक हर्बल नर्सरी•आयुर्वेदिक हर्बल नर्सरी•जीवन शैली केन्‍द्र स्‍वास्‍थ्‍य केन्‍द्र•स्‍वास्‍थ्‍य स्‍पा तथा रिसोर्ट•आयुर्वेदिक कॉस्‍मेंटिक क्‍लीनिक•आदि में सहायक के रूप में कार्य कर सकते है।

AI assistants and chatbots have been a topic of great interest for many years. However, good AI assistants have also been really hard to implement and deploy… until now. The AI Assistants API from OpenAI allows creating powerful AI assistants that are capable of performing a variety of tasks that are really hard to code using traditional coding mechanisms. In this course, OpenAI Assistants API, you’ll learn how to develop powerful assistants that can be deployed in your applications that can interact using natural language. First, you’ll learn how to create and retrieve assistants. Next, you’ll learn how to create threads, run, and retrieve responses. Next, you’ll learn how to call functions that can be used by your assistant. Finally, you will learn how to upload content that your assistant can use for its responses. When you’re finished with this course, you’ll have the skills and knowledge of the OpenAI Assistants API needed to create a powerful AI assistant that receives prompts in natural languages and provides excellent responses using natural language.

The Nursing Assistant Fundamentals specialization prepares students for a successful Nursing Assistant career in diverse healthcare settings, emphasizing patient care assistance, health care setting navigation, effective communication in healthcare, hygiene and safety protocols, and patient mobility and comfort. IMPORTANT: This specialization is not designed to prepare students for national certification. Enrollees will gain the foundational/fundamental knowledge on subject matter relevant to the profession. However, to gain industry certification, a more comprehensive program must be completed through enrollment via approved/eligible schools such as MedCerts.

Learn to build a Python-based voice assistant that integrates with Google Calendar API, enabling features like schedule retrieval, note-taking, and more. Explore topics such as sound playback using gTTS, microphone input processing, Google Calendar API setup, speech-to-date conversion, event retrieval and vocalization, program launching, and assistant activation in this comprehensive tutorial series spanning 1 hour and 30 minutes.