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CAIO Course: Chief AI Officer, AI Strategy, LLM, 390+ Tools

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Lead AI at C-level: use case portfolio, data readiness, MLOps, governance, EU AI Act, upskilling, team management
4.2
4.2/5
(2) Ratings
554 students
Created by PapaHR ★ 180K students: Human Resources, HR Management, SHRM, AI Analytics, Recruitment, Payroll, Certification, CIPD, Claude
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What you'll learn

  • Take away 390+ tools: question lists, templates, checklists, procedures, matrices and AI prompts, plus 7 downloadable workbooks
  • Tie AI to business strategy with AI strategy preparation questions, an AI suitability checklist and an AI strategy workbook
  • Prioritize the portfolio with an AI initiative prioritization score, an impact-feasibility matrix and a scale-or-close checklist
  • Assess data and architecture with a data readiness audit procedure, a readiness scorecard and a build, buy or hybrid decision matrix
  • Avoid vendor traps with an AI vendor lock-in prevention checklist and an AI vendor evaluation prompt
  • Lead the transformation with an AI literacy program matrix, an AI resistance reduction procedure and an AI culture roadmap
  • Govern AI with an AI governance checklist, an AI risk register workbook, the EU AI Act risk classification and the NIST framework
  • Prove value with an AI ROI calculator workbook, a CAIO KPI dashboard workbook and a CAIO board report
  • Hire, pay, motivate and keep people in AI teams, and run one-on-ones, OKR reviews and conflict talks
  • Learn with Mike, the #1 HR instructor on Udemy: 1,800,000+ enrollments, 170,000 students, about 200 books on Amazon
This course includes:
28.5 total hours on-demand video
1 articles
61 downloadable resources
55 lessons
Full lifetime access
Access on mobile and TV
Certificate of completion
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Course content

Requirements

  • Management experience is helpful: the course is for people who lead AI initiatives or prepare for it
  • No programming or data science background required: architecture is explained at the level of decisions
  • A spreadsheet program such as Excel or Google Sheets for the workbooks
  • Nothing else to buy for the course itself: 7 workbooks and the presentations are attached to the lectures

Description

This course contains the use of artificial intelligence.

397 tools for a chief AI officer in one course: 239 ready-to-use question lists, templates, checklists, procedures, matrices and AI prompts, 127 models and methods, 24 services and apps shown on screen, and 7 downloadable workbooks.

Open a lecture, take the tool, use it in your AI programme.

Why AI programmes stall

A company runs twenty pilots and none of them reaches production. Each team buys its own tool. The data is not ready, and nobody checked before the launch. Legal learns about a new model from the news. The board asks what all of this returned, and there is no number. A chief AI officer is appointed to turn scattered experiments into a portfolio with owners, risks and results.

What changes after this course

AI initiatives come from business goals and not from tools. The portfolio has a score for each project and a rule for stopping. You know the state of your data before you promise a result. Build, buy or partner is a decision made by a matrix. People are trained by level, and resistance has a plan. Risks are in a register and mapped to regulation. And the board gets a report with value and cost.

What is inside: 397 tools, counted lecture by lecture

You do not have to take this number on trust. Open any lecture and read its description: every tool inside is listed there by name.

  • 239 ready-to-use tools inside the presentations:
  • 60 question lists and scripts: AI strategy preparation questions, CAIO stakeholder communication scripts, one-on-one planning questions, exit interview questions
  • 42 templates and sample documents: AI strategy presentation outline, AI culture roadmap, CAIO board report, CAIO first-year roadmap
  • 40 checklists: AI suitability, AI product readiness, AI vendor lock-in prevention, AI governance
  • 39 step-by-step procedures and workflows: data readiness audit, AI literacy program launch, AI resistance reduction, data-first AI implementation
  • 33 scorecards, rubrics and matrices: build-buy-partner decision matrix, impact-feasibility matrix, AI technology risk matrix, AI workforce role transformation matrix
  • 9 ready AI prompts: data readiness assessment, AI vendor evaluation, AI risk assessment, AI governance policy
  • 9 formulas and metric sets: AI ROI calculation, AI ROI metrics, CAIO KPIs, AI literacy metrics
  • 7 other working tools: personal histories team exercise, team effectiveness feedback exercise, remote work competency interview scorecard
  • 127 models and methods explained with examples: MLOps lifecycle, AI technology stack, AI agent maturity model, EU AI Act risk classification, NIST AI Risk Management Framework, responsible AI principles
  • 24 services and apps shown on screen, from a quick look to a detailed demo: Jira, Trello, Asana, Miro, Notion, Slack, Zapier and others
  • 7 downloadable workbooks: AI strategy, AI workforce transformation assessment, AI culture roadmap, AI team planner, AI risk register, AI ROI calculator and CAIO KPI dashboard

Where the tools are

  • The chief AI officer role and AI leadership (6 sections, 83 tools). Role and KPIs, AI strategy, product portfolio, architecture and data strategy, transformation and culture, governance, ethics and ROI. All 7 workbooks are here.
  • People management skills for chief AI officers (316 tools, 48 lectures). Most of the tools are here: hiring, onboarding, team development, leadership styles, pay and bonuses, motivation, retention, talent, goals, performance, one-on-one meetings, coaching, meetings, change, business models, conflict, negotiation and remote teams.

What this course is not

It is not a certification programme and it does not teach machine learning engineering. It is a toolkit for the person who leads AI in a company.

Who is teaching

I am Mike, the #1 HR instructor on Udemy, with 1,800,000+ course enrollments from 170,000 students, and the author of about 200 books on Amazon. I built the people system at Preply as it became a unicorn and worked at Wargaming, iDeals and Alfa-Bank across 20 years in HR. I hold PHRi, SHRM-CP and HCI sHRBP certifications and represent HRCI in Eastern Europe. I am also a founder and lead the strategy of my own academy.

I am not an engineer. I lead AI adoption in my own business and use these tools every day. I started with ChatGPT on the day it became publicly available. When I exported my history, there were 5,000 dialogues, and that is ChatGPT alone, next to Gemini, Midjourney, Perplexity and others. I also count what it returns. I once had to update the page markup for our courses in three languages, about 390 pages. By hand it took about 10 minutes a page. I taught the assistant to do it from my template, and a page took a minute. On that task alone I saved about 50 hours. A chief AI officer does the same at the scale of a company: chooses where AI pays back and proves it with a number.

How to use the course

Watch the first six sections in order: they follow the first year of a chief AI officer from the role to the board report. Then use the people management section as a reference and open the lecture you need. Section and lecture titles show how many tools are inside, and each lecture description lists them by name.

What is included

  • 55 lectures across 8 sections, 28.5 hours
  • 61 downloadable resources: 7 workbooks and the lecture presentations
  • 397 tools across the lessons, ready to copy into your own work
  • A 9-question practice test, a quiz and a role play
  • Lifetime access to all materials
  • Active instructor support in the Q&A section
  • A Udemy Certificate of Completion

Where to start

Take the AI initiatives your company runs now. Open the lecture on the product portfolio and give each one an AI initiative prioritization score. Enrol now and start your first lesson today.

Who this course is for:

  • New chief AI officers and heads of AI in their first year
  • CTOs, CIOs, CDOs and COOs who had AI added to their responsibilities
  • Leaders of AI and data teams who are growing into a C-level role
  • Founders and CEOs who lead AI adoption themselves or are hiring a CAIO
  • Transformation and strategy leaders who prepare the AI case for the board
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