Starts May 30
~6 months
Track
Data Center Engineer
From megawatts to AI clusters: power, racks, cooling, network, operations, and data center economics.
Access to a Discord community of heavy hitters
A lot of hands-on practice, flash tests, and final projects
Mentors, checkpoints, and mock interviews
Lifetime access and permanent updates
TrackThis bootcamp is based on the LMS course /datacenters: 6 modules, 24 lessons, and 6 practices about AI data centers. You build a site map, single-line power diagram, rack budget, thermal loop, network map, and incident memo so the data center becomes a connected compute factory, not a black box.
- Go through 6 modules, 24 lessons, and 6 practices from the LMS course /datacenters
- Map an AI site: critical IT power, PUE, racks, water, network lead time, and regional constraints
- Trace the megawatt path: grid, transformers, switchgear, UPS, PDU, A/B power, and redundancy
- Budget an AI rack and explain the trade-off between air cooling and direct-to-chip liquid cooling
- Build a leaf-spine, storage, management/OOB map and diagnose bottlenecks in a training cluster
- Create a runbook and incident memo with telemetry, hypotheses, checks, and a safe next step
Data Center Engineer
Who this track is for
New
Engineers and builders who want to understand AI infrastructure through power, cooling, racks, and network constraints
Pro
DevOps, SRE, and backend engineers who need to read the system from GPU host to leaf-spine network and storage path
Infrastructure founders and product leads who model capacity, connection timelines, bottlenecks, CapEx, OpEx, and TCO
People working around GPU clusters who need a shared language with facility, network, and operations teams
Analysts and operators who need the practical loop: telemetry, runbook, incident memo, and fact-based decisions
Curriculum
6 modules and 24 lessons: site mapping, power path, racks, cooling loops, leaf-spine networking, bottlenecks, CapEx, and incident runbooks.
01
Data Center Map
02
Electrical Power
03
Racks and Compute
04
Cooling
05
Network and Cluster
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Platform
A crypto-native platform packed with research-backed learning tools and designed by a former Rarible product lead.
- Wallet-based loginNo logins or passwords — just connect MetaMask from any device and start learning.
- MicroformatsThe material is broken into small, easy-to-digest blocks so you can keep moving even if you only have 15 minutes a day.
- Active learningInteractive tasks and exercises that let you apply new knowledge in practice. Larger courses lead to a final project or capstone where separate skills come together in one result.
- Code firstThe platform is built for working with code: built-in editor, dark theme, and syntax highlighting like in your usual VS Code or Remix IDE.
CommunityA community of AI and crypto enthusiasts, developers, cryptographers, engineers, auditors, and investors who sharpen each other’s craft and form teams together.
Daily streams, no days off
01
Live coding
Hands-on development with a mentor — the closest alternative to pair programming, still the gold standard of effective skill transfer in IT.
02
AMA with experts
Top developers and project founders answer questions from the room, explain how the industry really works, and share insights and alpha.
03
Market reviews
Weekly summaries from GuideDAO researchers on the hottest sectors: from fresh papers on LLMs and agent architectures to DeFi narratives, hack breakdowns, and global regulation.
Career
Our goal is for you to outgrow the DAO as fast as possible — launch your own project or join a global startup.
Mock interviews
A simulation of a technical interview with active developers and team leads — like Total Recall on Valocordin.
Portfolio
Nothing sells you better than a GitHub profile packed with real production-grade architecture cases — whether it’s a complex smart contract or an autonomous AI agent.
Success stories
Graduates share their wins, explain how they found work in AI and crypto, and pass résumé hacks on to newcomers.