Master Concepts by Building Them.
Practice the Thinking Behind Modern Technology And Master Through Structured Workflows.
What CodePLU Is and Is Not
What CodePLU Is
CodePLU is a node-based e-learning and practice platform for technical subjects. It helps learners build real understanding through interactive workflows, guided concepts, and hands-on drills.
What CodePLU Is Not
CodePLU is not a passive article-only blog or a shortcut content dump. It is designed for active learning, structured practice, and step-by-step skill building.
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Search CodePLU Concepts
CodePLU Goal
Upgrading Human Mental Models
Learn how to think in Workflows
Why It Feels Different
See a concept as a workflow, not just a paragraph
Passive platforms tell you what sorting is. CodePLU shows how the idea moves from input to process to output, so your mental model becomes visual, structured, and easier to remember.
Learning Tracks
Interactive Workflow Based Learning
Each section is focused on a core track with interactive topics and basic concepts to help learners practice with clarity.
Artificial Intelligence
Learn Artificial Intelligence through hands-on workflows and visual nodes. Build, test, and connect AI components like vision, reasoning, and agents while understanding how real-world AI systems are designed, deployed, and improved in practice.
Interactive Topic
Build a Simple Decision Agent
Basic concept: AI systems convert input signals into actions using perception, reasoning, and feedback loops.
Checkpoint Detail
Define the goal and environment constraints.
Starter Lesson
Types of AI SystemsLearn how artificial intelligence is categorized based on its capabilities, from highly specialized tools to theoretical super-intelligence.
Beginner • 10 min
Start PracticeLarge Language Models (LLMs)
Explore Large Language Models through visual pipelines and node-based experiments. Build workflows with models like GPT, Claude, and Gemini to understand inference, tools, memory, and orchestration in real-world AI applications.
Interactive Topic
Prompt to Tokens Simulator
Basic concept: An LLM predicts the next token from context, so prompt structure directly affects response quality.
Checkpoint Detail
Split a prompt into role, instruction, and context.
Starter Lesson
What are Large Language Models (LLMs)?Learn how Large Language Models are trained on massive text data to recognize language patterns and generate human-like responses.
Beginner • 10 min
Start PracticePrompt Engineering
Practice Prompt Engineering using hands-on workflows that connect prompts, models, and outputs. Experiment with real scenarios, test variations, and learn how to design reliable prompt systems for automation, content, and AI-powered tools.
Interactive Topic
Prompt Debugging Lab
Basic concept: Prompt engineering is iterative: constrain output, provide examples, and test failure cases.
Checkpoint Detail
State task, output format, and quality criteria.
Starter Lesson
What is Prompt Engineering?Learn the core process of designing clear, structured instructions to guide AI systems toward your exact desired outputs.
Beginner • 10 min
Start PracticeData Science
Learn Data Science by assembling data workflows with practical nodes for cleaning, analysis, and visualization. Turn raw data into insights through step-by-step, hands-on projects that mirror real analytics and decision pipelines.
Interactive Topic
Data Pipeline Sanity Check
Basic concept: Reliable insights depend on clean data, explicit assumptions, and reproducible analysis steps.
Checkpoint Detail
Profile missing values and schema mismatch.
Starter Lesson
What is Data Science?Learn the core process of Data Science, from gathering raw data to extracting actionable insights for decision-making.
Beginner • 10 min
Start PracticeMachine Learning
Master Machine Learning by creating end-to-end pipelines with interactive nodes and workflows. Train models, evaluate results, and experiment with data step by step to understand how learning systems are built and optimized in real projects.
Interactive Topic
Model Training Playground
Basic concept: Machine learning learns patterns from training data and must generalize on unseen samples.
Checkpoint Detail
Split data into train, validation, and test.
Starter Lesson
What is Machine Learning?Learn the core difference between traditional programming and Machine Learning, and how systems learn from data to make predictions.
Beginner • 10 min
Start PracticeProgramming
Build real software by connecting logic through interactive nodes and workflows. Learn Programming concepts, algorithms, and system design by creating, testing, and iterating on practical projects instead of just reading code.
Interactive Topic
Algorithm Thinking Drill
Basic concept: Programming is structured problem solving: decompose the task, design logic, and verify behavior.
Checkpoint Detail
Translate the problem into inputs/outputs.
Starter Lesson
What is HTML?Learn the basics of HTML, the foundational markup language used to structure web pages and organize content on the internet.
Beginner • 10 min
Start PracticeComputer Science
Learn Computer Science through interactive workflows that make abstract ideas concrete. Explore algorithms, data structures, computation, and system thinking by following visual learning paths instead of only reading static explanations.
Interactive Topic
Algorithm Flow Explorer
Basic concept: Computer science explains how data, algorithms, and systems work together to solve problems systematically.
Checkpoint Detail
Identify the input, rules, and desired output.
Starter Lesson
What is Computational Thinking?Learn the foundation of problem-solving by breaking down complex tasks into clear, logical steps that a computer can execute.
Beginner • 10 min
Start Practice