Links
Curated links, tools, and resources handpicked by the Blue Note Logic team.
Learning & Courses
Curated courses, tutorials, and educational resources for AI, data engineering, and modern development.
Machine Learning Crash Course - Google
Free, practical introduction to machine learning featuring animated videos, interactive visualizations, and hands-on exercises. Recently refreshed with coverage of recent AI advances. Covers linear regression, classification, and working with data.
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Neural Networks and Deep Learning - DeepLearning.AI
Part of DeepLearning.AI Deep Learning Specialization by Andrew Ng, Kian Katanforoosh, and Younes Bensouda Mourri. Rated 4.9/5 with over 123,000 reviews. Covers RNNs, CNNs, supervised learning, and foundational concepts.
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Data Engineering Zoomcamp 2026
Free 9-week intensive program covering production-grade data pipeline development. Curriculum includes Docker, Terraform, BigQuery, dbt, Spark, and Kafka. Active Slack community with thousands of learners. Next cohort starts January 2026.
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Data Engineering Professional Certificate - DeepLearning.AI
Taught by Joe Reis, co-author of Fundamentals of Data Engineering. Covers data engineering lifecycle, building effective pipelines and architecture, and making data useful for business objectives. Hands-on experience with AWS and open-source tools.
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ChatGPT: Build, Integrate & Deploy AI Apps
Comprehensive course covering setting up ChatGPT with Python and deploying serverless functions on Azure. Teaches integration with Power Automate, Teams, Power Apps, and Bubble. Includes real-world projects like MealPlan and Finance assistants. Updated October 2025.
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Build and Execute an Organisational AI Strategy
Comprehensive 5-hour course covering AI governance, business strategy, regulation, and responsible AI implementation. Learn to build sustainable AI capabilities aligned with C-suite priorities and deliver ROI in weeks rather than months.
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AI Strategy Best Practices for 2026: Executive Guide
Practical guide covering five key pillars: governance and risk management, data readiness, high-ROI use case prioritization, operating models, and scale-through-delivery. Learn why strategies fail and how to build sustainable AI capabilities.
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Practical Deep Learning for Coders - fast.ai
Free course designed for people with coding experience. Apply deep learning to practical problems using PyTorch, fastai, and Hugging Face. Covers computer vision, NLP, and model deployment. No special hardware or advanced math required.
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Introduction to Deep Learning & Neural Networks with Keras
IBM course by Alex Aklson covering foundational deep learning concepts, neural networks, and advanced architectures (CNNs, RNNs, transformers) using Keras. Rated 4.7/5 with practical hands-on projects.
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Practical Deep Learning for Coders - Neural Networks
Free course covering neural networks from scratch using PyTorch and fastai. Learn to build and train neural networks for computer vision, NLP, and tabular data. Over 6 million video views with alumni at Google Brain, OpenAI, and Tesla.
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Getting Started with Natural Language Processing - Codecademy
Beginner-friendly course covering text preprocessing, language models, and topic modeling. Includes AI-assisted coding help, quizzes, and certificate of completion. Over 26,000 learners enrolled. Perfect starting point for NLP beginners.
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Data Engineering with AWS - Udacity Nanodegree
39-hour Nanodegree program updated December 2025 covering data modeling, data warehouses, data lakes, and pipeline automation. Includes 4 courses, 22 lessons, and 4 projects. Intermediate Python, SQL, and database knowledge required.
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Deploy AI Apps with Cloudflare
Intermediate course covering integrating OpenAI with Cloudflare Workers and deploying on Cloudflare Pages. Includes API management, error handling, and domain configuration. Rated 4.9/5 with 18+ reviews. Requires JavaScript basics.
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Integrate AI into Azure App Service Applications
Microsoft Learn guide for building AI-powered applications across multiple programming languages. Covers Azure OpenAI integration, local language models, and retrieval augmented generation (RAG). Emphasizes enterprise security and GitHub integration.
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