Courses & Learning Resources¶
Learning resources for building AI-first companies -- from technical foundations to business strategy. Organized by format to support the 90-Day AI Fluency Program.
Online Courses¶
Technical Foundations¶
| Course | Provider | Description |
|---|---|---|
| AI for Everyone | deeplearning.ai (Coursera) | Andrew Ng's non-technical introduction to AI strategy, workflow, and organizational impact. Good starting point for Phase 1 of the 90-Day program. |
| Deep Learning Specialization | deeplearning.ai (Coursera) | Five-course sequence covering neural networks, optimization, CNNs, sequence models, and attention mechanisms. |
| Machine Learning Specialization | Stanford / deeplearning.ai (Coursera) | Updated foundational ML course covering supervised learning, recommender systems, and reinforcement learning. |
| Practical Deep Learning for Coders | fast.ai | Top-down, code-first approach to deep learning. Free. Emphasizes practical application over theory. |
| Generative AI with Large Language Models | deeplearning.ai / AWS (Coursera) | Covers LLM lifecycle -- training, fine-tuning, deployment, and evaluation. Relevant to the Build path in the Build vs Buy Calculus. |
| LangChain for LLM Application Development | deeplearning.ai | Short course on building LLM applications with LangChain -- chains, agents, and memory. |
AI in Business¶
| Course | Provider | Description |
|---|---|---|
| AI Product Management Specialization | Duke University (Coursera) | Managing AI products, evaluating ML solutions, and building human-centered AI. |
| AI for Business | Wharton (Coursera) | AI fundamentals for business leaders: strategy, analytics, and workforce implications. |
| Prompt Engineering for Developers | deeplearning.ai | Techniques for effective prompting. Complements the 8 Patterns for AI Coding framework. |
| Building AI-Powered Apps | Replit | Hands-on course for building applications with AI coding assistants. |
Books¶
Recommended reading that complements the topics covered in Blueprint for an AI-First Company.
AI Strategy & Business¶
| Book | Author(s) | Why It Complements |
|---|---|---|
| Co-Intelligence: Living and Working with AI | Ethan Mollick | Practical frameworks for human-AI collaboration. Complements Chapter 2's Human-AI Collaboration framework. |
| Prediction Machines | Ajay Agrawal, Joshua Gans, Avi Goldfarb | Economic framework for understanding AI as a prediction technology. Complements the data strategy chapters. |
| The AI Organization | David De Cremer | Leadership and organizational design for AI-driven companies. Complements Chapter 8 (Teams). |
| Power and Prediction | Ajay Agrawal, Joshua Gans, Avi Goldfarb | Follow-up to Prediction Machines focused on AI-driven decision-making and system-level change. |
| Competing in the Age of AI | Marco Iansiti, Karim R. Lakhani | How AI transforms operating models and competitive dynamics. Harvard Business School research. |
Technical Depth¶
| Book | Author(s) | Why It Complements |
|---|---|---|
| Designing Machine Learning Systems | Chip Huyen | Production ML systems design -- data engineering, model deployment, monitoring. Complements Chapter 4 (Infrastructure). |
| Building LLM Powered Applications | Valentina Alto | End-to-end guide for LLM application development with practical examples. |
| AI Engineering | Chip Huyen | Building applications with foundation models. Covers the full stack from prompting to fine-tuning to deployment. |
Certifications¶
Professional certifications relevant to AI-first company building.
Cloud AI Certifications¶
| Certification | Provider | Focus |
|---|---|---|
| AWS Certified Machine Learning -- Specialty | Amazon Web Services | ML workflows on AWS -- data engineering, modeling, deployment, and operations. |
| Google Cloud Professional Machine Learning Engineer | Google Cloud | Designing, building, and productionizing ML models on GCP. |
| Microsoft Certified: Azure AI Engineer Associate | Microsoft | Designing and implementing AI solutions using Azure Cognitive Services and Azure Machine Learning. |
Responsible AI & Governance¶
| Certification | Provider | Focus |
|---|---|---|
| Certified AI Governance Professional | IAPP (International Association of Privacy Professionals) | AI governance, risk management, and compliance. Relevant to the AI Governance Framework. |
| ISO 42001 Lead Implementer | Various certification bodies | International standard for AI management systems. Referenced in the 7 AI Risks and Mitigations framework. |
| Google Responsible AI Certification | Google Cloud | Principles and practices for developing responsible AI systems. |
Newsletters¶
Regular reading to stay current on AI developments relevant to company building.
| Newsletter | Author / Publisher | Focus |
|---|---|---|
| The Batch | deeplearning.ai / Andrew Ng | Weekly AI news and analysis with business implications. |
| Import AI | Jack Clark (co-founder of Anthropic) | Weekly newsletter on AI research, policy, and industry trends. |
| The Neuron | The Neuron team | Daily AI business news -- product launches, funding, and trends. |
| Stratechery | Ben Thompson | Technology strategy analysis. Frequently covers AI business models, platforms, and competitive dynamics. |
| One Useful Thing | Ethan Mollick | Practical AI applications and research insights for professionals. |
| AI Tidbits | Michael Spencer | AI industry analysis focused on enterprise AI trends and market dynamics. |
Podcasts¶
Audio resources for AI strategy and technical depth.
| Podcast | Host / Publisher | Focus |
|---|---|---|
| Latent Space | Alessio Fanelli & swyx | Technical deep dives on AI engineering, infrastructure, and product development. |
| The AI Podcast | NVIDIA | Interviews with AI researchers and practitioners across industries. |
| Practical AI | Changelog | Practical applications of AI and ML in production systems. |
| No Priors | Sarah Guo & Elad Gil | AI founders and researchers discussing the latest in AI product development and company building. |
| Hard Fork | New York Times (Kevin Roose & Casey Newton) | Technology and AI industry analysis for a general business audience. |
| Cognitive Revolution | Nathan Labenz | In-depth conversations about AI capabilities, safety, and enterprise applications. |
Learning Path Recommendations¶
For the 90-Day AI Fluency Program¶
Aligned with the 90-Day AI Fluency Program phases:
Phase 1 (Days 1-30 -- Foundation): - AI for Everyone course - The Batch and One Useful Thing newsletters - Co-Intelligence book
Phase 2 (Days 31-60 -- Integration): - Prompt Engineering for Developers course - Latent Space and No Priors podcasts - Domain-specific courses from your cloud provider
Phase 3 (Days 61-90 -- Mastery): - LangChain for LLM Application Development course - Designing Machine Learning Systems or AI Engineering book - Cloud AI certification preparation