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Free Workshop / Seminar

Presented By: Institute for Social Research

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Generative AI For Practitioners (Part 2)

Register here: https://pdhp.isr.umich.edu/workshops/

Topics include: Comparing leading tools (ChatGPT, Claude, Google Gemini, Grok, and DeepSeek), while teaching effective prompting techniques, parameter tuning (e.g., temperature, system prompts), and evaluation methods for picking the right platform for the right task. Includes live examples of writing and refining prompts for research or coding tasks. Understanding AI model architecture and how it impacts common tasks, including base LLMs, instruction-tuned chatbots, reasoning/”thinking” models (like DeepSeek-R1), diffusion models (e.g., Stable Diffusion for images), and multimodal tools such as OpenAI’s o1, Gemini, and Anthropic’s Claude Artifacts. Participants will see practical demos showing why these differences matter for everyday tasks like analysis, text summarization, and media generation. Moving beyond single tools into integrated ecosystems such as Retrieval-Augmented Generation (RAG), GitHub Copilot/code assistance, research automation, autonomous agents, and Model Context Protocols (MCPs). Demons Topics include: Comparing leading tools (ChatGPT, Claude, Google Gemini, Grok, and DeepSeek), while teaching effective prompting techniques, parameter tuning (e.g., temperature, system prompts), and evaluation methods for picking the right platform for the right task. Includes live examples of writing and refining prompts for research or coding tasks. Understanding AI model architecture and how it impacts common tasks, including base LLMs, instruction-tuned chatbots, reasoning/”thinking” models (like DeepSeek-R1), diffusion models (e.g., Stable Diffusion for images), and multimodal tools such as OpenAI’s o1, Gemini, and Anthropic’s Claude Artifacts. Participants will see practical demos showing why these differences matter for everyday tasks like analysis, text summarization, and media generation. Moving beyond single tools into integrated ecosystems such as Retrieval-Augmented Generation (RAG), GitHub Copilot/code assistance, research automation, autonomous agents, and Model Context Protocols (MCPs). Demons
Topics include: Comparing leading tools (ChatGPT, Claude, Google Gemini, Grok, and DeepSeek), while teaching effective prompting techniques, parameter tuning (e.g., temperature, system prompts), and evaluation methods for picking the right platform for the right task. Includes live examples of writing and refining prompts for research or coding tasks. Understanding AI model architecture and how it impacts common tasks, including base LLMs, instruction-tuned chatbots, reasoning/”thinking” models (like DeepSeek-R1), diffusion models (e.g., Stable Diffusion for images), and multimodal tools such as OpenAI’s o1, Gemini, and Anthropic’s Claude Artifacts. Participants will see practical demos showing why these differences matter for everyday tasks like analysis, text summarization, and media generation. Moving beyond single tools into integrated ecosystems such as Retrieval-Augmented Generation (RAG), GitHub Copilot/code assistance, research automation, autonomous agents, and Model Context Protocols (MCPs). Demons
Please join for the next installment of the PDHP workshop series: Gen AI For Practitioners (Part 2), with Alexis Castellanos of the University Of Michigan. This workshop is a “sequel” to our original GenAI workshop from August of 2024, which was an introduction to using GenAI as a workplace tool. This year’s workshop will refresh and expand on the concepts introduced in Part 1, and update them for 2025 after 14 months of advancement in a field that moves with incredible pace. The 2025 workshop targets those that are already familiar with at least one of the popular web-based GenAI tools (ChatGPT, Google Gemini, and the like), and will focus on new advancements in the GenAI field, while comparing all the top GenAI providers, and offering live demonstration on ways to more effectively incorporate GenAI tools into your daily workflows.
Topics include:
Comparing leading tools (ChatGPT, Claude, Google Gemini, Grok, and DeepSeek), while teaching effective prompting techniques, parameter tuning (e.g., temperature, system prompts), and evaluation methods for picking the right platform for the right task. Includes live examples of writing and refining prompts for research or coding tasks.
Understanding AI model architecture and how it impacts common tasks, including base LLMs, instruction-tuned chatbots, reasoning/”thinking” models (like DeepSeek-R1), diffusion models (e.g., Stable Diffusion for images), and multimodal tools such as OpenAI’s o1, Gemini, and Anthropic’s Claude Artifacts. Participants will see practical demos showing why these differences matter for everyday tasks like analysis, text summarization, and media generation.
Moving beyond single tools into integrated ecosystems such as Retrieval-Augmented Generation (RAG), GitHub Copilot/code assistance, research automation, autonomous agents, and Model Context Protocols (MCPs). Demonstrations will show how to design workflows that combine these elements for more powerful, repeatable outcomes.
Privacy, infrastructure, and emerging trends, including: data security and governance requirements, frameworks for local/self-hosted models (Ollama, LM Studio, open-source LLMs), and hardware tradeoffs for running AI in-house. We will also discuss future trends in AI reasoning, agent collaboration, and compliance.
Topics include: Comparing leading tools (ChatGPT, Claude, Google Gemini, Grok, and DeepSeek), while teaching effective prompting techniques, parameter tuning (e.g., temperature, system prompts), and evaluation methods for picking the right platform for the right task. Includes live examples of writing and refining prompts for research or coding tasks. Understanding AI model architecture and how it impacts common tasks, including base LLMs, instruction-tuned chatbots, reasoning/”thinking” models (like DeepSeek-R1), diffusion models (e.g., Stable Diffusion for images), and multimodal tools such as OpenAI’s o1, Gemini, and Anthropic’s Claude Artifacts. Participants will see practical demos showing why these differences matter for everyday tasks like analysis, text summarization, and media generation. Moving beyond single tools into integrated ecosystems such as Retrieval-Augmented Generation (RAG), GitHub Copilot/code assistance, research automation, autonomous agents, and Model Context Protocols (MCPs). Demons Topics include: Comparing leading tools (ChatGPT, Claude, Google Gemini, Grok, and DeepSeek), while teaching effective prompting techniques, parameter tuning (e.g., temperature, system prompts), and evaluation methods for picking the right platform for the right task. Includes live examples of writing and refining prompts for research or coding tasks. Understanding AI model architecture and how it impacts common tasks, including base LLMs, instruction-tuned chatbots, reasoning/”thinking” models (like DeepSeek-R1), diffusion models (e.g., Stable Diffusion for images), and multimodal tools such as OpenAI’s o1, Gemini, and Anthropic’s Claude Artifacts. Participants will see practical demos showing why these differences matter for everyday tasks like analysis, text summarization, and media generation. Moving beyond single tools into integrated ecosystems such as Retrieval-Augmented Generation (RAG), GitHub Copilot/code assistance, research automation, autonomous agents, and Model Context Protocols (MCPs). Demons
Topics include: Comparing leading tools (ChatGPT, Claude, Google Gemini, Grok, and DeepSeek), while teaching effective prompting techniques, parameter tuning (e.g., temperature, system prompts), and evaluation methods for picking the right platform for the right task. Includes live examples of writing and refining prompts for research or coding tasks. Understanding AI model architecture and how it impacts common tasks, including base LLMs, instruction-tuned chatbots, reasoning/”thinking” models (like DeepSeek-R1), diffusion models (e.g., Stable Diffusion for images), and multimodal tools such as OpenAI’s o1, Gemini, and Anthropic’s Claude Artifacts. Participants will see practical demos showing why these differences matter for everyday tasks like analysis, text summarization, and media generation. Moving beyond single tools into integrated ecosystems such as Retrieval-Augmented Generation (RAG), GitHub Copilot/code assistance, research automation, autonomous agents, and Model Context Protocols (MCPs). Demons

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