diff --git a/config.toml b/config.toml
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--- a/config.toml
+++ b/config.toml
@@ -144,10 +144,10 @@ paginatePath = "/"
 
 [[menu.main]]
   name = '🚀 DeepLearning.AI'
-  url = 'https://www.deeplearning.ai/short-courses/building-ai-application-with-haystack/'
+  url = 'https://www.deeplearning.ai/short-courses/building-ai-applications-with-haystack/'
   parent = 'learn'
   weight = 1
-  params = { tag = "Waitlist" }
+  params = { tag = "Enroll" }
 
 # Resources children
 [[menu.main]]
diff --git a/content/blog/announcing-dlai/index.md b/content/blog/announcing-dlai/index.md
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+---
+layout: blog-post
+title: Announcing Our New Short Course with DeepLearning.AI
+description: Enroll in "Building AI Applications with Haystack"
+featured_image: thumbnail.png
+images: ["blog/announcing-dlai/thumbnail.png"]
+toc: True
+date: 2024-08-21
+last_updated:  2024-08-21
+authors:
+  - Tuana Celik
+tags: ["Community", "RAG"]
+---	
+
+[DeepLearning.AI](http://deeplearning.ai/) and Andrew Ng hold a special place in many AI/ML engineers' careers and development. For many engineers, they’ve played a pivotal role into breaking into AI, or extending their knowledge and capabilities by teaching about core concepts and technologies at the right time. So, we’re incredibly happy to announce that we’re launching our first short course with them - “Building AI Applications with Haystack”
+
+<iframe width="560" height="315" src="https://www.youtube.com/embed/oluZaroQROM?si=IvZKTTLQ0FpGWrH3" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
+
+[**🚀 Enroll now**](https://www.deeplearning.ai/short-courses/building-ai-applications-with-haystack/)
+
+## What you’ll learn
+
+This course is designed with a bottom up approach, starting by teaching you about the building blocks of generative AI applications. Throughout the course, you’ll start to design and customize your own retrieval-augmented generative (RAG) pipelines, you’ll learn how to extend Haystack with custom capabilities for your own generative AI use case, you’ll even implement a simple self-reflecting agent and end the course by creating a full chat agent with function calling.
+
+## Who is the course for?
+
+If you’re new to AI, this course is a great way to start learning about the basics and how they come together to build some of the most useful GenAI use cases. It will also teach you the fundamentals of Haystack and how you can make use of our framework to build out your own applications. You certainly do not need to have a deep understanding or much prior knowledge, however, it will be useful for you to be familiar with Python and have some basic understanding of different model types like embedding models and generative models.
+
+If you’re not new to AI, this course is a great way to get started with Haystack as a tool for you to make your GenAI use cases come to life. 
+
+It's been an absolute pleasure for me to create this with the Haystack team and the [DeepLearning.AI](http://deeplearning.ai/) team. I’d love to hear what you think, and if you take the course and end up with questions, please join me for an [AMA session on September 10th](https://landing.deepset.ai/webinar-haystack-ama-session-deeplearning).
+
+### Follow us
+
+- [Haystack on Twitter](https://x.com/Haystack_AI)
+- [Haystack on YouTube](https://www.youtube.com/@haystack_ai)
+- [Join our Discord](https://discord.com/invite/VBpFzsgRVF)
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