AI Diploma

Lectures

1. 1Lecture One — Welcome to the AI Era+−

   • What AI is (and is not)
   • Key concepts: data, models, inference
   • AI landscape and use cases

   Lecture 1 PDF

   Foundations of Artificial Intelligence

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2. 2Lecture Two — Understanding Generative AI & How It Works+−

   • Data quality, structure, and governance
   • Data pipelines and preparation
   • Ethics, privacy, and compliance

   Lecture 2 PDF

   Understanding Generative AI & How It Works

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3. 3Lecture Three — Prompt Engineering Mastery+−

   • Supervised vs. unsupervised learning
   • Model training, validation, and metrics
   • Common pitfalls: overfitting and bias

   Lecture 3 PDF

   Prompt Engineering Mastery

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   Prompts Library

   Professional prompts library (Word document)

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4. 4Lecture Four — AI Productivity Toolkit+−

   • Neural network architectures
   • Computer vision and NLP foundations
   • When deep learning is the right tool

   Lecture 4 PDF

   AI Productivity Toolkit

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5. 5Lecture Five — Mastering AI Tools+−

   • How LLMs work
   • Prompt engineering and retrieval augmentation
   • Enterprise adoption patterns

   Lecture 5 PDF

   Mastering AI Tools

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6. 6Lecture Six — AI in Business & Professional Workflows+−

   • Building an AI strategy and roadmap
   • Governance frameworks and risk controls
   • Responsible AI in the public sector

   Lecture 6 PDF

   AI in Business & Professional Workflows

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   Weekly AI Practical Exercise

   Weekly practical exercise for Lecture 6 (PDF)

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7. 7Lecture Seven — Responsible AI & AI Governance+−

   • Digital Twin concepts and architecture
   • Predictive maintenance and asset optimization
   • Decision-support systems for smart cities

   Lecture 7 PDF

   Responsible AI & AI Governance

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8. 8Lecture Eight — Final Capstone Project & Presentations+−

   • Selecting and scoping a high-value use case
   • Business case, KPIs, and value tracking
   • Capstone presentation and assessment