Clean Code

Learn how to write readable, understandable and therefore maintainable code - step by step, in an example-driven way

Clean Code

Course Overview

About This Course

Your code works—but when you come back a week later (or a teammate opens it), it suddenly feels harder than it should. You’re not alone: “working” code can still be confusing, fragile, and exhausting to change.

In this course, you’ll build a practical sense for what makes code easy for humans to read and maintain. You’ll see common pain points in real code, then fix them through hands-on “bad to good” transformations backed by examples, snippets, and demos.

By the end, you’ll be able to look at a messy piece of code and systematically improve it: make intent obvious, reduce surprises, keep changes local, and leave behind code your future self (and colleagues) can confidently extend.

What You'll Learn

You’ll apply clean-code rules and principles across real code examples (Python, JavaScript, TypeScript) without relying on any single language or paradigm.

  • Name with intent

    Write clear names for variables, properties, classes, and functions, and spot common naming pitfalls. You’ll make code self-explanatory so readers don’t need extra mental decoding.

  • Comment with purpose

    Decide when comments are harmful noise and remove them confidently. When a comment is truly useful, you’ll write the kind that adds value instead of repeating the code.

  • Format for readability

    Use horizontal and vertical formatting to guide the reader’s eye through a file. You’ll structure code so important ideas stand out and related logic stays visually grouped.

  • Design clean functions

    Keep functions focused on one thing, control parameter counts, and use levels of abstraction to split logic into small, readable units. You’ll also write DRY code while avoiding unexpected side effects.

  • Simplify control flow

    Replace deeply nested control structures with guards and extracted functions. You’ll also use errors and error handling as a cleaner alternative to sprawling if-chains.

  • Structure maintainable classes

    Differentiate objects vs data containers/data structures and use cohesion to keep classes small and focused. You’ll apply the Law of Demeter and understand how SOLID supports clean, maintainable code.

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Prerequisites

  • Basic programming knowledge in any language.

  • No prior experience with clean code is required.

  • You don’t need to know a specific programming language or paradigm.

Who Is This Course For?

  • Working developers

    You can ship features, but you’re tired of codebases that become harder to touch over time. This course helps you write code your team can read, trust, and maintain.

  • Early-career programmers

    You’ve learned to make programs run, but you’re unsure what “good code” looks like in real life. You’ll get a clear set of rules and examples you can apply immediately.

  • Serious builders

    You’re not coding just for practice—you want habits that hold up in real projects. This course gives you a practical way to improve code quality without needing a specific language background.

Curriculum Overview

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Preview the structure and pacing of this course before you begin.

  • Getting Started12 lectures30m
    • 01Welcome to the Course!2:27 min
    • 02What is "Clean Code"?5:57 min
    • 03Clean Code - Key Pain Points & How To Write Clean Code3:31 min
    • 04How Is This Course Structured?1:22 min
    • 05Course Prerequisites3:16 min
    • 06Clean Code & Strongly Typed Languages2:31 min
    • 07About The Course Code Examples2:04 min
    • 08Functional, OOP, Procedural: The Course Concepts Always Apply!1:29 min
    • 09Clean Code, Principles & Patterns & Clean Architecture3:17 min
    • 10Clean Code vs Quick Code5:01 min
    • 11Module & Course Resources0:00 min
    • 12The Academind Pro Referral Program0:00 min
  • Naming - Assigning Names to Variables, Functions, Classes & More16 lectures1h 6m
    • 01Module Introduction1:01 min
    • 02Why Good Names Matter3:23 min
    • 03Choosing Good Names4:03 min
    • 04Casing Conventions & Programming Languages3:07 min
    • 05Naming Variables & Properties - Theory3:48 min
    • 06Naming Variables & Properties - Examples4:44 min
    • 07Naming Functions & Methods - Theory2:36 min
    • 08Naming Functions & Methods - Examples3:10 min
    • 09Naming Classes - Theory1:56 min
    • 10Naming Classes - Examples2:34 min
    • 11Exceptions You Should Be Aware Of6:24 min
    • 12Common Errors & Pitfalls7:50 min
    • 13Demo Time!10:29 min
    • 14Your Challenge - Problem1:11 min
    • 15Your Challenge - Solution10:01 min
    • 16Module Resources0:00 min
  • Code Structure, Comments & Formatting10 lectures32m
    • 01Module Introduction1:06 min
    • 02Bad Comments3:52 min
    • 03Good Comments3:50 min
    • 04What is "Code Formatting" Really About?2:26 min
    • 05Vertical Formatting8:03 min
    • 06Formatting: Language-specific Considerations2:03 min
    • 07Horizontal Formatting3:36 min
    • 08Your Challenge - Problem1:01 min
    • 09Your Challenge - Solution6:19 min
    • 10Module Resources0:00 min
  • Functions & Methods20 lectures1h 45m
    • 01Module Introduction1:12 min
    • 02Analyzing Key Function Parts1:38 min
    • 03Keep The Number Of Parameters Low!6:38 min
    • 04Refactoring Function Parameters - Ideas & Concepts3:43 min
    • 05When One Parameter Is Just Right2:12 min
    • 06Two Parameters & When To Refactor4:07 min
    • 07Dealing With Too Many Values4:26 min
    • 08Functions With A Dynamic Number Of Parameters2:41 min
    • 09Beware Of "Output Parameters"4:19 min
    • 10Functions Should Do One Thing!9:51 min
    • 11Why "Levels of Abstraction" Matter6:11 min
    • 12When Should You Split?2:51 min
    • 13Demo & Challenge13:09 min
    • 14Stay DRY - Don't Repeat Yourself2:03 min
    • 15Splitting Functions To Stay DRY5:41 min
    • 16Don't Overdo It - Avoid Useless Extractions6:51 min
    • 17Understanding & Avoiding (Unexpected) Side Effects12:01 min
    • 18Side Effects - A Challenge9:21 min
    • 19Why Unit Tests Matter & Help A Lot!6:15 min
    • 20Module Resources0:00 min
  • Control Structures & Errors17 lectures1h 9m
    • 01Module Introduction2:52 min
    • 02Useful Concepts - An Overview1:22 min
    • 03Introducing "Guards"2:53 min
    • 04Guards In Action6:33 min
    • 05Extracting Control Structures & Preferring Positive Phrasing3:17 min
    • 06Extracting Control Structures Into Functions4:03 min
    • 07Writing Clean Functions With Control Structures7:32 min
    • 08Inverting Conditional Logic8:07 min
    • 09Embrace Errors & Error Handling6:57 min
    • 10Creating More Error Guards4:27 min
    • 11Extracting Validation Code4:10 min
    • 12Error Handling Is One Thing!3:35 min
    • 13Using Factory Functions & Polymorphism8:56 min
    • 14Working with Default Parameters1:14 min
    • 15Avoid Magic Numbers & Strings0:00 min
    • 16Module Summary3:37 min
    • 17Module Resources0:00 min
  • Objects, Classes & Data Containers / Structures15 lectures1h 19m
    • 01Module Introduction1:42 min
    • 02Important: This is NOT an OOP or "Patterns & Principles" Course!2:14 min
    • 03Objects vs Data Containers / Data Structures4:10 min
    • 04Why The Differentiation Matters3:57 min
    • 05Classes & Polymorphism12:54 min
    • 06Classes Should Be Small!6:20 min
    • 07Understanding "Cohesion"4:49 min
    • 08The "Law Of Demeter" And Why You Should "Tell, Not Ask"11:40 min
    • 09The SOLID Principles2:05 min
    • 10The Single-Responsibility-Principle (SRP) & Why It Matters7:04 min
    • 11The Open-Closed Principle (OCP) & Why It Matters5:43 min
    • 12The Liskov Substitution Principle5:56 min
    • 13The Interface Segregation Principle4:18 min
    • 14The Dependency Inversion Principle7:00 min
    • 15Module Resources0:00 min
  • Summary & Checklist1 lecture9m
    • 01Concepts Summary & Checklist9:05 min
  • Course Roundup4 lectures6m
    • 01Staying Clean!2:56 min
    • 02Possible Next Steps2:43 min
    • 03Thanks & Goodbye!1:14 min
    • 04Bonus!0:00 min

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Clean Code

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