Channel Partner Program
AI Cybersecurity Advanced Courses for Corporates
Partner with us to deliver advanced AI cybersecurity courses to your customers. Built for enterprise rollouts with live labs, instructor enablement, and optional credential pathways.
What’s inside
- Sequenced advanced course tracks mapped to customer maturity milestones
- Optional assessments and credentials for customers who request them
- Instructor feedback, project reviews, and partner-ready delivery playbooks
Delivery Highlights
- Zero install browser labs aligned to each stage
- Dedicated learning advisors + customizable pacing
- Integration with your LMS, SSO, and talent frameworks
Building Secure AI Applications
Secure design, implementation, and hardening for AI products
Build secure AI systems from day one. This certification focuses on secure architecture, agent and API hardening, and operational controls for production grade AI applications.
Ideal for
- Application security engineers supporting AI initiatives
- Platform teams building production LLM features
- Tech leads responsible for secure AI delivery
Optional Credential Path
ProctorWell assessments certify graduates as "ElephantScale Certified AI Security Engineer" with verifiable completion credentials.
Establish secure AI design principles and defensive coding standards.
Hands on labs focus on input validation, model boundary checks, and abuse prevention.
Threat modeling, secure defaults, and zero trust foundations
Model telemetry, data risk signals, and response playbooks
Harden AI services, identity boundaries, and secret distribution.
Design vault backed controls and enforce policy at service and tool layers.
OWASP labs, OAuth secured APIs, and code signing safeguards
Dynamic secrets, namespaces, and service mesh segmentation
Apply governance and enterprise controls across AI app lifecycles.
Capstone: incident response and governance sign-off for a production AI release.
Security, governance, and observability for autonomous agents
Malware triage and AI supply chain forensics
Practical AI Security for Security Teams
Runbook driven defense for SOC, AppSec, and platform security teams
Train security teams to secure and operate AI systems in real environments. This practical track emphasizes controls, detection engineering, red-team simulation, and response readiness for AI workloads.
Ideal for
- SOC and detection engineering teams
- Security operations leaders modernizing for AI risk
- Governance and risk teams supporting AI adoption
Optional Credential Path
ProctorWell assessments certify graduates as "ElephantScale Certified Practical AI Security Specialist" with verification ready credentialing.
Establish AI risk posture and baseline controls.
Labs cover AI threat taxonomy, control mapping, and baseline monitoring.
Threat indicators, drift risk, and alert quality tuning
Defensive coding and validation patterns for AI-powered apps
Deploy practical controls for identity, secrets, and service boundaries.
Hands on hardening with policy enforcement and blast-radius reduction.
Dynamic secrets, access boundaries, and service segmentation
API hardening and secure implementation patterns
Exercise enterprise readiness for AI security incidents.
Capstone includes breach simulation, response leadership, and recovery playbooks.
Forensics workflow and malware triage under incident pressure
Governance and controls for enterprise AI deployments
Agentic AI Builder
Design, orchestrate, and scale next generation AI agents
Guide teams from first agent build to enterprise scale orchestration. This enterprise course track covers LangChain, CrewAI, LangGraph, and large scale governance so you can ship reliable autonomous systems.
Ideal for
- AI engineers moving from prompt ops to agent ops
- Solution architects supporting agentic products
- Technical program managers driving automation initiatives
Optional Credential Path
Graduates receive a ProctorWell issued completion report with verification and LinkedIn sharing. Optional assessment-based credential is available on request.
Learn AI-agent fundamentals, reasoning loops, and tool integration.
Labs include building a research assistant with LangChain + function calling.
Agent basics, memory types, and evaluation strategies
LangChain tooling, prompt engineering, and error recovery
Scale to multi agent orchestration and stateful workflows.
Pair programming labs with CrewAI and LangGraph sandboxes.
Delegation, messaging, and supervisor agents
Role design, task queues, and tool integrations
Stateful graphs, branching logic, and HITL checkpoints
Engineer production ready autonomous agents with governance.
Capstone: deploy a monitored agent fleet assessed through ProctorWell.
Security, scalability, and compliance frameworks
Self-improvement loops, guardrails, and oversight
Retrieval orchestration and corrective reasoning