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DeepLearning.AI is empowering the global workforce to build an AI-powered future through world-class education, hands-on training, and a collaborative community.
06/23/2026
🚀 The 7-Day Voice AI Builder Challenge is Officially LIVE!
Stop babysitting your terminal.
🗣️ The Challenge: Teach your AI coding agent to call you for backup—but only when human intervention is actually required.
Real-time feedback? Yes. Live leaderboard? Absolutely. Epic prizes for the winners? You bet.
The clock is officially ticking. Competitors are already shipping.
Are you in?
👉 https://hubs.la/Q04mkz9R0
Adding voice to an existing AI agent used to mean rewriting a lot of code. In our new short course, Voice for AI Agents and Applications, built in partnership with Vocal Bridge and taught by CEO Ashwyn Sharma, you'll learn to layer voice onto an existing agent using minimal code without touching your prompts, RAG pipeline, or tools.
You'll implement three integration patterns: voice embedded in an app, voice layered onto an existing agent, and voice as a callable tool your agent uses to place outbound phone calls.
Enroll for free: https://hubs.la/Q04lHm2G0
06/10/2026
🚀 Introducing the new DeepLearning.AI GitHub repository!
We've launched a brand-new public DeepLearning.AI GitHub repository to make it easier than ever to find the resources you need.
Inside you'll find:
📚 A master course catalog
🛠️ Developer tools and resources
🔗 Direct access to supplemental course artifacts
✨ And much more coming soon
Follow the repository and give it a ⭐ to stay updated as we continue adding new resources.
🔗 https://hubs.la/Q04kSyKq0
Serving LLMs efficiently comes down to how well you manage GPU memory.
In Fast & Efficient LLM Inference with vLLM, you’ll quantize an open-source model, serve it with vLLM, and benchmark your deployment across speed, cost, and accuracy.
Built in collaboration with Red Hat and taught by Cedric Clyburn.
Enroll for free: https://hubs.la/Q04jWvwV0
05/28/2026
A vague prompt gives vague advice. Context changes the quality of the answer.
The more clearly you explain your situation, constraints, priorities, and goals, the more useful AI becomes for complex decisions.
Learn practical prompting techniques in AI Prompting for Everyone with Andrew Ng: https://hubs.la/Q04jj39M0
05/26/2026
AI agents seem to be increasingly capable of performing economically valuable tasks, but current benchmarks measure this capability only narrowly.
Zora Z. Wang and colleagues at Carnegie Mellon University and Stanford University mapped examples drawn from agent benchmarks to statistics that represent U.S. labor. The mapping revealed a mismatch between the tests, which generally emphasize software development, and the more varied work most people do.
Read the full article in The Batch:
AI Agents May Not Be Getting Better at Full Range of Economically Valuable Labor AI agents seem to be increasingly capable of performing economically valuable tasks, but current benchmarks measure this capability only narrowly.
Humans can keep a few ideas in working memory at once. Modern AI models can process the equivalent of multiple Harry Potter books in a single conversation.
Understanding context windows changes how you prompt, write, research, and work with AI systems.
Learn more in AI Prompting for Everyone with Andrew Ng: https://hubs.la/Q04hZf5j0
05/22/2026
China halted Meta’s planned acquisition of Manus, asserting tighter government control over strategically important AI technology.
The decision disrupts a popular strategy among Chinese AI startups: relocating abroad to attract Western investment and partnerships.
Learn more in The Batch: https://hubs.la/Q04hJ10c0
“Budget” and “financials” are different words, but embeddings understand they’re related.
That’s the foundation behind semantic search and one of the core building blocks of modern multimodal systems.
Learn how embeddings power retrieval across text, audio, images, and video in Building Multimodal Data Pipelines: https://hubs.la/Q04hJs8v0