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The Executive Fellowship (Both Technical and Non Technical AI Tracks)
Thu, Jan 29, 2026
9:00 am – 5:00 pm EST
Assist Prof. Bright
Frimpong,
Limited Capacity
We offer two distinct tracks designed for different career stages and levels of commitment. Both are rigorous, university-level programs, but they lead to different outcomes.
Standard courses are designed to transfer information; the Executive Fellowship is designed to transfer authority and total career rebrand.
Most market offerings provide generic, pre-recorded content taught by peers or enthusiasts. This Fellowship is a rigorous, scientist-led immersion. You are trained directly by Faculty Leads with PhDs and deep-tech pedigrees, utilizing proprietary intellectual property (like our VIPER Protocol) not available to the public. Furthermore, we do not rely on simulations alone; we guarantee real-world execution through our B2B consulting wing. This is not a course; it is career re-architecture.
Because complex AI risk cannot be solved with generic compliance theory. The current landscape is filled with noise and surface-level understanding. By learning directly from deep-domain scientists and experts, you receive an immediate transfer of high-status credibility. You learn the rigorous mental models required to diagnose issues that standard professionals miss entirely.
We are looking for high-caliber professionals with strong existing domain expertise—such as legal counsel, risk officers, compliance directors, senior auditors, or technical leaders—who realize their current playbook is becoming obsolete.
You do not need to be an AI expert today, but you must possess high professional resilience, critical thinking skills, and the ambition to pivot into a senior leadership or high-value consulting role as an AI Governance Architect.
No. Our goal is not to turn you into a machine learning engineer; our goal is to make you capable of auditing and governing them.
While we do not require prior coding experience, we do require "technical courage." You must be willing to enter our sandboxed technical labs (RatioMesh Labs) and get hands-on with enterprise tools. We provide the scaffolded environment and proprietary protocols to give you the necessary technical fluency to command respect in a boardroom of engineers.
The "experience paradox" is the biggest barrier to entering high-level AI governance: you cannot get the job without experience, but you cannot get experience without the job.
We solve this by leveraging RatioMesh’s B2B consulting wing. We guarantee every Fellow placement on a live audit for a real enterprise client. During this phase, you cease acting as a "student" and act as a Junior Partner under a seasoned RatioMesh Industry Lead. You will be on the front lines, executing the audit and delivering the final boardroom-ready report.
ou will be applying the proprietary frameworks learned during the immersion phase to real-world problems. This may include auditing for "Shadow AI" data leakage, stress-testing RAG (Retrieval-Augmented Generation) architectures for security flaws, or evaluating compliance with emerging regulations like the EU AI Act using our scientific models.
You are not just taught skills; but you are taken t hrough a full re-engineering of your professional identity. Through our "Executive Career Architecture" pillar, we overhaul your CV, LinkedIn profile, and professional narrative to reflect your new status. We use your completed Enterprise Residency as irrefutable proof of competence. We coach you specifically on the tone, posture, and executive signaling required to command top-tier consulting fees or secure senior internal leadership roles.
Choose the track that aligns with your professional trajectory—from strategic pivots to elite architectural tenure.
From $10,000
Monthly financing options coming soon*Financing via Climb Credit/Meritize (US) or StepEx (UK)coming soon
*Subject to credit approval and terms.
| Feature / Benefit | Standard | Career Pro | Executive |
|---|---|---|---|
| 14-Week Curriculum | ✔ | ✔ | ✔ |
| Weekly Live Sessions | ✔ | ✔ | ✔ |
| TA Support | Business hours | Priority | Priority + private channel |
| Intermediate Project + Capstone | ✔ | ✔ (Advanced optional) | ✔ + priority supervision |
| GitHub Portfolio Setup | ✔ | ✔ (with optimisation) | ✔ (advanced refinement) |
| Career Curriculum (Weeks 10–14) | — | ✔ | ✔ (extended) |
| CV, LinkedIn, GitHub Review | — | ✔ | ✔ (executive positioning) |
| Mock Interviews | — | ✔ (technical + behavioural) | ✔ (advanced + coaching) |
| 90-Day Job Strategy Plan | — | ✔ | ✔ (executive-level) |
| Cloud Certification Vouchers | — | ✔ (1 exam/year) | ✔ (Up to 3 attempts) |
| Portfolio Aftercare (12 weeks) | — | ✔ | ✔ (extended) |
| Access to Project Lab | — | ✔ | ✔ (priority) |
| Private Masterclasses | — | ✔ | ✔ (executive-only) |
| Talent Vault Access | — | ✔ | ✔ (priority placement) |
| Senior Mentor | — | — | ✔ |
| Direct Slack Access to Faculty | — | — | ✔ |
| Executive Coaching | — | — | ✔ |
| Priority Hiring Introductions | — | — | ✔ |
| Offer Negotiation Support | — | — | ✔ |
| Exclusive LLMOps/RAG Clinics | — | — | ✔ |
| Executive Alumni Circle | — | — | ✔ |
| Job Guarantee | — | — | ✔ |
The structure is divided into three 12 (+4) week phases: Foundation, Architecture, and Deployment.
Master the regulatory landscape, the threat vectors, and the “governance mindset.” Stop thinking like a user, start thinking like a regulator.
The 12-Week Strategic Shield: From Regulatory Risk to Enterprise Trust
| Curriculum Phase | Week & Core Focus | Executive Outcome & Artifact |
|---|---|---|
| Phase 1: Foundation & Strategic Alignment (Weeks 1-4) | ||
| The Mandate | Week 1: AI Governance Landscape & C-Suite Buy-in | Artifact: Enterprise AI Governance Charter (Roles, Scope, & Mandate) |
| Risk Frameworks | Week 2: Operationalizing Risk (NIST AI RMF & ISO 42001) | Artifact: Level 1 AI Risk Register (NIST-mapped taxonomy) |
| Regulatory Laws | Week 3: The Regulatory Tsunami (EU AI Act & Global Compliance) | Artifact: Regulatory Gap Analysis Memo (Compliance Posture Audit) |
| Data Privacy | Week 4: Data Governance & Privacy by Design (AIGP Domain 4) | Artifact: AI Data Suitability Assessment (Bias, PII, & Copyright Audit) |
| Phase 2: Technical Execution & Engineering Guardrails (Weeks 5-8) | ||
| Usage Policy | Week 5: Governing GenAI Risks & Shadow AI Mitigation | Artifact: Corporate GenAI Acceptable Use Policy (AUP) |
| System Defense | Week 6: Technical Guardrails: Input/Output Filtering | Artifact: Guardrail Configuration Log & Red-Team Test Report |
| RAG Security | Week 7: Governing RAG & Grounding Truth Systems | Artifact: RAG Governance Architecture Diagram (Annotated Control Points) |
| Monitoring | Week 8: LLMOps Governance & Continuous Monitoring | Artifact: AI Monitoring Dashboard (Drift, Fairness, & KRI Tracking) |
| Phase 3: Auditing, Strategy & Career Authority (Weeks 9-12) | ||
| Vendor Risk | Week 9: Third-Party & Supply Chain AI Risk Management | Artifact: B2B AI Vendor Due Diligence Questionnaire |
| Conformity | Week 10: The AI Audit & Conformity Assessment | Artifact: Final Audit Readiness Report (Evidence Compilation) |
| Capstones | Week 11: The "Shark Tank" Strategy Defense | Artifact: Verified Complete AI Governance Portfolio |
| Certification | Week 12: Career Strategy & IAPP AIGP Exam Prep | Artifact: Authority Brand & Market-Ready LinkedIn/Resume |
| Strategic Comparison | Governance Strategy Track | The Titan Fellowship |
|---|---|---|
| Target Role | AI Compliance Officer / AI Risk Lead | Chief AI Officer (CAIO) / DPO |
| Regulation Focus | General Compliance (EU/NIST) | Cross-Jurisdictional Arbitrage |
| Security Depth | Operational Guardrails | Adversarial Red-Teaming & Forensic Audit |
Master the Industrial land
The 12-Week Elite Execution Path: From Strategy to Deployment
| Curriculum Phase | Week & Core Focus | Executive Outcome & Artifact |
|---|---|---|
| Phase 1: Opportunity Identification & Business Alignment | ||
| Market Dynamics | Week 1: The AI PM Mandate & Strategic Selection | Artifact: AI Opportunity Thesis (ROI & Use-Case Mapping) |
| Data Strategy | Week 2: Data Flywheels & Intellectual Property | Artifact: Data Acquisition & Proprietary Flywheel Map |
| Competitive Moats | Week 3: Defensibility in the LLM Era | Artifact: Competitive Moat Analysis & Unit Economics |
| User Psychology | Week 4: UX for Probabilistic Systems | Artifact: AI UX Wireframes & Trust-Failure Maps |
| Phase 2: Stakeholder Leadership & Business Intelligence | ||
| Executive Buy-in | Week 5: Stakeholder Mapping & Political Engineering | Artifact: AI Steering Committee Charter |
| Financial Modeling | Week 6: Cost-to-Serve & Inference Economics | Artifact: 3-Year AI Product Financial Forecast |
| Legal & Compliance | Week 7: AI Product Governance (EU AI Act/NIST) | Artifact: Regulatory Conformity Assessment Memo |
| Metric Design | Week 8: Defining "Success" Beyond Accuracy | Artifact: Executive KPI Dashboard (Business vs. Model) |
| Phase 3: Technical Execution & Security Guardrails | ||
| Model Selection | Week 9: Buy vs. Build vs. Fine-Tune Logic | Artifact: Technical Feasibility & Model Selection Matrix |
| Security Design | Week 10: Security Guardrails & Input/Output Filtering | Artifact: AI Safety Audit & Red-Team Test Report |
| Architecture | Week 11: RAG Governance & Grounding Truth | Artifact: Annotated RAG Governance Architecture |
| Ops & Monitoring | Week 12: MLOps for PMs & Continuous Drift Detection | Artifact: AI Monitoring & Model Lifecycle Protocol |
| Phase 4: GTM Mastery & Professional Authority | ||
| Market Entry | Week 13: GTM Strategy & Value-Based Pricing | Artifact: AI Product Launch & Pricing Playbook |
| Growth Scaling | Week 14: Product Growth & Viral AI Loops | Artifact: Scalability Roadmap & Technical Debt Audit |
| Final Portfolio | Week 15: Capstone Defense & Executive Pitch | Artifact: Verified AI Product Management Portfolio |
| Authority Launch | Week 16: Career Branding & The "Cyborg" Profile | Artifact: Optimized AI-Authority Brand & Mock Interview |
| Executive Comparison | Product Strategy Track | The Titan Fellowship |
|---|---|---|
| Professional Identity | AI Product Manager (AIPM) | Chief AI Officer / Lead Architect |
| Admission Status | Open Enrollment | By Selection Interview Only |
| Credentialing | Certified AI Product Lead | RatioMesh Accredited + ICO Priority |
| Phase 1: Market Intelligence & Strategic Vision (Weeks 1-4) | ||
| Weeks 1-2 | AI Opportunity Thesis & ROI Mapping | Cross-Border Market Arbitrage |
| Weeks 3-4 | Competitive Moat & Unit Economics | Proprietary IP Strategy (VIPER) |
| Phase 2: Technical Architecture & Stakeholder Synergy (Weeks 5-8) | ||
| Weeks 5-6 | Feasibility Matrix: RAG vs. Fine-Tuning | Enterprise Red-Teaming & RAG Auditing |
| Weeks 7-8 | Engineering Alignment & Tech-to-Biz Translation | C-Suite Communication War Room |
| Phase 3: Lifecycle Governance & Ethical Scalability (Weeks 9-12) | ||
| Weeks 9-10 | AI Safety UX & Hallucination Guardrails | Global Regulatory Compliance (EU/NIST) |
| Weeks 11-12 | MLOps Governance & Drift Monitoring | Advanced TARA & CAGA Protocols |
| Phase 4: GTM & Executive Career Launch (Weeks 13-16) | ||
| Weeks 13-14 | Pricing Strategy & GTM Playbook Launch | Guaranteed B2B Audit Deployment |
| Weeks 15-16 | Portfolio Review & Certification Bridge Prep | "Work Till Placed" Consultancy Bridge |
| Next Step | Secure Your Spot | Request Selection Interview |
The AI Product Management track is designed for leaders ready to move beyond "Product Management" into the realm of Probabilistic Strategy. We seek professionals who demonstrate:
The ability to translate complex model limitations into business-centric risk strategies for engineers and stakeholders.
A mastery of AI unit economics and the strategic intuition required to build defensible market moats.
The executive presence to manage cross-functional friction between Data Science, Legal, and Marketing teams.
This track creates the “Foundational Architects” who command the highest market premiums.
The 28-Week Production Path: From Experimentation to Global Scale
| Curriculum Phase | Weeks & Core Focus | Engineering Outcome & Industrial Project |
|---|---|---|
| Phase 1: MLOps Foundations & Experiment Tracking (Weeks 1-8) | ||
| Lifecycle Design | Weeks 1-2: The LLM Lifecycle & Dev Environment Setups | Project: "The Reproducible Lab"—Setting up a containerized dev-to-prod environment with Docker & DevContainers. |
| Experimentation | Weeks 3-4: Experiment Tracking with MLflow & W&B | Project: Hyperparameter tuning and prompt versioning for a Sentiment Analysis Engine at scale. |
| Data Versioning | Weeks 5-6: Data Lineage & Feature Stores (DVC/Feast) | Project: Pipeline for a Dynamic Pricing Model with automated data versioning and rollback triggers. |
| CI/CD for ML | Weeks 7-8: Automated Testing & GitHub Actions for AI | Project: A "Clean Code" CI/CD pipeline that runs unit tests on model logic and data schema validation automatically. |
| Phase 2: Advanced RAG & Compound AI Systems (Weeks 9-16) | ||
| Vector Ops | Weeks 9-10: Production Vector DBs & Indexing Strategies | Project: Enterprise Knowledge Base—Optimizing HNSW vs. IVF indices for sub-50ms retrieval on 1M+ documents. |
| Retrieval Engineering | Weeks 11-12: Hybrid Search & Re-ranking (ColBERT/Cross-Encoders) | Project: A Legal Discovery RAG system using semantic and keyword hybrid search to ensure 99% recall. |
| Evaluation Frameworks | Weeks 13-14: RAGAS & DeepEval for Automated Quality Checks | Project: An automated Evaluation Harness that calculates Faithfulness and Relevancy scores for every model iteration. |
| Context Management | Weeks 15-16: Semantic Caching & Context Window Optimization | Project: Cost-Saving Proxy—Implementing GPTCache and Redis to reduce API costs by 40% via prompt-deduplication. |
| Phase 3: Deployment, Serving & High-Availability (Weeks 17-24) | ||
| Inference Serving | Weeks 17-18: Serving with vLLM, TGI & NVIDIA Triton | Project: Deploying an Open-Source Llama-3 API optimized for high-throughput batch inference. |
| Orchestration | Weeks 19-20: Kubernetes for ML (Kueue/Kserve) | Project: Auto-scaling an AI inference cluster on K8s that reacts to "GPU utilization" spikes during peak traffic. |
| Monitoring & Drift | Weeks 21-22: Observability with Prometheus, Grafana & Arize | Project: Drift Detection Dashboard—Alerting on "concept drift" in a Fraud Detection System. |
| Security & Guardrails | Weeks 23-24: NeMo Guardrails & PII Anonymization Pipelines | Project: Medical HIPAA Auditor—A real-time PII scrubbing and safety filtering layer for healthcare LLMs. |
| Phase 4: Optimization & Professional Residency (Weeks 25-28) | ||
| Industrial Capstone | Weeks 25-26: The "Alpha X" MLOps Residency | Project: Global Supply Chain Predictor—An end-to-end autonomous pipeline that retrains, validates, and deploys every 24 hours. |
| System Defense | Week 27: Final Architecture Defense (The "Whiteboard" Challenge) | Outcome: Verified architectural blueprints for a 10,000-user concurrent AI system. |
| Authority Launch | Week 28: Career Brand Architecture & Salary Negotiation | Outcome: Optimized "MLOps Specialist" Profile & Interview Prep for FAANG/High-growth startups. |
The 28-Week Master Engineering Path: From Reasoning to Autonomous Swarms
| Curriculum Phase | Weeks & Core Focus | Engineering Outcome & Industrial Project |
|---|---|---|
| Phase 1: Agentic Reasoning & Tool Foundations (Weeks 1-8) | ||
| LLM Internals | Weeks 1-2: Advanced Prompting & Reasoning Loops | Project: Chain-of-Thought (CoT) & ReAct Reasoner for complex logical tasks. |
| Tool Integration | Weeks 3-4: Function Calling & API Orchestration | Project: Building "The Tool-Belt"—A multi-tool agent capable of executing SQL, Python, and Web-Search. |
| Context & Memory | Weeks 5-6: Episodic vs. Semantic Memory Systems | Project: Personal Knowledge Graph Agent with long-term memory persistence (Vector DBs). |
| Evaluation | Weeks 7-8: Agentic Evals & Benchmarking | Project: An automated "Red-Teaming" suite to test agent reliability and hallucination rates. |
| Phase 2: Multi-Agent Orchestration & Swarm Design (Weeks 9-16) | ||
| Framework Mastery | Weeks 9-10: Deep Dive into CrewAI & LangGraph | Project: Hierarchical "Creative Studio"—A swarm of 3 agents (Writer, Critic, Publisher). |
| Communication | Weeks 11-12: Inter-Agent Communication Protocols (MCP) | Project: Cross-platform Sync Agent: Agents communicating via Slack, Email, and Jira to manage tasks. |
| Decision Logic | Weeks 13-14: Supervisor Patterns & Task Decomposition | Project: The "Project Manager Agent" that decomposes vague Jira tickets into executable code sub-tasks. |
| State Management | Weeks 15-16: Graph-based State & Persistence | Project: Multi-turn "Customer Support Swarm" with complex state hand-offs and human-in-the-loop gates. |
| Phase 3: Production Engineering & System Guardrails (Weeks 17-24) | ||
| Security | Weeks 17-18: Agentic Security & Prompt Injection Defense | Project: Hardened Financial Agent with input-sanitization and sandbox execution environments. |
| Infrastructure | Weeks 19-20: Cloud Deployment & Containerization (Docker/K8s) | Project: Scalable Agent-as-a-Service API deployed on AWS/GCP with rate-limiting. |
| Observability | Weeks 21-22: Monitoring & Tracing (LangSmith/Weights & Biases) | Project: Live Performance Dashboard for a swarm, tracking latency, cost, and "reasoning path" success. |
| Fine-Tuning | Weeks 23-24: Domain-Specific Agent Tuning (LoRA/QLoRA) | Project: Fine-tuned Llama-3 model optimized for a specific industry "Voice" or "Knowledge Base." |
| Phase 4: Capstone Residency & Career Launch (Weeks 25-28) | ||
| Industrial Capstone | Weeks 25-26: Enterprise "Alpha X" Swarm Residency | Project: **The Digital Employee**—A fully autonomous business unit (e.g., SDR Swarm or Automated Legal Auditor). |
| Portfolio Defense | Week 27: Final Review & Technical Demo Day | Outcome: Verified GitHub Repository with 5+ Production-Grade Agentic Systems. |
| Authority Launch | Week 28: Career Brand Architecture & Salary Negotiation | Outcome: Optimized "Agent Architect" Profile & Mock Technical Interviews with Senior Architects. |
Choose the track that aligns with your professional trajectory—from strategic pivots to elite architectural tenure.
From $10,000
Monthly financing options coming soon*Financing via Climb Credit/Meritize (US) or StepEx (UK)coming soon
*Subject to credit approval and terms.
