After taking this course, learners will be able to effectively integrate generative AI tools (Large Language Models, LLMs, like ChatGPT) into their project management workflows to enhance efficiency, communication, and decision-making while maintaining ethical standards and data security.
Expérience recommandée
Compétences que vous acquerrez
- Catégorie : Large Language Models
- Catégorie : Project Management
- Catégorie : Large language models
- Catégorie : Scientific Management
- Catégorie : Data Science
Détails à connaître
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septembre 2024
6 devoirs
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Il y a 7 modules dans ce cours
In this course, we explore how we can effectively utilize GenAI tools to enhance project management. Across five key sessions, we cover the integration of Generative AI for optimizing workflows, using AI as a sounding board for decision-making, targeting information processing, providing constructive feedback, and addressing common challenges in communication and transcription. Each session emphasizes the importance of balancing AI capabilities with our judgment, ensuring that AI can enhance our creativity, efficiency, and ethical decision-making within project management practices. Through practical examples, hands-on exercises, and discussions on ethical considerations, we will gain the skills needed to apply AI-driven solutions in real-world scenarios.
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This unit introduces the integration of Generative AI (GenAI) technologies to optimize our modern project management practices. We emphasize the importance of leveraging AI tools to enhance our decision-making processes by freeing up time for more complex tasks like analysis and reasoning. Our lecture covers key topics such as data-driven decision-making and people-centric tools. We delve into the practical aspects of text parsing and data standardization using AI techniques, with a focus on improving communication and documentation within our project management workflows.
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We delve into how AI can enhance our practices by acting as a tool for guidance, feedback, and ideation. We explore how AI can assist us in generating and refining communication styles, offering constructive criticism, and considering multiple approaches to problem-solving. This session emphasizes the importance of integrity and transparency in our use of AI, advising on how we can incorporate AI-generated suggestions while maintaining control over the final output. Through practical examples, we demonstrate how AI can help us draft emails, manage project documents, and generate creative alternatives, making it an important assistant in our decision-making process.
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We explore how we can leverage AI to enhance information processing and communication. We demonstrate strategies of using AI for tasks such as defining acronyms, transforming tables into text, and generating meaningful summaries for different audiences. This session emphasizes the importance of clarity, accuracy, and the potential pitfalls of relying on AI for information conversion and interpretation. Additionally, we discuss the role of AI in reflecting and shaping perceptions while also highlighting the need for validation and critical thinking when using AI-generated content.
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We explore communication and reporting within project management, specifically focusing on delivering constructive feedback. We cover strategies for offering detailed, individual, and specific feedback that promotes growth and improvement. We also discuss the importance of balancing positive reinforcement with constructive criticism and illustrate practical approaches to optimizing our team meetings and feedback loops. Emphasis is placed on the ethical use of AI in providing feedback, ensuring that it complements our judgment rather than replacing it
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As we conclude this module, it's time to apply what we've learned. The following test and project will challenge your understanding of the key concepts and your ability to integrate them into practical scenarios.
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Instructeur
Offert par
Recommandé si vous êtes intéressé(e) par Data Analysis
Coursera Instructor Network
Banco Interamericano de Desarrollo
Amazon Web Services
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