English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 1h 56m | 292 MB
AI is changing the world around us, and completely revolutionizing the way we work. Data professionals now have access to tools that provide superpowers to work smarter and faster than ever before.
In this course, the Maven Analytics team guides you through the world of deep learning and generative AI and shows you how to leverage Power BI and ChatGPT together to work more efficiently and make smarter, data-driven decisions.
Explore the rapid rise of large language models like ChatGPT and Google Gemini, and get up and running with free tools that will take your skills to the next level. You’ll also dive into the art of prompt engineering, review tips and best practices for generating consistent and accurate model outputs, and find out how to address common limitations and pitfalls to be aware of.
From there, Aaron Parry takes you through some of the most powerful and practical ChatGPT use cases for data science and analytics, with instructor-led demos in Power BI.
Table of Contents
Introduction
1 The future is now Intro to AI for data analytics
2 Setting expectations
How AI Is Revolutionizing Data Analysis
3 Why AI is a game changer for data analysis
4 AI use cases for data analytics
A Crash Course in AI, LLMs, and ChatGPT
5 The AI landscape
6 Generative AI and large language models
7 The road to ChatGPT
8 Generative AI tools
9 Warning Pitfalls of ChatGPT
10 Accessing ChatGPT and Google Bard
Prompt Engineering Tips
11 Intro to prompt engineering
12 Prompt tip Be clear and specific
13 Prompt tip Provide context
14 Prompt tip Establish roles
15 Prompt tip Set the tone
ChatGPT for Power BI
16 Intro to ChatGPT for Power BI
17 Getting started with ChatGPT for Power BI
18 Connect to data from Power BI
19 Create a data dictionary
20 Format and comment power query code
21 Explain fundamental Power BI concepts
22 Generate DAX from examples
23 Explain and comment DAX code
24 Generate DAX measures from scratch
25 Troubleshoot DAX errors
26 Visualize data with Power BI
27 Build a Power BI dashboard
Conclusion
28 Key takeaways and next steps
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