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This course on hint design is a unique opportunity to dive into the world of ChatGPT and Large Language Models (LLM). Designed by Andrew Maynard, an expert in transformational technologies, this course equips students with the skills needed to effectively leverage the power of ChatGPT. Through a compact and engaging curriculum, students will learn how to evaluate hints and create effective hints, maximizing the potential of ChatGPT. The course covers hint patterns, creative hint structures, and the art of hint design for a variety of tasks and applications. Open to students of all backgrounds, this course does not require traditional engineering skills. Instead, it focuses on the clear and creative use of language, making it especially appealing to those studying English, languages, humanities, and social sciences.

This course will help you become a better negotiator. Unlike many negotiation courses, we develop a framework for analyzing and shaping negotiations. This framework will enable you to make principled arguments that persuade others. It will enable you to look beneath the surface of apparent conflicts to discover underlying interests. By the end of the course, you will be better able to predict, interpret, and shape the behavior of those you encounter in competitive situations. Throughout this course, you will have several opportunities to negotiate with other students using examples based on common situations in business and life. You will be able to receive feedback on your performance and compare what you did with how others approached the same scenario. These examples also provide an opportunity to discuss a wide range of topics, including preparing for a negotiation, making ultimatums, avoiding regret, expanding the pie, and communicating with someone who has a completely different world view. Additional topics include negotiating when you don’t have the power, negotiating over email, and the role of gender differences in negotiations. To round out the course, we'll hear from three negotiation experts: Linda Babcock, Herb Cohen, and John McCall McBain. Enjoy.

Google AI Essentials is a self-paced course designed to help people across roles and industries get essential AI skills to boost their productivity, zero experience required. The course is taught by AI experts at Google who are working to make the technology helpful for everyone. In under 10 hours, they’ll do more than teach you about AI — they’ll show you how to actually use it in the real world. Stuck at the beginning of a project? You’ll learn how to use AI tools to generate ideas and content. Planning an event? You’ll use AI tools to help research, organize, and make more informed decisions. Drowning in a flooded inbox? You’ll use AI tools to help speed up those daily work tasks, like drafting email responses. You’ll also learn how to write effective prompts and use AI responsibly by identifying AI’s potential biases and avoiding harm. After you complete the course, you’ll earn a certificate from Google to share with your network and potential employers. By using AI as a helpful collaboration tool, you can set yourself up for success in today’s dynamic workplace — and you don’t even need programming skills to use it.

LangChain, a popular open source framework for building LLM applications, recently introduced LangGraph. This extension allows developers to create highly controllable agents. In this course you will learn to build an agent from scratch using Python and an LLM, and then you will rebuild it using LangGraph, learning about its components and how to combine them to build flow-based applications. Additionally, you will learn about agentic search, which returns multiple answers in an agent-friendly format, enhancing the agent’s built-in knowledge. This course will show you how to use agentic search in your applications to provide better data for agents to enhance their output. In detail: 1. Build an agent from scratch, and understand the division of tasks between the LLM and the code around the LLM. 2. Implement the agent you built using LangGraph. 3. Learn how agentic search retrieves multiple answers in a predictable format, unlike traditional search engines that return links. 4. Implement persistence in agents, enabling state management across multiple threads, conversation switching, and the ability to reload previous states. 5. Incorporate human-in-the-loop into agent systems. 6. Develop an agent for essay writing, replicating the workflow of a researcher working on this task. Start building more controllable agents using LangGraph!

This course will give you a fundamental understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.), and demonstrate how these models can solve complex problems in a variety of industries, from medical diagnostics to image recognition and text prediction. In addition, we have developed practical exercises that will allow you to gain hands-on experience in applying these data science models to data sets. These hands-on exercises will teach you how to implement machine learning algorithms using PyTorch, an open source library used by leading technology companies in the field of machine learning (e.g. Google, NVIDIA, CocaCola, eBay, Snapchat, Uber and many others).

This course will help you become a better negotiator. Unlike many negotiation courses, we develop a framework for analyzing and shaping negotiations. This framework will enable you to make principled arguments that persuade others. It will enable you to look beneath the surface of apparent conflicts to discover underlying interests. By the end of the course, you will be better able to predict, interpret, and shape the behavior of those you encounter in competitive situations. Throughout this course, you will have several opportunities to negotiate with other students using examples based on common situations in business and life. You will be able to receive feedback on your performance and compare what you did with how others approached the same scenario. These examples also provide an opportunity to discuss a wide range of topics, including preparing for a negotiation, making ultimatums, avoiding regret, expanding the pie, and communicating with someone who has a completely different world view. Additional topics include negotiating when you don’t have the power, negotiating over email, and the role of gender differences in negotiations. To round out the course, we'll hear from three negotiation experts: Linda Babcock, Herb Cohen, and John McCall McBain. Enjoy.

With the advent of Generative AI, data engineering processes have undergone an amazing transformation. In this course, you will learn the impact of Generative AI on data engineering. As a data engineer, you will be able to use Generative AI to improve productivity by implementing innovative ways to deliver projects. Data engineering is responsible for building powerful data pipelines, managing data infrastructure, and ensuring high-quality data insights. This course is suitable for existing and aspiring data engineers, data warehousing specialists, and other data professionals such as data analysts, data scientists, and BI analysts. You will learn how to use and apply generative models to solve problems such as architecture design, database querying, data warehouse schema design, data augmentation, data pipelines, ETL workflows, data analysis and mining, data lakes, and data warehouses. You will also explore the challenges and ethical considerations associated with using Generative AI. Demonstrate your new Generative AI skills in a hands-on data engineering project that you can apply in your real life. Then take a final test to earn a certificate. You will be able to present your project and certificate to your current or future employers.

This course gives a broad overview of the impact that generative artificial intelligence (AI) could have on jobs and how it can be used to support everyday tasks. As the use of generative AI increases, organizations are finding new ways to augment their work, impacting the number and types of jobs we can expect in the future. In “Generative AI: Labor and the Future of Work,” you’ll explore how generative AI can support workers in all industries, as well as the labor that goes into developing and managing these systems. Explore what the “future of work” could mean for both employees and employers and how these systems can impact work quality, creativity, and the labor market. You’ll also look at how the global digital divide could impact tool adoption for different groups across the world. By analyzing the adoption and implementation of generative AI in the workplace, you will better understand how these tools could shift how we work together.

We all negotiate every day. On a personal level, we negotiate with friends, family members, landlords, car dealers, employers, etc. Negotiation is also the key to success in business. No business can survive without lucrative contracts. Within a company, negotiation skills can lead to your career advancement. I hope you will join the hundreds of thousands of listeners who have made Successful Negotiations one of the most popular and top-rated MOOCs around the world. During the course, you will learn and put into practice the four steps to successful negotiation: (1) Preparation: Plan your negotiation strategy (2) Negotiate: Use key tactics for success (3) Closing: Close the contract (4) Complete and Assess: The End Game To successfully complete this course and improve your negotiation abilities, you will need to do the following: (1) Watch short videos (5 to 20 minutes in length). The videos are interactive and contain questions to test your understanding of strategy and negotiation skills. You can speed up or slow down the videos to choose a listening pace that suits you. Depending on your schedule, you can watch the videos over several weeks, or you can watch them “in one go.” One student who watched the course in one sitting concluded that “It's as good as Breaking Bad.” Another student compared the course to “House of Cards.” Both series contain interesting examples of difficult negotiations! (2) Test your negotiation skills by completing negotiations in Module 6. You can negotiate with a local acquaintance or use Discussions to find a partner from another part of the world. Your negotiation partner will give you feedback on your negotiation skills. To help you with your negotiations, I have developed several free negotiation planning tools related to the course. These tools and a free app are available at http://negotiationplanner.com/. The course also includes an interactive experience where you can test your negotiation skills before engaging in real negotiations. (3) Pass the final exam. To successfully complete the course, you must answer 80% of the questions correctly. The exam is a mastery test, which means you can take it as many times as you like until you have mastered the material. Course Certificate You have the opportunity to receive a Course Certificate. The certificate provides official recognition of your achievements in the course and includes the University of Michigan logo. You can find out more about certificates at: https://learner.coursera.help/hc/en-us/articles/209819053-Get-a-Course-Certificate This course is also available in Spanish and Portuguese.To join the fully translated Spanish version, visit this page: https://www.coursera.org/learn/negociacion/ To join the fully translated Portuguese version, visit this page: https://www.coursera.org/learn/ negociacao Subtitles for video materials are available in English, Ukrainian, Chinese (simplified), Portuguese (Brazilian), Spanish Created by: University of Michigan Composite course logo is distributed under the Creative Commons CC BY-SA license and was created using images kindly provided by Flazingo Photos and K2 Space.

This is an introductory course on micro-research destinations that explains what IA is responsible for, why it is important and how Google implements it in its products. Here are the 7 principles of Google IA.

Learn key principles of designing effective AI agents, and organizing a team of AI agents to perform complex, multi-step tasks. Apply these concepts to automate 6 common business processes. Learn from João Moura, founder and CEO of crewAI, and explore key components of multi-agent systems: 1. Role-playing: Assign specialized roles to agents 2. Memory: Provide agents with short-term, long-term, and shared memory 3. Tools: Assign pre-built and custom tools to each agent (e.g. for web search) 4. Focus: Break down the tasks, goals, and tools and assign to multiple AI agents for better performance 5. Guardrails: Effectively handle errors, hallucinations, and infinite loops 6. Cooperation: Perform tasks in series, in parallel, and hierarchically Throughout the course, you’ll work with crewAI, an open source library designed for building multi-agent systems. You’ll learn to build agent crews that execute common business processes, such as: 1. Tailor resumes and interview prep for job applications 2. Research, write and edit technical articles 3. Automate customer support inquiries 4. Conduct customer outreach campaigns 5. Plan and execute events 6. Perform financial analysis By the end of the course, you will have designed several multi-agent systems to assist you in common business processes, and also studied the key principles of AI agent systems.

Generative AI knowledge is now an essential skill in project management. According to Business 2 Community, 93% of companies that invest in AI for project management report a positive return on investment. Additionally, generative AI can improve the success rate of projects by around 25%. Reflecting on the industry’s direction, IBM introduces this specialization to boost your career in project management. This specialization consisting of short self-paced courses is designed to help you kickstart your journey into applying generative AI within project management practices. This program is ideal for current and aspiring project professionals, including project managers, project coordinators, scrum masters, and those passionate about the field. You will begin the specialization by understanding the basics of generative AI and its real-world applications. You will then learn about generative AI prompts engineering concepts and approaches, and explore commonly used prompt engineering tools including IBM watsonx Prompt Lab, Spellbook, and Dust. Finally, you will explore how to apply generative AI techniques and tools, such as ChatGPT, Copilot, Gemini, and DALL-E throughout the project management lifecycle. Enhance your project management capabilities with generative AI! Enroll today and show your current and prospective employers your readiness to adeptly leverage the transformative power of generative AI in project management. Applied learning project This Specialization emphasizes applied learning and includes a series of hands-on activities and projects. In these exercises, you’ll take the theory and skills you’ve gained and practice them with real-world scenarios. Some projects include: - - Generate text, images, and code using generative AI - Apply prompt engineering techniques and best practices - Apply generative AI tools to improve project management performance