Comparing AI Research Tools: ChatGPT, Claude, Gemini, and Perplexity

Course details

Generative AI has brought efficiency to many areas of work, but when it comes to research and data analysis, most users are barely scratching the surface. This practical, hands-on course explores AI tools such as ChatGPT, Claude, Gemini, and Perplexity, providing you with essential tools and knowledge to super-charge research and data analysis work. Instructor Ronnie Sheer delves into real-world business scenarios, exploring how LLM-powered search, data analysis, and data visualization can enhance efficiency and productivity. Ronnie also examines strategies for teams and organizations to harness the potential of GenAI in larger research endeavors, enabling organizations to streamline processes and make data-driven decisions more effectively.

Learning objectives
Analyze the differences between tools like ChatGPT, Claude, and Gemini and determine the ideal tool for specific tasks.
Set up and configure ChatGPT for data analysis within Microsoft Teams.
Create custom GPTs to streamline your organization's workflows.
Explore ethical considerations related to the use of AI tools.
Identify potential content ownership and copyright concerns related to the use of generative AI tools.
Utilize Claude Artifacts to generate data visualizations.

Concepts

0. Introduction

01 - Choosing the right AI tool for the job
02 - Warning - Use responsibly

1. ChatGPT

03 - Processing data with ChatGPT
04 - Setting up ChatGPT for analysis
05 - Leveraging Python library to visualize data
06 - Outputting data
07 - Custom GPTs to streamline your organization's workflows
08 - Case study - OpenAI and Moderna
09 - Challenge - Custom GPT
10 - Solution - Custom GPT

2. Claude

11 - Anthropic and ethical AI
12 - Using Claude for research and analysis
13 - Claude artifacts for data visualization

3. Google Gemini

14 - An overview of Gemini for research
15 - Using Gemini for research and analysis

4. Augmented Search

16 - Reliability in LLM driven search
17 - Content ownership and copyright concerns with AI search
18 - LLM driven search in practice

Conclusion

19 - Continuing your AI journey