Udacity✓

Organic traffic is down, everyone says AI is why, and nobody can tell you what to do about it. There’s no shortage of hot takes on this, but marketers don’t need more hot takes. They need practical guidance. On October 27 at 8:00am PT, digital marketing specialist and Udacity mentor Megha Jain is running a live workshop to help. You'll leave with a repeatable processes, not vague best practices. Beginner friendly, no coding needed. Save your seat ➡️

85% of builders worked on AI projects in the past year. But 1 in 3 has never shipped one to production. Udacity surveyed 1,585 tech professionals and found the biggest blockers aren't technical. They're budget, ROI, security, and leadership buy-in. Getting AI to production takes more than building a working demo. Read the full report ➡️

AI is only spooky if you aren't ready for it. Save on our latest courses in AI Engineering, Agentic AI, AI Ops & Security, and more. Explore courses 🎃

AI is writing more of your code. But can you trust it? AI-generated work can look correct, complete, and production-ready. Sometimes it isn’t. As AI becomes standard across the software development lifecycle, knowing how to direct it, evaluate it, and verify its output is now a core skill. Join Udacity and Ascendient Learning, both part of Accenture LearnVantage, for a free webinar with Dr. Dan Grahn. You’ll walk away with: ✅ A clearer view of how AI is changing roles, responsibilities, and risks across the SDLC ✅ The ability to spot where AI-generated errors enter the delivery process ✅ Four guiding principles for working with AI-assisted tools ✅ A practical framework for directing AI and applying meaningful human oversight 📅 Wednesday, October 28, 2026 🕛 12 pm to 1 pm ET Register free:

We just launched a free AI marketing course. 90 minutes. No cost. Here’s what you will learn to build: 🔄 Reusable AI skills that encode your brand voice, product knowledge, and platform guidelines 🗓️ Scheduled routines that run recurring marketing tasks automatically on a cadence 🤖 A system your whole team can use, with human review built in If you have been using AI for individual tasks but still feel like you are doing most of the work yourself, this is the course that closes that gap. Enroll for free →

Swipe to see what you'll build in the new AI Ops Engineer Nanodegree program. Three projects, each one a step deeper into production. A financial news sentiment pipeline. An e-commerce RAG service with evaluation and guardrails. A SalesOps agent with full observability and state replay. Build the portfolio you need to get hired as an AI Ops engineer. Explore the program today →

Most AI projects stall somewhere between "it works on my laptop" and production. The skills that close that gap — versioning models, operating LLM applications at scale, running agents that don't fail silently — are what the new AI Ops Engineer Nanodegree program helps you build. Three months. Three projects. A full production stack from MLOps through LLM Ops to agent operations. Explore the program today →

Security engineers know how to assess a web app. Most don't know how to assess an AI system. ML engineers understand the model. Most can't tell you where the attack surface is. That gap is where production AI gets compromised. We built a Nanodegree program for the engineer who wants to close it. The new AI Security Engineer Nanodegree program covers threat modeling, red teaming, and AI governance across four real projects on AWS. Become an AI security engineer and secure AI, end to end. Learn more →

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:

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: #AIEngineering #Claude #AgenticAI #StructuredOutputs

🤖 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: #Claude #AIAgents #AgenticAI #AIEngineering

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 ➡️

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: #AgenticAI #Claude #MultiAgent #AIEngineering

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: #AgenticAI #Claude #AIGovernance #AIEngineering

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: #Claude #AIEngineering #AgenticAI #LLM

"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 👉 #BackToSchool #AI #MachineLearning #MastersDegree #Udacity #CareerGrowth #LearningAndDevelopment

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: #AIEngineering #AgenticAI #Claude #ProductionAI

A crashed agent gets fixed the same afternoon. An agent that returns a confident wrong answer runs for weeks, because nothing in the stack knows it is wrong until a customer does. Catching that takes evaluation built for agents: scoring task completion, quality, tool use, and reliability at the response, step, and trajectory level. Measuring what agents actually do gets a full course in the new AI Engineering with Claude Nanodegree program. Explore the program: #AIEngineering #AgenticAI #Claude #AIObservability

📊 You wire an agent to custom scraper and database servers over MCP, point it at competitor pricing, and make it gather, reconcile, and reason over what comes back, including the malformed responses and misbehaving tools production data guarantees. The project is called PriceScout, and it's one of the hands-on builds in the new AI Engineering with Claude Nanodegree program. Explore this and other projects today: #Claude #MCP #AIAgents #AIEngineering

The first MCP server most teams ship takes an afternoon. The security review that follows takes a month, because the server can reach every table in the database, the API key is sitting in a config file, and nobody can say what the agent did with any of it. Scoped access, a secret-leak gate in CI, an audited loop: that layer is the actual engineering, and in the AI Engineering with Claude Nanodegree program you build it alongside the server, because in production they are the same job. Learn more: #AIEngineering #MCP #Claude #AgenticAI