01Computational Thinking - Module OverviewMaster computational thinking before mastering Python. This module teaches how computers reason, how memory works, how programs execute, and how to think algorithmically - the engineering foundation that makes everything else possible.02Compilation vs Interpretation - How Python Actually Runs Your CodeUnderstand Python's hybrid execution model - source code, bytecode, the Python Virtual Machine, CPython internals, JIT compilation, and why this architecture matters for performance and system design.03↳ Practice: Compilation vs InterpretationSolve 12 Python compilation vs interpretation problems. Covers compilation practice, bytecode exercises, dis module. Hints and solutions.04Variables in Memory — Stack, Heap, and Python's Object ModelA deep engineering dive into how Python stores variables in memory — stack frames vs heap objects, reference counting, garbage collection, pointer arithmetic, and the complete object model that governs Python's behavior.05↳ Practice: Variables in MemorySolve 12 Python variables in memory problems. Covers variables practice, memory model, is vs, mutable vs. Hints and solutions.06Binary, Bits, and Bytes - How Computers Store EverythingDeep engineering dive into binary representation, bits, bytes, two's complement, IEEE 754 floating point, text encoding, and Python's arbitrary-precision integers - with real code and AI/ML connections.07↳ Practice: Binary, Bits, and BytesSolve 12 Python binary, bits, and bytes problems. Covers binary practice, bitwise operators, two's complement. Hints and solutions.08Data Types at the Hardware Level - What Python Hides From YouUnderstand how integers, floats, booleans, and characters are represented in hardware, how Python's type system differs from C, and how libraries like NumPy bridge the gap for performance.09↳ Practice: Data Types at Hardware LevelSolve 12 Python data types at the hardware level problems. Covers data types, numpy dtypes, hardware types. Hints and solutions.10Pseudocode - Design Before You CodeLearn to design algorithms using pseudocode before writing Python. Build structured thinking that prevents logic errors, guides clean implementation, and scales to complex real-world systems.11↳ Practice: Pseudocode WritingSolve 10 Python pseudocode writing problems. Covers pseudocode practice, algorithm design, pseudocode to. Hints and solutions.12Flowcharts - Seeing Logic Before Writing ItLearn to design algorithms visually using flowcharts. Model control flow, decision branches, and system behavior before touching code - and translate diagrams directly into clean Python.13↳ Practice: FlowchartsSolve 10 Python flowcharts coding problems (3 Easy, 4 Medium, 3 Hard). Covers flowchart practice, flowchart to, control flow. Full hints and solutions included.14Big-O Notation - How Your Code Behaves at ScaleBuild deep intuition for algorithmic complexity. Understand O(1), O(n), O(n²), O(log n), and O(2^n) through real Python examples, visualizations, and production engineering scenarios.15↳ Practice: Big-O NotationSolve 12 Python big-o notation problems. Covers big o, algorithm complexity, time complexity. Hints and solutions.16Projects8 lessons8 lessons
