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🚀 Ready to dive into the world of Neo4j and Generative AI? Join us for a virtual live workshop on December 11 and get hands-on with Neo4j!

In this session, Jennifer Reif will break down the fundamentals of GenAI, explore how Neo4j and knowledge graphs enhance AI-driven applications, and how GraphRAG improves accuracy and explainability over standard RAG. Through practical exercises, you’ll build your own conversational agent using Neo4j, Python, and LangChain. What to expect: 🔹 Introduction to graphRAG concepts 🔹 Hands-on agnetic exercises 🔹 Real-world applications and use cases

🔗 Register HERE now to start your journey with graph databases: Whether you're a developer, data scientist, or tech enthusiast, this workshop is the perfect starting point to unlock the potential of Neo4j.

https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+C-FX-08+V1

Thanks to improvements in computing power and scientific theory, generative AI is more accessible than ever before. Generative AI plays a significant role across industries due to its numerous applications, such as creative content generation, data augmentation, simulation and planning, anomaly detection, drug discovery, personalized recommendations, and more.

In this course, learners will take a deeper dive into denoising diffusion models, which are a popular choice for text-to-image pipelines.

This course is online and offered free of charge to academic participants (students and staff). If you are in industry, and would like to take the training, please send an email to [email protected]

Important Access links to the NVIDIA DLI environment required to complete the graded assessment and obtain a certification will be sent to your academic email shortly before the event, please be sure to fill the access form to gain access to it.

Learning Objectives

• Build a U-Net to generate images from pure noise
• Improve the quality of generated images with the denoising diffusion process
• Control the image output with context embeddings
• Generate images from English text prompts using the Contrastive Language–Image Pretraining (CLIP) neural network

Topics Covered

• U-Nets
• Diffusion
• CLIP
• Text-to-image Models

From U-net to Diffusion

• Build a U-Net architecture
• Train a model to remove noise from an image

Diffusion Models

• Define the forward diffusion function
• Update the U-Net architecture to accommodate a timestep
• Define a reverse diffusion function

Optimizations

• Implement Group Normalization
• Implement GELU
• Implement Rearrange Pooling
• Implement Sinusoidal Position Embeddings

Classifier-free Diffusion Guidance

• Add categorical embeddings to a U-Net
• Train a model with a Bernoulli mask

CLIP

• Learn how to use CLIP Encodings
• Use CLIP to create a text-to-image neural network

We are excited to announce our next virtual meetup!

Join us on November 30 from 4:00 pm to 5:00 pm CET (GMT+1) for a talk on using Generative AI in R with Sharon Machlis — Tech Journalist and Data Professional.

Generative AI is evolving rapidly, and that includes powerful new ways to integrate AI into your R scripts. In this session, Sharon will offer an accessible, high-level overview of what’s possible today — including how large language models can help you write and improve your R code, as well as add AI-driven features to your applications.

This is not a hands-on workshop. Instead, you’ll walk away with a clear understanding of the emerging R–AI landscape, plus a set of R packages, resources, and tutorials to help you explore further on your own.

If you’d like to join us, please register here on the Meetup page.

We look forward to seeing many of you there!

https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+C-FX-08+V1

Thanks to improvements in computing power and scientific theory, generative AI is more accessible than ever before. Generative AI plays a significant role across industries due to its numerous applications, such as creative content generation, data augmentation, simulation and planning, anomaly detection, drug discovery, personalized recommendations, and more.

In this course, learners will take a deeper dive into denoising diffusion models, which are a popular choice for text-to-image pipelines.

This course is online and offered free of charge to academic participants (students and staff). If you are in industry, and would like to take the training, please send an email to [email protected]

Important Access links to the NVIDIA DLI environment required to complete the graded assessment and obtain a certification will be sent to your academic email shortly before the event, please be sure to fill the access form to gain access to it.

Learning Objectives

• Build a U-Net to generate images from pure noise
• Improve the quality of generated images with the denoising diffusion process
• Control the image output with context embeddings
• Generate images from English text prompts using the Contrastive Language–Image Pretraining (CLIP) neural network

Topics Covered

• U-Nets
• Diffusion
• CLIP
• Text-to-image Models

From U-net to Diffusion

• Build a U-Net architecture
• Train a model to remove noise from an image

Diffusion Models

• Define the forward diffusion function
• Update the U-Net architecture to accommodate a timestep
• Define a reverse diffusion function

Optimizations

• Implement Group Normalization
• Implement GELU
• Implement Rearrange Pooling
• Implement Sinusoidal Position Embeddings

Classifier-free Diffusion Guidance

• Add categorical embeddings to a U-Net
• Train a model with a Bernoulli mask

CLIP

• Learn how to use CLIP Encodings
• Use CLIP to create a text-to-image neural network

Take your AI applications to the next level by mastering GraphRAG in this exclusive Neo4j virtual workshop. Discover how to use the neo4j-graphrag open-source python package to build and optimize Retrieval-Augmented Generation (RAG) systems seamlessly integrated with generative AI models.

Take your AI applications to the next level by mastering GraphRAG in this exclusive Neo4j virtual workshop. Discover how to use the neo4j-graphrag open-source python package to build and optimize Retrieval-Augmented Generation (RAG) systems seamlessly integrated with generative AI models.

Take your AI applications to the next level by mastering GraphRAG in this exclusive Neo4j virtual workshop. Discover how to use the neo4j-graphrag open-source python package to build and optimize Retrieval-Augmented Generation (RAG) systems seamlessly integrated with generative AI models.

Take your AI applications to the next level by mastering GraphRAG in this exclusive Neo4j virtual workshop. Discover how to use the neo4j-graphrag open-source python package to build and optimize Retrieval-Augmented Generation (RAG) systems seamlessly integrated with generative AI models.

Hands-On: Prompt Engineering Online Bootcamp Date: 06 September 2025, 9 AM to 12.30 PM Eastern Time Level: Beginners/Intermediate Registration Link: https://www.eventbrite.com/e/hands-on-prompt-engineering-bootcamp-tickets-1443819937299?aff=oddtdtcreator Who Should Attend? This hands-on workshop is for developers, senior software engineers, IT pros, architects, IT managers, citizen developers, technology product managers, IT leaders, enterprise architects, chief analytics officers, chief information officers, chief technology officers, and decision-makers who want to learn how prompt engineering can help bring AI into next-gen apps and agents. Experience with C#, Python, or JavaScript is helpful but not required. No prior knowledge of AI is necessary. While this isn’t a data & analytics-focused session, data scientists, data stewards, and tech-savvy data protection officers will also find it super valuable. Description: The rise of generative AI, led by ChatGPT and other large language models, has sparked serious interest across industries and leadership teams. Models like OpenAI’s GPT-3.5, GPT-4o, and GPT-4.5 rely heavily on the quality of the prompts they're given. The better the prompt, the better the output. That makes prompt engineering a must-have skill. In this half-day virtual hands-on workshop, Microsoft AI and Business Applications MVP and Microsoft Certified Trainer, Prashant G Bhoyar, will cover these topics in detail:

• What is Prompt Engineering? Learn how prompts work, why they matter, and what affects their performance.
• Advanced Prompting Techniques:
• Few-shot prompting (use examples to get better answers)
• Chain-of-thought prompting (step-by-step reasoning)
• Instruction fine-tuning (force the model to follow your rules)
• Persona-based prompting (get responses in specific roles)
• Multi-step prompting (refine results through iteration)
• Debugging & Refining AI Responses
• How to fine-tune prompts for ChatGPT, Claude, Google Gemini, and other tools
• Automating prompts with APIs and workflows
• Working with reasoning models like o3
• Best practices for real-world use

By the end of this bootcamp, you'll be ready to create clear, powerful prompts that unlock the full potential of generative AI in your projects. The labs will feature a mix of Python, C#, and low-code/no-code UI tools, so even if you don't want to write code, you're covered. Workshop Resources: You’ll get access to Microsoft Copilot, Azure, and Azure OpenAI services (worth $500) for hands-on labs. If you already have your own Microsoft Copilot or Azure subscription, you’re welcome to use that too. Attendee Workstation Requirements: You must have your own computer (Windows or Mac) with:

• Camera, speakers, microphone, and a reliable internet connection. Tablets will not work for this workshop.
• A modern browser (Microsoft Edge, Google Chrome, Firefox, or Safari).
• Access to www.azure.com and https://copilotstudio.microsoft.com.
• Nice to have is the ability to run C# 10 or Python code, using Visual Studio 2022, VSCode 1.66+, Visual Studio for Mac, Rider, or a similar IDE.

Important: Register on the event website to receive joining link. (rsvp on meetup will NOT receive joining link).

Description: Welcome to the weekly AI virtual seminars, in collaboration with Oracle. Join us for deep dive tech talks on AI, hands-on experiences on code labs, workshops, and networking with speakers & fellow developers from all over the world.

Tech Talk: Bring the Power of Knowledge Graphs to Generative AI Speakers: Melliyal Annamalai (Oracle) Abstract: AI is great, but some of us are skeptical about the black box that makes decisions and answers our questions. It's hard to know whether it's hallucinating or if the answer is accurate. But it doesn't have to be that way! Knowledge graphs can add context, relationships, and meaning to AI responses and decisions. In this session, we'll go over Retrieval-Augmented Generation (RAG) and explore how we can use the power of knowledge graphs to enhance RAG (Graph RAG). Using a simple detective story, we will demonstrate how Graph RAG can help direct AI tools so that they are more trustworthy.

More upcoming sessions:

• Sep 3rd: AI Webinar with Docker - Local AI Development
• Sep 4th: AI Webinar with Oracle (Ep 5) - Use Knowledge graphs to transparently apply AI
• Sep 16th: AI Webinar with Oracle (Ep 7) - Hands-on workshop for Improving AI Predictions using Location Data
• Sep 23rd: AI Webinar with Oracle (Ep 8) - MongoDB to Oracle – Switch and Use AI on Your Data and App
• Oct 10th: AI Webinar with Oracle (Ep 9) - Develop an AI Agent Application using LangChain and Oracle Database 23ai
• Oct 28th: AI Webinar with Oracle (Ep 10) - Implementing AI Vector Search *

Local and Global AI Community on Discord Join us on discord for local and global AI tech community:

• Events chat: chat and connect with speakers and global and local attendees;
• Learning AI: events, learning materials, study groups;
• Startups: innovation, projects collaborations, founders/co-founders;
• Jobs and Careers: job openings, post resumes, hiring managers *

Important: Register on the event website to receive joining link. (rsvp on meetup will NOT receive joining link).

Description: Welcome to the weekly AI virtual seminars, in collaboration with Oracle. Join us for deep dive tech talks on AI, hands-on experiences on code labs, workshops, and networking with speakers & fellow developers from all over the world.

Tech Talk: Bring the Power of Knowledge Graphs to Generative AI Speakers: Melliyal Annamalai (Oracle) Abstract: AI is great, but some of us are skeptical about the black box that makes decisions and answers our questions. It's hard to know whether it's hallucinating or if the answer is accurate. But it doesn't have to be that way! Knowledge graphs can add context, relationships, and meaning to AI responses and decisions. In this session, we'll go over Retrieval-Augmented Generation (RAG) and explore how we can use the power of knowledge graphs to enhance RAG (Graph RAG). Using a simple detective story, we will demonstrate how Graph RAG can help direct AI tools so that they are more trustworthy.

More upcoming sessions:

• Sep 3rd: AI Webinar with Docker - Local AI Development
• Sep 4th: AI Webinar with Oracle (Ep 5) - Use Knowledge graphs to transparently apply AI
• Sep 16th: AI Webinar with Oracle (Ep 7) - Hands-on workshop for Improving AI Predictions using Location Data
• Sep 23rd: AI Webinar with Oracle (Ep 8) - MongoDB to Oracle – Switch and Use AI on Your Data and App
• Oct 10th: AI Webinar with Oracle (Ep 9) - Develop an AI Agent Application using LangChain and Oracle Database 23ai
• Oct 28th: AI Webinar with Oracle (Ep 10) - Implementing AI Vector Search *

Local and Global AI Community on Discord Join us on discord for local and global AI tech community:

• Events chat: chat and connect with speakers and global and local attendees;
• Learning AI: events, learning materials, study groups;
• Startups: innovation, projects collaborations, founders/co-founders;
• Jobs and Careers: job openings, post resumes, hiring managers *

Important: Register on the event website to receive joining link. (rsvp on meetup will NOT receive joining link).

Description: Welcome to the weekly AI virtual seminars, in collaboration with Oracle. Join us for deep dive tech talks on AI, hands-on experiences on code labs, workshops, and networking with speakers & fellow developers from all over the world.

Tech Talk: Bring the Power of Knowledge Graphs to Generative AI Speakers: Melliyal Annamalai (Oracle) Abstract: AI is great, but some of us are skeptical about the black box that makes decisions and answers our questions. It's hard to know whether it's hallucinating or if the answer is accurate. But it doesn't have to be that way! Knowledge graphs can add context, relationships, and meaning to AI responses and decisions. In this session, we'll go over Retrieval-Augmented Generation (RAG) and explore how we can use the power of knowledge graphs to enhance RAG (Graph RAG). Using a simple detective story, we will demonstrate how Graph RAG can help direct AI tools so that they are more trustworthy.

More upcoming sessions:

• Sep 3rd: AI Webinar with Docker - Local AI Development
• Sep 4th: AI Webinar with Oracle (Ep 5) - Use Knowledge graphs to transparently apply AI
• Sep 16th: AI Webinar with Oracle (Ep 7) - Hands-on workshop for Improving AI Predictions using Location Data
• Sep 23rd: AI Webinar with Oracle (Ep 8) - MongoDB to Oracle – Switch and Use AI on Your Data and App
• Oct 10th: AI Webinar with Oracle (Ep 9) - Develop an AI Agent Application using LangChain and Oracle Database 23ai
• Oct 28th: AI Webinar with Oracle (Ep 10) - Implementing AI Vector Search *

Local and Global AI Community on Discord Join us on discord for local and global AI tech community:

• Events chat: chat and connect with speakers and global and local attendees;
• Learning AI: events, learning materials, study groups;
• Startups: innovation, projects collaborations, founders/co-founders;
• Jobs and Careers: job openings, post resumes, hiring managers *