Learning Pathways
Guided Learning Paths
Structured pathways to master AI and prompt engineering
3
Learning Pathways
13
Total Steps
Free
All Pathways
AI Strategy for Leaders
A guided pathway for engineering managers and directors to develop a robust AI strategy for their teams.
5 Steps
1
Understand the Landscape
Start by reading a key article on how AI is impacting engineering leadership to understand the challenges and opportunities.
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2
Define Your AI Policy
Before you can adopt AI, you need a clear and safe policy. Browse our prompt library to find templates for AI usage policies.
playbook
3
Set Measurable Goals
A great strategy needs measurable goals. Use the 'Goal & OKR Architect' to define clear objectives for your team's AI adoption this quarter.
workbench
4
Learn from the Best
Read how we shipped a production platform in one day using strategic iteration.
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5
Tackle Strategic Problems
Now, apply your strategic thinking. Use the 'Technical Debt Strategist' to build a business case for a real-world problem.
workbench
Foundational AI & Cloud Certifications
A curated list of cost-effective, industry-recognized courses to build a strong foundation in AI and cloud engineering.
4 Steps
1
Google AI Essentials
Taught by Google AI experts on Coursera, this course provides a solid, non-technical introduction to AI and machine learning concepts. It's the perfect starting point for understanding Google's ecosystem.
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2
AI for Everyone by DeepLearning.AI
Created by Andrew Ng, this is a classic, highly-regarded course that explains AI from a strategic, business-oriented perspective. Essential for leaders, PMs, and any engineer who wants to understand the 'why' behind AI.
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3
AWS Certified Cloud Practitioner
A foundational understanding of cloud computing is essential for working with AI at scale. This certification from AWS provides a comprehensive overview of cloud concepts, services, and security. Similar certifications are available for GCP and Azure.
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4
Microsoft Azure AI Fundamentals
This certification is a great entry point into Microsoft's AI ecosystem. It covers fundamental concepts of machine learning and AI workloads on Azure, making it a valuable credential in a multi-cloud world.
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Prompt Engineering Basics
Learn the fundamental techniques of writing effective prompts to get better results from any AI model.
4 Steps
1
Understand the Model Landscape
Start by reading Ethan Mollick's guide to understand when to use free vs. advanced models. This context is crucial before writing any prompt.
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2
Learn a Structured Framework
A great prompt has a clear structure. Use the C.R.A.F.T.E.D. framework to learn how to provide clear context, roles, and actions to the AI.
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3
Master Key Prompting Strategies
Explore powerful techniques like the two-step 'Plan + Execute' method and giving the AI a persona to dramatically improve output quality.
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4
Apply Your Skills in the Lab
Go to the Prompt Lab in the Workbench. Try using the C.R.A.F.T.E.D. framework and the two-step method to write a prompt for a task you do every day.
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Ready to start learning?
Pick a pathway above and begin your journey to AI mastery