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AI-Learning-Roadmap.excalidraw
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Text Elements
Practical use of AI
Prompt Engineering
Practical use of AI tools
Workflow automation & AI integration
Python
Data & Ml
Governance, Risk and Decision Frameworks
Architecture Literacy
Core ML concepts
Model evaluation
Overfitting, bias and vairance
Fine tuning vs prompting
How LLMs are trained
Inference and optimisation
Multimodal models
Data pipelines
Storage architecture
Data quality and lineage
RAG
Agentic systems
Evaluation architecture
Cloud infrastructure concepts
Containerisation and orchestration concepts
Security for AI systems
Observability
Regulatory Landscape
Model risk management
AI governance frameworks
Technical standards
Bias in AI systems
Fairness, accountability, transparency
AI safety concepts
AI investement sequencing
Total cost of ownership
AI readiness assessment
Use case prioritisation
Reading and writing ADRs
C4 model diagrams
Human in the loop design
AI Literacy
What AI Is (and isn’t) 🔗
LLMs fundamentals
Key terminology
Models - Frontier vs Open Source (Open Weight)
AI tooling (landscape)
End-User AI tools (landscape)
Use case identification
ROI & business case
AI strategy fundametnals
Build vs buy vs prompt
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Element Links
M8pGgQdz: Choosing the right LLM
Link to original
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