Kotlin from Scratch (Faisal Islam) (z-library.sk, 1lib.sk, z-lib.sk)

【One-Line Pitch】 A project-driven introduction to Kotlin that uses 37 small apps—charts, simulations, fractals, and nature-inspired optimizers—to teach both the language and computational problem-solving. Best for motivated beginners and programmers from other languages who want hands-on practice rather than a reference manual. 【Book Arc】 - **Opening (~0%–10%)**: Sets up the premise—Kotlin as a concise, general-purpose language—and orients you to tools, workflow, and the book’s four-part structure; solves the “where do I start?” problem. - **Early (~10%–30%)**: Covers Kotlin fundamentals (variables, control flow, functions, lambdas, I/O, classes) and introduces JavaFX for charts, canvas drawing, and animation; solves the “how do I write and visualize Kotlin code?” problem. - **Middle (~30%–55%)**: Applies the language to math and science projects—root-finding, primes, Fibonacci, encryption, random walks, projectile motion, pendulums, cooling, and binary stars; solves the “how do I model real problems in code?” problem. - **Late (~55%–75%)**: Moves into recursion and fractals (Sierpiński triangle, fractal tree, L-systems, Mandelbrot) plus classic sorting and graph search (insertion/merge/quick sort, DFS, BFS, A*); solves the “how do I handle recursive and algorithmic thinking?” problem. - **Ending (~75%–100%)**: Introduces stochastic, nature-inspired optimization—genetic algorithms and ant colony systems—culminating in the Berlin52 traveling salesman problem; solves the “how do I tackle hard optimization problems?” problem. 【Key Takeaways】 - **Learning is project-first, not reference-first** (Early): Each concept is introduced through a concrete app, so you build intuition by doing rather than memorizing syntax. - **Kotlin is treated as a general-purpose language** (Early): The book deliberately steps outside Android to show Kotlin for console apps, data visualization, and scientific computing. - **JavaFX is the visualization backbone** (Early): Charts, canvas drawing, and animation are used repeatedly, making graphics a practical way to see your code’s output. - **Mathematical modeling is a core skill** (Middle): Projects translate physical and mathematical problems into simplified models before coding, emphasizing strategy over brute force. - **Recursion is taught through fractals** (Late): Self-similar patterns and L-systems make recursive functions and stopping conditions tangible. - **Classic algorithms are implemented, not just described** (Late): Sorting and graph search are coded and compared, with big O notation used to discuss time and space complexity. - **Nature-inspired algorithms are presented as practical tools** (Ending): Genetic algorithms and ant colony optimization are framed as options for intractable or complex optimization problems. - **The book is explicit about its scope** (Middle): It is not a comprehensive Kotlin reference and does not cover generics, coroutines, Android development, or advanced data structures. 【Reading Tips】 - Read Part I sequentially; the later projects assume fluency with Kotlin basics and JavaFX setup. - Type and run the projects rather than skimming code listings—the book’s value is in the build-and-debug loop. - Treat the math/science chapters as strategy lessons: pause to understand the model before reading the implementation. - Skim the algorithm-comparison sections if you already know sorting and search; focus instead on the Kotlin implementations and complexity discussion. - Use the appendix for environment setup and key definitions if you are new to IDEs, JDKs, or compiling and running programs. 【Coverage Limits】 The excerpts cover the book’s structure, project list, and stated scope well, but do not include detailed code, exercise content, or chapter-level explanations, so this guide cannot assess depth or difficulty of individual projects.