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Published 8/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 11h 54m | Size: 3.86 GB
AI Foundations: Core theories and paradigms for developers to build intelligent systems.
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 11h 54m | Size: 3.86 GB
AI Foundations: Core theories and paradigms for developers to build intelligent systems.
What you'll learn
Software Developers and Engineers who want to understand the impact of AI without diving into code or complex math.
Beginners to AI who are curious about how it works and how it's shaping the future of software development.
Technical Professionals (DevOps, QA, SRE, Product Engineers) looking to build AI awareness and future-proof their careers.
Students and Early-Career Technologists who want a clear, structured, and conceptual starting point for their AI journey.
Developers exploring roles like AI Integrator or AI Product Engineer, who need a foundational understanding before learning tools or frameworks.
Requirements
No prior AI or Machine Learning experience is required.
No coding or math skills needed-this course is 100% theoretical and concept-focused.
A basic understanding of software development concepts (e.g., what APIs, IDEs, and code are) will help you relate to examples, but is not mandatory.
Curiosity, a learner's mindset, and a desire to stay relevant in the evolving tech landscape are the most important prerequisites.
Description
Disclaimer (Read This First!):This is not an AI coding bootcamp. You won't find model training, toolkits, or implementation walk-throughs here. Instead, this course is your first and most crucial step toward becoming AI-aware. It's designed for developers who want to understand how AI actually works-conceptually, architecturally, and philosophically-before diving into hands-on tools. If you're looking to demystify AI, build mental models, and gain clarity in a fast-evolving field without jumping straight into code, this course is for you. You won't become an AI expert here-but you'll gain something arguably more important: the awareness and foundation needed to grow into one.Full Course Description:The landscape of software development has dramatically shifted. Ten years ago, developer expectations were different; today, the advent of AI demands that you operate "two levels up" in your understanding of systems, data flow, and problem-solving. This course directly addresses that raised bar, providing the crucial conceptual foundation you need. AI acts as a powerful multiplier: without a fundamental understanding, your "AI multiplier factor" risks remaining at zero, potentially leaving you outpaced. This course ensures you gain that vital conceptual "multiplier factor of one," keeping you highly relevant and competitive.This course equips you with the comprehensive conceptual knowledge to not just keep pace, but to truly thrive in this evolving landscape. You'll explore what AI is, its rich historical journey, and the powerful drivers behind its current boom, understanding its indispensable role in shaping today's developer workflows. Dive into Core AI & Machine Learning Concepts, from understanding data lifecycles, features, and the various ML paradigms (Supervised, Unsupervised, Reinforcement Learning) to grasping the essence of neural networks, embeddings, and essential model evaluation.Master Large Language Models (LLMs) & Generative AI Fundamentals, learning their conceptual architecture, how to control their output with prompt engineering, understanding their inherent limitations, and distinguishing key adaptation methods like fine-tuning versus Retrieval-Augmented Generation (RAG).Discover how AI conceptually augments developer productivity, leveraging tools like GitHub Copilot, AI-native IDEs, and AI for enhanced testing, documentation, code review, and security. Learn to build with AI APIs, integrating smart features and implementing semantic search. We'll also introduce the emerging world of Agentic AI and delve into AI infrastructure concepts, LLMOps, and critical security, privacy, and ethical best practices for responsible AI development.The course concludes by examining your evolving role in the AI era, identifying crucial "AI-resistant" skills, and strategizing for continuous learning and adaptation. This course provides the robust conceptual bedrock for developers to confidently navigate, innovate, and lead in the AI-driven future of software.
Who this course is for
Software developers who want to build a strong conceptual understanding of AI without jumping into code or math.
Beginner learners in AI who feel overwhelmed by technical jargon and want a structured, theory-first foundation.
Developers in any role-frontend, backend, DevOps, QA, mobile-looking to stay relevant as AI transforms the industry.
Students, recent graduates, and early-career technologists exploring how AI impacts software careers and workflows.
Professionals transitioning into AI-adjacent roles like AI Product Manager, AI Architect, or Prompt Engineer.
Anyone curious about AI's real-world impact on development tools, workflows, and career trajectories-without needing to code.
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