Udacity

Udacity changes lives, businesses, and nations by providing job-ready skills in digital technologies.
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We prepare the world’s workforce to
take on new challenges with confidence, providing the best opportunity to empower the careers of the future. Our exceptional curriculum, personalized mentor support, and measurable outcomes create expertise with a focus on the in-demand competencies that ensure workplace relevance.

08/25/2026

No computer science degree required.

Sabrina Palis spent a decade as a teacher before enrolling in the Master of Science in AI degree program. Her capstone project: a decision support system that uses AI to detect anomalies in aerospace telemetry.

Watch the full graduate panel: https://bit.ly/4qE0Pj0

08/17/2026

What's your best defense against an agent inventing data? It isn't the schema: schema validation checks shape, and a hallucinated value has perfect shape.

The agent needed a date, invented one, and the pipeline accepted it, which is how fabricated data spreads through systems that look well defended. The defense is layered: a schema that makes missing data representable, so the model has a legal way to say it doesn't know, plus validation that catches the internal inconsistencies a model smooths over.

That extraction work is part of the evaluation coursework in the new AI Engineering with Claude Nanodegree program.

Learn more about the program: https://bit.ly/3TFDWPQ

08/14/2026

🤖 One of the cumulative projects in the new AI Engineering with Claude Nanodegree program is a claims intake agent.

You start with the raw agentic loop and build up to an agent that reads an ambiguous claim and decides its own next step: clarify with the user, route it forward, or escalate to a person.

By the last exercise the decision logic is yours, written and tested by hand.

Explore the program: https://bit.ly/4weBZaK

08/13/2026

The best people to tell you about our master's in AI program? The ones who've been through it.

Join us live this Wednesday for a Q&A with three program graduates:
✅ Nhan Le – Data Quality Analyst, Meta
✅ Sabrina Palis – AI and Data Science Specialist
✅ Christopher O'Hara – Applied AI Engineer & Researcher

They'll share what the experience was really like: the challenges, the highlights, and what they'd tell someone considering the program today.

Register for free here, and come with your questions ➡️ https://bit.ly/4qgoYvD

08/12/2026

Multi-agent systems are having a moment, and plenty of them shouldn't exist.

Every agent you add brings coordination, handoffs, and failure modes the single-agent version never had, and a lot of problems come out better with one well-engineered agent than five loosely coordinated ones. The judgment call is knowing when the added complexity pays for itself; when it does, the hard parts are the unglamorous ones: scoped roles, structured handoffs, agents you can hold accountable.

You design that tradeoff, and build it with the Claude Agent SDK, in the new AI Engineering with Claude Nanodegree program.

Learn More: https://bit.ly/45aeyEq

08/10/2026

Every turn of an agent conversation carries the whole conversation with it: old tool output, resolved threads, context the model stopped needing ten turns ago.

Cost and latency climb until someone engineers the context. Prune stale tool output, keep a persistent block of load-bearing facts, compress resolved threads against a token budget, and put the important context where the model will see it.

You build that harness by hand in the new AI Engineering with Claude Nanodegree program.

Explore the program: https://bit.ly/4fM2wHp

08/07/2026

Our take: for anything high-stakes, don't rely on a prompt at all.

A prompt can ask an agent to follow the rules, but it can't guarantee it will. That is fine for low-stakes work and risky the moment an agent is moving money or touching customer data. The fix is enforcement in code: deterministic control logic that holds the line no matter what the model decides, with a human in the loop where the stakes demand it.

That is how bounded autonomy gets built in the new AI Engineering with Claude Nanodegree program.

Learn more: https://bit.ly/4ySU80h

08/05/2026

Watch an agent bill grow for a quarter and a pattern shows up: routing, extraction, and classification all running on the largest model available, because that was the safe pick on day one and nobody revisited it.

Most of that work runs fine on a smaller, faster model at a fraction of the cost, and choosing it deliberately is an engineering call. It is one of the first calls you practice making in the new AI Engineering with Claude Nanodegree program.

Explore the program: https://bit.ly/4pXDLLK

08/04/2026

"The program's greatest value lies in its portfolio-first approach, building production-ready AI systems rather than focusing solely on theoretical exams." - Thounda Craig Jr, master’s in AI student

Back to school looks a little different with our Master's in AI 🎓

This fall, skip the backpack and grab the skills that actually move your career forward: 50+ hands-on projects, a capstone, and a credential built for the future of work.

The master's in AI degree is designed for people who want to build with AI, not just learn it.

The back-to-school sale is ending soon. If you've been thinking about it, now's the time 👉 https://bit.ly/4528SfF

08/03/2026

Most agent demos die the same death: they work in the meeting and fall over in production, because the demo was the model and production is the harness.

That harness is real engineering: controlling the loop, governing which tools the agent can reach, surfacing failures before customers hit them, and enforcing guardrails in code where a prompt would only ask nicely.

It is also most of what you build in the new AI Engineering with Claude Nanodegree program.

Learn More: https://bit.ly/4fOAN7A

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