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Clear Progression Toward a Career Outcome. This track offers a cohesive roadmap. Instead of randomly selecting courses, you follow a sequenced, job-aligned path — starting from prompt engineering and building to production agentic systems. Each course builds on the previous one, leading to better retention and job readiness.
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Motivation Through Milestones. Each completed course becomes a motivational checkpoint. You can see tangible progress, both professionally (gaining production skills and digital badges) and in your portfolio (each capstone produces a working system you can demonstrate to employers).
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Value in Commitment and Structure. Enrolling in a track signals commitment to a longer-term goal, which may unlock priority access to training or mentors, additional support from advisors who track your progression, stackable credentials or digital badges tied to the full track.
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Alignment with Reimbursement Policies. Even if you are reimbursed after each course, being enrolled in a Track ensures pre-approval for funding bodies (VA, workforce boards, etc.), easier tracking of eligibility and status, and full utilization of benefits (since some funding expires or has usage caps).
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Production-Ready Portfolio. Unlike theoretical courses, every module includes hands-on labs using real tools — Neo4j, Pinecone, n8n, Claude — and every course culminates in a capstone project. By program completion, you have eight working systems demonstrating your capabilities to employers.
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AI Study Companions Included. Every course includes an AI-powered study companion that explains concepts, helps debug labs, quizzes you on material, and suggests study paths — available 24/7 throughout your learning journey.
AI Systems Builder
The AI Systems Builder Program is a structured eight-course path from prompt engineering to production AI. Master RAG, knowledge graphs, workflow orchestration, eval-driven development, AI-assisted coding, agentic systems, and FinOps/GRC with hands-o
About this Track
The AI Systems Builder Program track is designed to develop professionals who can design, build, and operate production-grade AI systems. If you're unfamiliar with the term "AI Systems Builder," think of it as the engineering discipline of creating intelligent automation — it's the practice of combining retrieval, reasoning, orchestration, and governance into reliable systems that organizations can trust and scale.
This track combines eight progressive courses to give learners a complete, hands-on path from foundational AI skills to enterprise-ready system deployment. It draws from practices and tools used across three critical disciplines:
The Three Pillars
Product Management: Every AI system is a product that serves users and stakeholders. This track teaches you to think in terms of requirements, trade-offs, user stories, and business case justification — not just technical demos. Every capstone requires you to articulate why your system matters, not just how it works.
Systems Thinking Organizations are dynamic systems with feedback loops, bottlenecks, and emergent behavior. This track prevents the common failure mode of building isolated automations that optimize one step while degrading the whole. You'll learn to see how your AI systems fit into larger organizational processes.
Compliance Management Every AI system operates within regulatory, ethical, and organizational constraints. This track teaches data governance, audit trails, access controls, explainability, and risk mitigation — designed in from Course 1, not bolted on at the end.
With this combination, learners are prepared to build both intelligent retrieval systems and autonomous agent architectures, gaining the full-stack AI engineering skills essential for enterprise and government roles.
What You Will Learn
This track builds foundational, technical, and strategic skills in AI systems design and deployment. Learners will move from hands-on prompt crafting to architecting production-grade intelligent systems.
With FinOps & GRC included, learners not only build capable AI systems but are also positioned as leaders in responsible, cost-effective AI deployment. This track not only prepares learners for technical implementation — it also teaches how to think like an AI Systems Architect.
Who is this Track for:
This track is ideal for:
- Career Transitioners — Individuals entering IT and AI for the first time, looking for a structured path from fundamentals to production-ready skills. No prior coding or IT experience required.
- Military Veterans and Service Members — Those transitioning to civilian AI and technology careers, leveraging the structured, mission-oriented learning approach and veteran-centered examples throughout the curriculum.
- Aspiring AI Engineers — Professionals seeking to move beyond prompt crafting into designing and deploying complete AI systems for enterprise environments.
- IT Professionals Upskilling — Current technology workers who want to add production AI, knowledge graphs, and agentic systems to their skill set.
- Military and Government Personnel — Those working in or transitioning to roles involving AI systems, intelligent automation, or data-driven decision support in government contexts.
- Team Leads and Technical Managers — Leaders who need to understand the full AI systems stack to make informed architecture, vendor, and staffing decisions.
- Compliance and Risk Professionals — Those who need to understand AI governance, audit trails, and responsible deployment practices from the inside out.
- Cleared Professionals and Federal Contractors — Those looking to build AI systems capabilities applicable to DoD and federal agency environments.
Courses in this Track
Prompt Engineering
Learn to design, test, and version structured prompts across Claude and ChatGPT. Build custom AI tools, run professional evaluations, and embed AI into browser and spreadsheet workflows. No coding required.
Mastering RAG
Build production-ready Retrieval-Augmented Generation systems. Learn LLM fundamentals, RAG architectures, chunking, embeddings, retrieval, prompting, evaluation, & enterprise-scale design to deliver accurate, observable, & trustworthy AI applications
Knowledge Reasoning
Build hybrid AI systems that reason over knowledge, not just retrieve text. Combine Neo4j knowledge graphs with Pinecone vector search through n8n workflows and Claude MCP to deliver accurate, explainable, production-ready AI.
Workflow Orchestration
Build multi-agent AI systems in n8n 2.0. Design agentic workflows with memory, human-in-the-loop approval, MCP integration, evaluation pipelines, and Chat Hub deployment. 8 sessions. No coding required. Leave with a production-ready capstone.
Evaluation-Driven Development
Stop guessing if your AI works. Learn to build continuous evaluation systems — reference datasets, automated metrics, LLM judges, and production monitoring — using hands-on labs with Langflow and Arize Phoenix. From vibes to flywheels.
Taught by world class instructors:
Sravan Ankaraju
Principal Instructor
Frequently Asked Questions:
The AI Systems Builder Program is a structured eight-course track that takes you from foundational prompt engineering through production AI deployment, covering RAG, knowledge graphs, workflow automation, evaluation, coding, agentic systems, and governance.
Each course stands on its own and awards a digital badge upon completion. However, completing the full track provides the most comprehensive skill set and the strongest portfolio for employers.
You'll work with Neo4j AuraDB, Pinecone, n8n, Claude (with MCP integration), LLM Graph Builder, GraphGPT, and other production AI tools. All tools used have free tiers — no additional software purchases required.
Yes. Each course builds on the skills and systems developed in the previous course. The recommended sequence is: Prompt Engineering → Context Engineering → Knowledge Reasoning → Workflow Orchestration → Eval-Driven Development → AI-Assisted Coding → Agentic Systems → FinOps & GRC.
Each course consists of 8 sessions at 4.5 hours per session (36 hours per course). The full track is 280+ hours of instruction across eight courses. Completion timeline depends on scheduling and your pace through self-study materials.
AI Engineer, AI Systems Architect, Intelligent Automation Specialist, AI Solutions Developer, RAG/Knowledge Graph Engineer, AI Operations Analyst, and related roles in enterprise AI implementation.
Yes. The curriculum covers governance, compliance, audit trails, and explainability — skills directly applicable to DoD, federal civilian, and government contractor AI roles.
No. All labs use visual, low-code tools. The track is designed for career transitioners entering AI as their first professional IT role. No Python, no Jupyter notebooks, no prior programming required.
Each course awards a digital certificate with a verifiable badge for your LinkedIn profile. Completing the full track awards the AI Systems Builder Program credential, plus a portfolio of eight capstone projects demonstrating production-ready AI skills.
Checklist
A track delivers structured guidance, increased motivation, cumulative value, and career credibility - benefits that go fat beyond the sums of its individual courses.