Computer Science and AI Foundations: The Dual-Major Curriculum

Transitioning into tech or understanding artificial intelligence requires more than just learning to code; it demands a solid grasp of core computing principles. This text-based course bridges the gap, offering a structured pathway through the essential concepts of both computer science and modern AI. By reading through this comprehensive curriculum, you will build a strong mental model of how computers process information, how software is structured, and how intelligent systems learn from data. You will move from a curious beginner to someone who can confidently discuss algorithms, system architecture, and machine learning workflows. What you'll learn: - Understand foundational computer science concepts, including data structures, algorithms, and operating system basics. - Explore core mathematics for AI, focusing on the essential linear algebra and probability used in machine learning. - Master modern Python programming practices, including type hints, virtual environments, and clean code principles. - Apply machine learning workflows, from data preprocessing to training neural networks and evaluating model performance. - Learn modern AI concepts, including vector databases, large language model basics, and prompt engineering fundamentals. - Analyze how software systems scale, covering basic database design, APIs, and cloud deployment principles. The course starts with key terminology, basic computing hardware concepts, and foundational programming definitions before guiding you through algorithms, data structures, and practical machine learning applications. You will learn by reading clear explanations and studying step-by-step code examples. This course is designed for complete beginners, self-taught programmers, and professionals looking to gain a comprehensive dual-major style understanding of CS and AI without any prior academic background in tech. Start your journey into the core of computing and artificial intelligence today.