Data Science Dojo

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[Data Science Dojo @DataScienceDojo]

The July 14th cohort is coming up soon. 10 weeks. 12,000+ alumni. Spots are filling fast.

The Agentic AI Bootcamp is back and it covers the full stack of what matters right now.

Week 1, you're wrapping your head around how Transformers actually work.

Week 3, you're building with LangChain and setting up your first vector database for a RAG pipeline.

By week 5, you're not just prompting. You're engineering context and designing systems using Agentic design patterns used in production.

Week 7 hits and you're implementing Model Context Protocol and learning how agents actually talk to each other.

Week 10? You ship a multi-agent LLM application. From scratch. In 10 weeks.

That's what the Agentic AI Bootcamp cohort starting July 14th looks like. 3 hours a week, structured to take you from foundations to deployment.

Register now before it's too late: https://t.co/gOKkz5sjhv

#agenticai #rag #aibootcamp #vectordatabases

[Data Science Dojo @DataScienceDojo]

LLM and Agentic AI Bootcamp Information Session https://t.co/QCf472K5bX

[Data Science Dojo @DataScienceDojo]

Once an LLM agent starts calling tools, writing files, and hitting APIs, where it runs becomes a security problem, not a prompting one.

Broad access lets an agent read, write, or call something it shouldn't. The fix is containment.

In this hands-on session, Dan Ndombe, Staff Developer Success Advocate at Docker, will walk through how Docker Sandboxes scope exactly what an agent can touch (filesystem, network, process) before it ever runs.

In this session, you'll learn:
🔹 How Docker Sandboxes isolate an agent's filesystem, network, and process access from the host
🔹 How to spin up a sandboxed agent runtime and hand it a real task end-to-end
🔹 How to read and tighten a sandbox policy: what to allow, what to block, and why
🔹 A reusable containment pattern for your own LLM and agent prototypes, no prior Docker experience required

This is built for engineers building or prototyping LLM agents, DevOps/platform teams deploying AI workloads, and anyone who wants practical guardrails instead of theoretical ones.

📅 September 16, 2026 | 11AM PT
🎙️ Dan Ndombe, Staff Developer Success Advocate, Docker

Register here: https://t.co/GgquhYTuSs

#AgenticAI #AIAgentSecurity #Docker #LLMs #datasciencedojo

[Data Science Dojo @DataScienceDojo]

Agentic AI is moving fast enough that most teams are still figuring out how to build, deploy, secure, and govern it responsibly.

The Agentic AI Conference returns this November to work through exactly that, in the open, with the people actually doing the work.

Across 2 days, the event brings together AI practitioners, researchers, industry leaders, and technology experts through panels, technical sessions, tutorials, and fireside chats spanning architecture, evaluation, real-world deployment, and governance.

What you'll get:
- Real conversations with industry leaders and practitioners actively building agentic AI
- Practical, technical sessions you can apply to your own work
- Insight into where agentic AI is headed, from architecture to governance
- Networking with a global community of AI and data professionals
- Free access to all sessions, no cost to attend

Previous editions have featured speakers from Google, AWS, Microsoft, Oracle, Docker, AMD, Hugging Face, LlamaIndex, SambaNova, LandingAI, Atlassian, and Neo4j, alongside founders and leaders from Ejento AI, CrewAI, Weaviate, Fiddler AI, and Arcade dev.

📅 Nov 9–10, 2026 | Virtual
🎟️ Free to attend

👉 Register here: https://t.co/3PcRyIrPhR

#AgenticAI #AIAgents #DataScienceDojo #AIConference

[Data Science Dojo @DataScienceDojo]

Reasoning, context, and autonomy: those three pillars decide whether you get an agent or just a fancier prompt.

We put together a full roadmap for our upcoming Agentic AI Bootcamp, and it goes deep.

Ten modules that move from transformer fundamentals and self-attention math, through LangChain and LangGraph, into vector databases, context engineering, agentic design patterns, and the protocols (MCP, A2A, ACP) that let agents actually talk to tools and to each other. It closes with a capstone: building and shipping a production-ready multi-agent application.

If you want to see the curriculum in detail and ask questions before you commit, join our live information session.

In this session, you'll learn:
🔹 What the bootcamp covers, module by module
🔹 How the curriculum builds from LLM fundamentals to multi-agent systems
🔹 What the final capstone project looks like
🔹 How to get your specific questions answered live

📅 Thu, Sep 10, 2026 | 12:00 PM PT
🎙️ Raja Iqbal, Founder, Ejento AI
📍 Live Online Session

Register here: https://t.co/KT1LNSXjET

If you've been thinking about building real skills in agentic AI, this is the place to start.

#AgenticAI #LLMAgents #AIBootcamp #datasciencedojo #MachineLearning

[Data Science Dojo @DataScienceDojo]

🎙️ How will visual AI change the way we work in the next 3–5 years?

💡 Dan Maloney, CEO of Landing AI, shares what excites him most: for decades, companies have been drowning in documents — too many humans, too many templates, too many fragile systems. With visual AI and agentic systems, that complexity is finally being resolved — at lower cost, higher trust, and faster speed. But the bigger picture is what happens when you start combining all these building blocks. Doctors and nurses spend more time on paperwork than with patients.

Governments are buried in administrative processes. If visual AI can read, understand, and process what's inside those documents and images, humans get to focus on what they were actually built to do — think strategically, solve real problems, and tackle challenges that matter. Dan compares the data trapped in documents and images right now to the world before we figured out how to harness fossil fuels or solar power. The next few years won't be incremental — they'll be a leap.

🎧 Watch the full episode: https://t.co/x1208WQ3ix
🔗 View all podcasts: https://t.co/dsTN86SjPZ

#VisualAI #DocumentAI #ComputerVision #AIFuture #Healthcare #LandingAI #FutureofDataAndAI

[Data Science Dojo @DataScienceDojo]

Your AI pilot isn't testing the AI. It's testing your organization.

That's the argument Raja Iqbal makes in his latest piece — and it's one every executive planning an agentic AI rollout should sit with before they finalize the budget for the pilot.

Agents don't improvise around broken processes the way people do. They execute exactly what's documented. So the gap between how your company says it runs and how it actually runs — the workarounds, the tribal knowledge, the "ask Marcus" accountability — stops being invisible. It becomes the first thing that breaks.

The companies that win aren't the ones deploying agents fastest. They're the ones treating the pilot as what it is: a forcing function to finally fix the structural debt that was always there — and building the governance to match.

Full piece here: https://t.co/iEPYOy6iu1

#AgenticAI #AIGovernance #EnterpriseAI #AIReadiness #OrganizationalDesign

[Data Science Dojo @DataScienceDojo]

Prompt injection isn't the only way an agent goes rogue. Sometimes it's just doing exactly what it was told, with permissions that were too broad to begin with.

Join Dan Ndombe, Staff Developer Success Advocate at Docker, for a hands-on session on running LLM agents safely using Docker Sandboxes.

We'll spin up a sandboxed agent runtime, give it a real task, then tighten the policy around it so it can only do what it's meant to do.

In this session, you'll learn:
- How Docker Sandboxes isolate an agent's filesystem, network, and process access from the host
- How to hand a sandboxed agent a real task, end to end
- How to read and tighten a sandbox policy: what to allow, what to block, and why
- Common ways "sandboxed" agents leak permissions anyway
- A reusable containment pattern for your own agent prototypes

No prior Docker experience required. We'll build live and take questions.

📅 Wednesday, September 16, 2026 | 11:00 AM – 12:00 PM PT
🎙️ Dan Ndombe, Staff Developer Success Advocate, Docker
📍 Virtual

👉 Register here: https://t.co/zceI23qOWX

#AgenticAI #AIAgentSecurity #Docker #datasciencedojo

[Data Science Dojo @DataScienceDojo]

Master Scaling AI Coding Agents: Cut Costs with Best-of-N https://t.co/FQYNBf0EG8

[Data Science Dojo @DataScienceDojo]

🎙️ What does LASIK for LLMs mean?

💡 Dan Maloney, CEO of Landing AI, explains: LLMs do a great job with text and language — but when it comes to documents, images, and visual data, they're not quite sharp enough. They might even be 90% accurate — but when you're processing hundreds of millions to billions of documents, that small margin of error is extremely costly.

Landing AI brings deep visual AI expertise to give LLMs crystal-clear accuracy on unstructured visual data — turning fuzzy into precise. That's LASIK for LLMs: making the world's documents computable at near-perfect accuracy.

🎧 Watch the full episode: https://t.co/H5ro7rHx88
🔗 View all podcasts: https://t.co/nEdF7gDTUx

#VisualAI #LLMs #DocumentAI #LASIK #LandingAI #FutureofDataAndAI

[Data Science Dojo @DataScienceDojo]

What happens when your AI agent makes the wrong move? 👀

When an agent can read files, run processes, call tools, and access networks, a simple mistake can have real consequences.

That’s why securing AI agents isn’t just about writing better instructions. It’s about controlling the environment they can actually interact with.

Join us for a hands-on session exploring how Docker Sandboxes can help safely run LLM agents with defined boundaries around access, execution, and resources.

📅 September 16, 2026 | 11 AM PT
🎙️ Dan Ndombe, Staff Developer Success Advocate

👉 Register here: https://t.co/tP7eopgkDO

#AgenticAI #LLMAgents #Docker

[Data Science Dojo @DataScienceDojo]

Happening today! 🚨

Scaling AI coding agents can get expensive fast.

Every extra attempt means more inference, compute, and executor time. So how can we give agents more chances to find stronger solutions without letting costs spiral?

Join us today to explore Best-of-N, parallel execution, and smarter serving architectures for scaling AI coding agents.

📅 Today | September 2 | 1 PM PT
🎙️ Kwasi Ankomah, Lead AI Architect at SambaNova Systems

👉 Register here: https://t.co/u7cB2mkZ3Q

#AgenticAI #AICodingAgents #SambaNova

[Data Science Dojo @DataScienceDojo]

Thinking about building your skills in Agentic AI and LLMs?

Not sure where to start or whether a structured bootcamp is the right fit for you?

Join Raja Iqbal for an upcoming Agentic AI & LLM Bootcamp Information Session where we'll walk through the curriculum, what you'll learn, and what to expect from the program.

In this session, you'll learn:
- What the Agentic AI & LLM Bootcamp covers
- What you'll learn throughout the program
- How the curriculum is structured
- Whether the bootcamp is the right fit for your goals
- What to expect from the learning experience
- Get your questions answered live

📅 September 10, 2026 | 12:00 – 1:00 PM PT

Whether you're looking to deepen your AI skills, understand how LLM-powered agents work, or take the next step in your AI journey, this session is a great place to start.

Register here: https://t.co/XOCNMgx75F

#AgenticAIbootcamp #LLMBootcamp

[Data Science Dojo @DataScienceDojo]

🎙️ $5 Billion a Year on AI — Miscalculation or Bet?

💡 Dan Maloney, CEO of Landing AI, breaks down what's really happening: Facebook's token budget alone was estimated at $5 billion per year. Companies like Meta and Microsoft went all-in early — and now they're adjusting. Dan says that's not a miscalculation, it's how new technology works.

You loosen the guardrails first to see what's possible, then tighten once you understand what delivers. The real metric? If $5 billion in spend drives $100 billion in returns, nobody's complaining. It only becomes a problem when the outcomes aren't there. And this cycle isn't new — the same thing played out when companies moved from on-prem to SaaS. We're still early, and everyone's finding the right balance together.

🎧 Watch the full episode: https://t.co/pF3KeEmQop
🔗 View all podcasts: https://t.co/SfzMnDBXtQ

#AISpending #EnterpriseAI #Meta #Microsoft #TokenUsage #LandingAI #FutureofDataAndAI

[Data Science Dojo @DataScienceDojo]

Your AI coding agent is burning money in the executor.

Every agent session can involve dozens of edits, test-fix cycles, and parallel candidate solutions. At scale, the executor layer determines both how fast your agents run and how much they cost.

Join Kwasi Ankomah, Lead AI Architect at SambaNova Systems, for a hands-on webinar on scaling AI coding agents without scaling your bill.

📅 September 2, 2026 | 1 PM – 2 PM PDT

In this session, you'll learn:
- Where coding agents spend time and money  
- How parallel execution changes the economics of scaling  
- How best-of-N selection picks the strongest candidate solutions  
- How disaggregated serving affects throughput, latency, and utilization  
- Which serving decisions make test-time compute financially viable  
- How to evaluate the executor costs of your own AI agent infrastructure  

🔗 Register here: https://t.co/vN6VeeysZe

#datasciencedojo #sambanova #codingagents

[Data Science Dojo @DataScienceDojo]

Your next coworker might not be human. 🤖

"Works on my machine" has always been a dev challenge — but it gets a whole lot weirder when the one writing code, running commands, and spinning up infrastructure is an AI agent.

Join Michael Irwin, Principal Software Engineer for Developer Success at Docker, for a hands-on session on building reproducible environments for AI applications and the AI coding agents that work alongside them.

In this session, you'll learn how to:
🔹 Build a reproducible AI app environment using containers and Docker Compose
🔹 Understand why AI agents need an extra layer of isolation beyond regular containerized apps
🔹 Use Docker Sandboxes to give agents a safe space to work
🔹 Keep agent configurations portable with environment files
🔹 Create a shared dev environment for humans and agents alike
🔹 Build a mental model for choosing the right isolation boundary
🔹 Get hands-on practice wiring it all together

🗓️ August 28, 2026 🕘 9 AM – 11 AM PT

👉 Register: https://t.co/x40q547FNP

#datasciencedojo #docker

[Data Science Dojo @DataScienceDojo]

🎙️ Revenue is growing 50%. Headcount isn't. So who's doing the work?

💡 Dan Maloney, CEO of Landing AI, breaks down what's quietly happening inside enterprises right now. Revenue is climbing, business is growing — but headcount is staying flat or shrinking. Budgets are shifting into AI. The mandate is clear: do more with less. One example? Banks growing their customer base 50% year over year — with everything that comes with it — but doing it with the same number of people or fewer. That's the point where AI stops being an experiment and becomes the only way to scale.

Companies are hitting the ceiling of what they can do with people alone, and that's exactly where automation is stepping in.

🎧 Watch the full episode: https://t.co/P4W7OXrH2r
🔗 View all podcasts: https://t.co/uvz8cURaNy

#EnterpriseAI #Automation #AIStrategy #DoMoreWithLess #LandingAI #FutureofDataAndAI

[Data Science Dojo @DataScienceDojo]

💸 Your AI coding agent isn't burning money in the planning step — it's burning it in the executor: dozens of edits, test-fix cycles, and parallel candidate solutions running side by side.

Join Kwasi Ankomah, Lead AI Architect at SambaNova, for a hands-on webinar on scaling AI coding agents without scaling your bill.

🗓️ September 2, 2026 | 🕐 1 PM – 2 PM

In this session, you'll learn:
- Where coding agents actually spend time and money
- How parallel SambaNova executors change scaling economics
- How best-of-N selection picks winning candidates
- How disaggregated serving affects throughput and latency
- The serving decisions that make scaling financially viable
- How to evaluate your own agent infrastructure costs

🔗 Register here: https://t.co/j674JBumS3

#datasciencedojo #sambanova #codingagents

[Data Science Dojo @DataScienceDojo]

🎙️ What's the biggest mistake enterprises make when adopting AI?

💡 Dan Maloney, CEO of Landing AI, says it's trying to do everything at once. It sounds cliché, but don't boil the ocean. Companies that went everywhere with AI ended up with a $100M to $5B bill and nothing to show for it. The fix? Pick one use case that's core to your business — something that's growing but can't be solved by throwing more people at it. Prove it works there first.

What you learn from that one case applies to everything else downstream. You can test faster, throw away what doesn't work quicker, and actually measure impact.

🎧 Watch the full episode: https://t.co/0ephXcSxLA
🔗 View all podcasts: https://t.co/zyMmfknEft

#AIStrategy #EnterpriseAI #AgenticAI #Automation #LandingAI #FutureofDataAndAI

[Data Science Dojo @DataScienceDojo]

🚨 Your LLM agent can call APIs, write files, and take actions on its own — do you know where it's actually running?

Join Dan Ndombe, Staff Developer Success Advocate at Docker, for a hands-on webinar on running LLM agents safely using Docker Sandboxes (SBX).

🗓️ September 16, 2026 | 🕚 11 AM – 12 PM

In this session, you'll learn:
- How Docker Sandboxes isolate an agent's filesystem, network, and process access from the host
- How to spin up a sandboxed agent runtime and hand it a real task end-to-end
- How to read and tighten a sandbox policy — what to allow, what to block, and why
- Common ways "sandboxed" agents leak permissions anyway (and how to avoid them)
- A reusable pattern for your own LLM and agent prototypes — no prior Docker experience required

🔗 Register here: https://t.co/G8XFzOJyvv

#datasciencedojo #docker #dockersandboxes

[Data Science Dojo @DataScienceDojo]

🎙️ How do you stop LLMs from hallucinating when processing documents?

💡 Dan Maloney, CEO of Landing AI, breaks down where LLMs go wrong — and it's not a single-company problem. Anthropic, Google, OpenAI — all of them showed the same inconsistencies early on.

His fix: don't hand an LLM a whole document and hope for the best. Break it down so simply that the LLM's job is narrow and repeatable, then build smaller, purpose-built models for the parts LLMs are inconsistent at. Only pass on to the LLM what it's actually reliable on.

🎧 Watch the full episode: https://t.co/rPmQ1DB4w1
🔗 View all podcasts: https://t.co/bn8yehHRsi

#LLMs #Hallucination #DocumentAI #AgenticAI #LandingAI #FutureofDataAndAI