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Everyday AI Business Tools

Everyday AI Business Tools

50mGeneral2024-12-05

Authors

Doug Rose

Doug Rose

Teaching Fortune 500s and professionals how to lead change

Course details

There are many business needs that AI tools can help solve: logistics, market analysis, customer support, inventory prediction, and more. But without a technical background, it can be difficult to make the connection between these challenges and the AI technology and tools that can help solve them. This course links common business needs to practical AI-based solutions, so you can build or buy the best AI systems for your organization. Instructor Doug Rose explains how AI can automate customer service, including phone, online chat, and even in-person interactions. He shows how business logistics can benefit from automated decision-making and data retrieved from IoT devices. He also discusses machine learning for making better predictions for sales, purchasing, and many other aspects of your business. Along the way, Doug reviews top AI tools, including TensorFlow, Amazon Web Services, and Microsoft Azure. By taking this course, you can leverage the untapped potential of AI to take your business to the next level.

Learning objectives
Understand how AI systems and tools can provide value to businesses, and identify potential use cases for predictive and generative tasks.
Analyze and group together large data sets using machine learning platforms, and discover how this can help businesses make better decisions.
Explore and compare different machine learning tools, and select the most appropriate one for a given business need.
Practice using clear and concise prompts to get the best data from AI systems, and use this to make better decisions for the business.

Skills covered

Artificial Intelligence for BusinessBusiness Analysis and StrategyOne-Off

Concepts

0. Introduction

  • 01 - Exploring essential AI tools for everyday business

1. Key Tools in the AI Tool Chest

  • 02 - Tools for toolmakers
  • 03 - The rise of AI systems
  • 04 - Artificial neural networks

2. Predictive Artificial Intelligence

  • 05 - How to build a machine learning platform
  • 06 - Fine-tune your data model

3. Generative Artificial Intelligence

  • 07 - The flexibility of foundation models
  • 08 - Generate text with large language models (LLM)
  • 09 - Run a local LLM with Llama
  • 10 - The promise of prompt engineering
  • 11 - Create graphics with image diffusion models

4. Administration at Scale

  • 12 - How machines learn
  • 13 - Self-supervised learning

5. Tools of Today to Build Tomorrow's Tools

  • 14 - The AI upskilling framework
  • 15 - Human intelligence

Conclusion

  • 16 - Tools and concepts

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