Module 3 - Lesson 4: The AI Technology Stack
The AI technology stack encompasses data processing, storage options, development platforms, deployment solutions, and monitoring tools.
Daz Williams
Module 3 - Lesson 3: Technical Infrastructure for AI
AI implementation requires careful consideration of computing resources, infrastructure decisions (cloud vs. on-premises), system integration, and build vs. buy options.
Module 3 - Lesson 2: Building Your Data Foundation
A robust data foundation requires thoughtful strategy, governance frameworks, efficient collection and storage infrastructure, and rigorous quality management.
Module 3 - Lesson 1: Assessing Your AI Readiness Introduction
Assess your organization's AI readiness through technical evaluation, data infrastructure, skills analysis, and organizational factors using a comprehensive assessment tool.
Module 3 - Overview
This module helps you assess and build the technical and organizational foundations needed for successful AI implementation.
Module 2 - Resources
AI Value Assessment Framework, Business Case Template, Implementation Roadmap, and Pilot Project Metrics Guide comprise essential resources for successful AI initiatives.
Module 2 - Conclusion
AI implementation, emphasizing business-driven approaches, structured frameworks, comprehensive business cases, phased implementation, effective pilots, and strategic alignment with organizational goals.
Module 2 - Lesson 5: Aligning AI with Business Strategy
AI initiatives must align with business goals, receive executive support, involve cross-functional teams, and be future-proofed to create competitive advantage.
Module 2 - Lesson 4: Pilot Projects and Proof of Concept
Initiatives involve designing effective AI trials, setting appropriate scope and expectations, measuring success metrics, and developing strategies for scaling successful pilots to production.
Module 2 - Lesson 3: AI Implementation Roadmapping
AI Implementation Roadmapping, including planning timeframes, resource allocation, phased deployment approaches, defining success metrics, and practical roadmap development exercises.
Module 2 - Lesson 2: Building the Business Case for AI
A comprehensive framework for building an AI business case includes ROI calculation, cost-benefit analysis, risk assessment, stakeholder presentation techniques, and a templated approach for justifying AI initiatives.
Module 2 - Lesson 1: Finding High-Value AI Opportunities
The course explores strategic AI implementation through frameworks for identifying, prioritizing, and mapping high-value opportunities that drive business results.