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AI Deep Learning Program
The AI Deep Learning Program is a 12-week itinerary split across 6 half-day workshops. Move your team from Stage 2 to Stage 4 on the Improving AI Adoption Model — crossing the Autonomy Inflection Point from permission-based AI usage to autonomous workflow integration with embedded coaching.
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AI Deep Learning Program Full Description
Two Phases, Measured Maturity Growth
12-Week Program
6 Half-Day Workshops
Maturity Stages 2-4
1:1 Embedded AI Coach
WEEKS 1–6 · SESSIONS 1–3 · STAGE 2 → 3
Foundations: Product, Coding & Testing
Cross the Autonomy Inflection Point. Prompt engineering fundamentals, AI-assisted product elicitation, coding with AI assistants for generation and refactoring, and TDD with AIgenerated assertions. Teams shift from permission-based AI to task-level autonomy.
WEEKS 7–12 · SESSIONS 4–6 · STAGE 3 → 4
Advanced: Product, Coding & Testing
Build cross-system workflow capability. Agentic product workflows with MCP integration, chaining reusable skills and automation pipelines, AI-powered validation including browser testing, IaC automation, and governance agents. Teams operate as reviewers directing AI output.
Delivery Model
Track Lead: Senior trainer-coach who delivers half-day workshops and coordinates execution across your team's learning journey.
Embedded AI Engineer: A dedicated coach working alongside your team daily — building habits, applying concepts in real work, and extracting reusable workflows.
Improving AI Adoption Model
STAGE 2 - PERMISSIONS: Human does the work. AI assists with permission.
ROLE: DOER
STAGE 3 - TASK: Autonomy emerges. AI acts on single tasks independently.
INFLECTION POINT
STAGE 4 - WORKFLOW: AI drafts across systems. Human reviews output.
ROLE: REVIEWER
*WAVE TRANSITION - From Wave 1: Chatbots (permission-based, human does the work) to Wave 2: Insights (autonomy emerges, human reviews output).
Learning Outcomes
Prompt engineering mastery — the foundational skill for every maturity stage
AI assistants integrated into coding, testing, and deployment workflows
Ability to build and chain agents for autonomous task execution (Stage 3)
Cross-system workflow automation with reusable skills (Stage 4)
Governance habits for safe autonomous operations beyond permissions
A 90-day framework to sustain maturity growth toward Stage 5+
*Crossing the Autonomy Inflection Point: At Stage 2, your team uses AI with full permission controls — slow but safe. The jump to Stage 3+ requires turning permissions off, demanding new skills, governance, and trust. Tooling alone yields only 18–25% gains. Without embedded coaching, less than 45% adopt and stall at Stage 2. The DLP builds the habits to cross this threshold safely.