NEWS > March 2026
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Telerik: 10+ Learning Resources to Kick-Start Your AI Journey March 19, 2026 -Telerik: Getting started with AI doesn’t require a PhD, but it does require the right mix of fundamentals, intuition and practical exposure. The following resources strike that balance, giving developers a clear path from curiosity to capability. 1. NVIDIA AI Learning Essentials https://www.nvidia.com/en-us/learn/ai-learning-essentials/ NVIDIA delivers a structured, developer-friendly introduction to AI, covering everything from machine learning basics to deep learning workflows. As powerful as it is convenient, this resource provides a guided path that keeps concepts grounded in real-world application. 2. Anthropic Learn AI https://www.anthropic.com/learn Anthropic focuses on modern AI systems, including large language models (LLMs) and responsible AI practices. The material is concise, current and aligned with how AI is evolving today. This is where foundational concepts meet real-world relevance. 3. Andrej Karpathy’s AI Resources https://karpathy.ai/ Karpathy’s work stands out for its ability to connect theory with implementation. Neural networks, training loops and model behavior are explained in a way that resonates with engineers. This is where developers move beyond using AI and begin to understand it. 4. 3Blue1Brown (YouTube) https://www.youtube.com/@3blue1brown 3Blue1Brown transforms complex math into visual intuition. Topics like neural networks and gradients become approachable through clear, animated explanations. With this level of clarity, abstract concepts start to feel practical. 5. IBM Technology (YouTube) https://www.youtube.com/@IBMTechnology IBM’s channel bridges the gap between theory and enterprise use. It covers AI concepts, tooling and infrastructure with a focus on real-world adoption. This is where AI is placed into the context of systems developers already understand. 6. Everyday AI (YouTube) https://www.youtube.com/@EverydayAI_ Everyday AI emphasizes applied workflows and tools. It highlights how AI is used in day-to-day scenarios, making it easier to translate knowledge into action. The key takeaway is simple: knowing how to use AI is just as important as knowing how it works. 7. Burke Holland (YouTube) https://www.youtube.com/@BurkeHolland/featured Burke Holland’s content brings a developer-first perspective to modern tooling, including AI-powered workflows. The focus is on practical productivity, integrating AI into real development environments and making sense of rapidly evolving tools. This is where AI meets day-to-day developer experience, with an emphasis on getting real work done. 8. Dometrain AI Courses https://dometrain.com/courses/?filters=ai Dometrain offers in-depth, developer-focused courses that emphasize hands-on learning. The AI catalog includes practical training on building, integrating and deploying AI-powered applications. The key to its success is its focus on real implementation. Developers are not just learning concepts, they are building solutions. 9. Telerik AI Blog https://www.telerik.com/blogs/artificial-intelligence The Progress Telerik AI blog provides developer-focused insights into how AI is being applied in modern applications. Topics range from integrating AI into UI workflows to exploring new tooling and frameworks. This is where AI concepts are translated into practical guidance for building real-world applications. 10. Progress Data & AI Blog https://www.progress.com/blogs/data-and-ai The Progress Data & AI blog expands on broader data and AI topics, offering insights into trends, architecture and implementation strategies. It connects AI with the larger data ecosystem, highlighting how systems, pipelines and applications come together. With this perspective, AI becomes part of a bigger picture, one that developers can design, build and scale. 11. Microsoft Reactor https://developer.microsoft.com/en-us/reactor/ Microsoft Reactor offers live and on-demand sessions covering AI, cloud and modern development practices. It brings together experts, community leaders and hands-on demos in an interactive format. This is where learning becomes collaborative. Developers gain not just knowledge, but context from real-world discussions and evolving best practices. 12. Microsoft Learn AI https://learn.microsoft.com/en-us/ai/ Microsoft Learn provides a comprehensive AI learning path with modules, exercises and hands-on labs. It spans fundamentals through advanced topics, often integrated with Azure services. This is where structured learning meets practical implementation at scale. 13. Google AI https://ai.google/ Google AI offers research insights, educational content and real-world applications of AI across products and services. It provides a broader view of how AI is shaping modern technology. This is where innovation and research intersect with real-world impact. 14. AI Explained (YouTube) https://www.youtube.com/@aiexplained-official AI Explained breaks down complex AI topics, trends and news into digestible insights. It is particularly useful for staying current with rapid advancements in the field. This is where awareness of the AI landscape begins to take shape. 15. bycloud (YouTube) https://www.youtube.com/@bycloudAI bycloud focuses on hands-on AI applications, tools and workflows. Content often explores building with modern AI stacks and integrating APIs into real solutions. This is where experimentation turns into working implementations. 16. Theo Browne (YouTube) https://www.youtube.com/@t3dotgg Theo Browne brings a full-stack developer perspective to AI, often exploring how AI fits into modern web development workflows. This is where AI integrates into the tools developers already use daily. 17. Matt Pocock (YouTube & AI Hero) https://www.youtube.com/@mattpocockuk Matt Pocock focuses on developer productivity, TypeScript, and modern tooling, with growing coverage of AI-assisted development. AI Hero complements this with structured learning content. This is where strong developer fundamentals meet AI-enhanced workflows. 18. Sam Witteveen (YouTube) https://www.youtube.com/@samwitteveenai Sam Witteveen provides deep technical explorations of LLMs, agents, and AI architectures. The content often includes hands-on walkthroughs and real implementations. This is where developers dive deep into how modern AI systems are actually built. Final Thoughts AI learning is not a single track. It is a layered experience. Start with structured fundamentals, build intuition through visualization and reinforce everything with practical use. With that approach, AI becomes less about theory and more about capability. And that shift is where real progress begins. 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