What is the best AI curriculum for high school students?

Code.org's AI Foundations is the most comprehensive free high school AI curriculum in 2026—a full-year pathway with Semester 1 on core CS and Semester 2 on understanding, creating with, and evaluating AI ethically. Supplement with MIT Day of AI high school units, TeachAI resources, and AI4K12 Big Ideas 3–5 at advanced depth.

Do high school students need to know Python for AI?

Python is the standard language for high school AI courses aligned to CSTA standards (e.g., CSTA 3A-AP-16). Code.org AI Foundations and most district programs introduce Python in Semester 1 before ML modules in Semester 2. Students targeting ML engineering careers should also learn basic statistics and linear algebra concepts.

How does high school AI curriculum align with AP exams?

AI Foundations aligns with AP Computer Science Principles topics including data, algorithms, and computing's impact on society. AP CSP does not require ML implementation, but AI units strengthen Big Idea 7 (Global Impact). Schools offering AP CSA can extend with ML libraries (scikit-learn, TensorFlow Lite) as post-AP electives.

What should high school AI ethics cover?

High school ethics should include facial recognition policy, algorithmic hiring bias, LLM hallucinations in academic work, deepfake legislation, environmental costs of model training, and intellectual property for AI-generated content. AI4K12 Big Idea 5 and California's 2025 TK–12 AI guidance provide grade-appropriate case studies.

How many credits should a high school AI course be?

A full-year course (1.0 credit, 120–180 hours) is ideal for college-bound students. Half-credit semester electives work for AI literacy requirements. Georgia, Ohio, and Massachusetts have published state-specific AI course standards that districts can adopt directly.

What capstone projects work for high school AI courses?

Strong capstones include training a classifier on a community dataset, building a RAG chatbot for a school FAQ, auditing a local government's AI use, or creating an AI-assisted accessibility tool. Portfolios with GitHub repos and written impact analyses prepare students for college CS programs.

What is the best AI curriculum for high school students?

Code.org's AI Foundations is the most comprehensive free high school AI curriculum in 2026—a full-year pathway with Semester 1 on core CS and Semester 2 on understanding, creating with, and evaluating AI ethically. Supplement with MIT Day of AI high school units, TeachAI resources, and AI4K12 Big Ideas 3–5 at advanced depth.

Do high school students need to know Python for AI?

Python is the standard language for high school AI courses aligned to CSTA standards (e.g., CSTA 3A-AP-16). Code.org AI Foundations and most district programs introduce Python in Semester 1 before ML modules in Semester 2. Students targeting ML engineering careers should also learn basic statistics and linear algebra concepts.

How does high school AI curriculum align with AP exams?

AI Foundations aligns with AP Computer Science Principles topics including data, algorithms, and computing's impact on society. AP CSP does not require ML implementation, but AI units strengthen Big Idea 7 (Global Impact). Schools offering AP CSA can extend with ML libraries (scikit-learn, TensorFlow Lite) as post-AP electives.

What should high school AI ethics cover?

High school ethics should include facial recognition policy, algorithmic hiring bias, LLM hallucinations in academic work, deepfake legislation, environmental costs of model training, and intellectual property for AI-generated content. AI4K12 Big Idea 5 and California's 2025 TK–12 AI guidance provide grade-appropriate case studies.

How many credits should a high school AI course be?

A full-year course (1.0 credit, 120–180 hours) is ideal for college-bound students. Half-credit semester electives work for AI literacy requirements. Georgia, Ohio, and Massachusetts have published state-specific AI course standards that districts can adopt directly.

What capstone projects work for high school AI courses?

Strong capstones include training a classifier on a community dataset, building a RAG chatbot for a school FAQ, auditing a local government's AI use, or creating an AI-assisted accessibility tool. Portfolios with GitHub repos and written impact analyses prepare students for college CS programs.

What is the best AI curriculum for high school students?

Code.org's AI Foundations is the most comprehensive free high school AI curriculum in 2026—a full-year pathway with Semester 1 on core CS and Semester 2 on understanding, creating with, and evaluating AI ethically. Supplement with MIT Day of AI high school units, TeachAI resources, and AI4K12 Big Ideas 3–5 at advanced depth.

Do high school students need to know Python for AI?

Python is the standard language for high school AI courses aligned to CSTA standards (e.g., CSTA 3A-AP-16). Code.org AI Foundations and most district programs introduce Python in Semester 1 before ML modules in Semester 2. Students targeting ML engineering careers should also learn basic statistics and linear algebra concepts.

How does high school AI curriculum align with AP exams?

AI Foundations aligns with AP Computer Science Principles topics including data, algorithms, and computing's impact on society. AP CSP does not require ML implementation, but AI units strengthen Big Idea 7 (Global Impact). Schools offering AP CSA can extend with ML libraries (scikit-learn, TensorFlow Lite) as post-AP electives.

What should high school AI ethics cover?

High school ethics should include facial recognition policy, algorithmic hiring bias, LLM hallucinations in academic work, deepfake legislation, environmental costs of model training, and intellectual property for AI-generated content. AI4K12 Big Idea 5 and California's 2025 TK–12 AI guidance provide grade-appropriate case studies.

How many credits should a high school AI course be?

A full-year course (1.0 credit, 120–180 hours) is ideal for college-bound students. Half-credit semester electives work for AI literacy requirements. Georgia, Ohio, and Massachusetts have published state-specific AI course standards that districts can adopt directly.

What capstone projects work for high school AI courses?

Strong capstones include training a classifier on a community dataset, building a RAG chatbot for a school FAQ, auditing a local government's AI use, or creating an AI-assisted accessibility tool. Portfolios with GitHub repos and written impact analyses prepare students for college CS programs.

What is the best AI curriculum for high school students?

Code.org's AI Foundations is the most comprehensive free high school AI curriculum in 2026—a full-year pathway with Semester 1 on core CS and Semester 2 on understanding, creating with, and evaluating AI ethically. Supplement with MIT Day of AI high school units, TeachAI resources, and AI4K12 Big Ideas 3–5 at advanced depth.

Do high school students need to know Python for AI?

Python is the standard language for high school AI courses aligned to CSTA standards (e.g., CSTA 3A-AP-16). Code.org AI Foundations and most district programs introduce Python in Semester 1 before ML modules in Semester 2. Students targeting ML engineering careers should also learn basic statistics and linear algebra concepts.

How does high school AI curriculum align with AP exams?

AI Foundations aligns with AP Computer Science Principles topics including data, algorithms, and computing's impact on society. AP CSP does not require ML implementation, but AI units strengthen Big Idea 7 (Global Impact). Schools offering AP CSA can extend with ML libraries (scikit-learn, TensorFlow Lite) as post-AP electives.

What should high school AI ethics cover?

High school ethics should include facial recognition policy, algorithmic hiring bias, LLM hallucinations in academic work, deepfake legislation, environmental costs of model training, and intellectual property for AI-generated content. AI4K12 Big Idea 5 and California's 2025 TK–12 AI guidance provide grade-appropriate case studies.

How many credits should a high school AI course be?

A full-year course (1.0 credit, 120–180 hours) is ideal for college-bound students. Half-credit semester electives work for AI literacy requirements. Georgia, Ohio, and Massachusetts have published state-specific AI course standards that districts can adopt directly.

What capstone projects work for high school AI courses?

Strong capstones include training a classifier on a community dataset, building a RAG chatbot for a school FAQ, auditing a local government's AI use, or creating an AI-assisted accessibility tool. Portfolios with GitHub repos and written impact analyses prepare students for college CS programs.

What is the best AI curriculum for high school students?

Code.org's AI Foundations is the most comprehensive free high school AI curriculum in 2026—a full-year pathway with Semester 1 on core CS and Semester 2 on understanding, creating with, and evaluating AI ethically. Supplement with MIT Day of AI high school units, TeachAI resources, and AI4K12 Big Ideas 3–5 at advanced depth.

Do high school students need to know Python for AI?

Python is the standard language for high school AI courses aligned to CSTA standards (e.g., CSTA 3A-AP-16). Code.org AI Foundations and most district programs introduce Python in Semester 1 before ML modules in Semester 2. Students targeting ML engineering careers should also learn basic statistics and linear algebra concepts.

How does high school AI curriculum align with AP exams?

AI Foundations aligns with AP Computer Science Principles topics including data, algorithms, and computing's impact on society. AP CSP does not require ML implementation, but AI units strengthen Big Idea 7 (Global Impact). Schools offering AP CSA can extend with ML libraries (scikit-learn, TensorFlow Lite) as post-AP electives.

What should high school AI ethics cover?

High school ethics should include facial recognition policy, algorithmic hiring bias, LLM hallucinations in academic work, deepfake legislation, environmental costs of model training, and intellectual property for AI-generated content. AI4K12 Big Idea 5 and California's 2025 TK–12 AI guidance provide grade-appropriate case studies.

How many credits should a high school AI course be?

A full-year course (1.0 credit, 120–180 hours) is ideal for college-bound students. Half-credit semester electives work for AI literacy requirements. Georgia, Ohio, and Massachusetts have published state-specific AI course standards that districts can adopt directly.

What capstone projects work for high school AI courses?

Strong capstones include training a classifier on a community dataset, building a RAG chatbot for a school FAQ, auditing a local government's AI use, or creating an AI-assisted accessibility tool. Portfolios with GitHub repos and written impact analyses prepare students for college CS programs.

What is the best AI curriculum for high school students?

Code.org's AI Foundations is the most comprehensive free high school AI curriculum in 2026—a full-year pathway with Semester 1 on core CS and Semester 2 on understanding, creating with, and evaluating AI ethically. Supplement with MIT Day of AI high school units, TeachAI resources, and AI4K12 Big Ideas 3–5 at advanced depth.

Do high school students need to know Python for AI?

Python is the standard language for high school AI courses aligned to CSTA standards (e.g., CSTA 3A-AP-16). Code.org AI Foundations and most district programs introduce Python in Semester 1 before ML modules in Semester 2. Students targeting ML engineering careers should also learn basic statistics and linear algebra concepts.

How does high school AI curriculum align with AP exams?

AI Foundations aligns with AP Computer Science Principles topics including data, algorithms, and computing's impact on society. AP CSP does not require ML implementation, but AI units strengthen Big Idea 7 (Global Impact). Schools offering AP CSA can extend with ML libraries (scikit-learn, TensorFlow Lite) as post-AP electives.

What should high school AI ethics cover?

High school ethics should include facial recognition policy, algorithmic hiring bias, LLM hallucinations in academic work, deepfake legislation, environmental costs of model training, and intellectual property for AI-generated content. AI4K12 Big Idea 5 and California's 2025 TK–12 AI guidance provide grade-appropriate case studies.

How many credits should a high school AI course be?

A full-year course (1.0 credit, 120–180 hours) is ideal for college-bound students. Half-credit semester electives work for AI literacy requirements. Georgia, Ohio, and Massachusetts have published state-specific AI course standards that districts can adopt directly.

What capstone projects work for high school AI courses?

Strong capstones include training a classifier on a community dataset, building a RAG chatbot for a school FAQ, auditing a local government's AI use, or creating an AI-assisted accessibility tool. Portfolios with GitHub repos and written impact analyses prepare students for college CS programs.

What is the best AI curriculum for high school students?

Code.org's AI Foundations is the most comprehensive free high school AI curriculum in 2026—a full-year pathway with Semester 1 on core CS and Semester 2 on understanding, creating with, and evaluating AI ethically. Supplement with MIT Day of AI high school units, TeachAI resources, and AI4K12 Big Ideas 3–5 at advanced depth.

Do high school students need to know Python for AI?

Python is the standard language for high school AI courses aligned to CSTA standards (e.g., CSTA 3A-AP-16). Code.org AI Foundations and most district programs introduce Python in Semester 1 before ML modules in Semester 2. Students targeting ML engineering careers should also learn basic statistics and linear algebra concepts.

How does high school AI curriculum align with AP exams?

AI Foundations aligns with AP Computer Science Principles topics including data, algorithms, and computing's impact on society. AP CSP does not require ML implementation, but AI units strengthen Big Idea 7 (Global Impact). Schools offering AP CSA can extend with ML libraries (scikit-learn, TensorFlow Lite) as post-AP electives.

What should high school AI ethics cover?

High school ethics should include facial recognition policy, algorithmic hiring bias, LLM hallucinations in academic work, deepfake legislation, environmental costs of model training, and intellectual property for AI-generated content. AI4K12 Big Idea 5 and California's 2025 TK–12 AI guidance provide grade-appropriate case studies.

How many credits should a high school AI course be?

A full-year course (1.0 credit, 120–180 hours) is ideal for college-bound students. Half-credit semester electives work for AI literacy requirements. Georgia, Ohio, and Massachusetts have published state-specific AI course standards that districts can adopt directly.

What capstone projects work for high school AI courses?

Strong capstones include training a classifier on a community dataset, building a RAG chatbot for a school FAQ, auditing a local government's AI use, or creating an AI-assisted accessibility tool. Portfolios with GitHub repos and written impact analyses prepare students for college CS programs.

What is the best AI curriculum for high school students?

Code.org's AI Foundations is the most comprehensive free high school AI curriculum in 2026—a full-year pathway with Semester 1 on core CS and Semester 2 on understanding, creating with, and evaluating AI ethically. Supplement with MIT Day of AI high school units, TeachAI resources, and AI4K12 Big Ideas 3–5 at advanced depth.

Do high school students need to know Python for AI?

Python is the standard language for high school AI courses aligned to CSTA standards (e.g., CSTA 3A-AP-16). Code.org AI Foundations and most district programs introduce Python in Semester 1 before ML modules in Semester 2. Students targeting ML engineering careers should also learn basic statistics and linear algebra concepts.

How does high school AI curriculum align with AP exams?

AI Foundations aligns with AP Computer Science Principles topics including data, algorithms, and computing's impact on society. AP CSP does not require ML implementation, but AI units strengthen Big Idea 7 (Global Impact). Schools offering AP CSA can extend with ML libraries (scikit-learn, TensorFlow Lite) as post-AP electives.

What should high school AI ethics cover?

High school ethics should include facial recognition policy, algorithmic hiring bias, LLM hallucinations in academic work, deepfake legislation, environmental costs of model training, and intellectual property for AI-generated content. AI4K12 Big Idea 5 and California's 2025 TK–12 AI guidance provide grade-appropriate case studies.

How many credits should a high school AI course be?

A full-year course (1.0 credit, 120–180 hours) is ideal for college-bound students. Half-credit semester electives work for AI literacy requirements. Georgia, Ohio, and Massachusetts have published state-specific AI course standards that districts can adopt directly.

What capstone projects work for high school AI courses?

Strong capstones include training a classifier on a community dataset, building a RAG chatbot for a school FAQ, auditing a local government's AI use, or creating an AI-assisted accessibility tool. Portfolios with GitHub repos and written impact analyses prepare students for college CS programs.

What is the best AI curriculum for high school students?

Code.org's AI Foundations is the most comprehensive free high school AI curriculum in 2026—a full-year pathway with Semester 1 on core CS and Semester 2 on understanding, creating with, and evaluating AI ethically. Supplement with MIT Day of AI high school units, TeachAI resources, and AI4K12 Big Ideas 3–5 at advanced depth.

Do high school students need to know Python for AI?

Python is the standard language for high school AI courses aligned to CSTA standards (e.g., CSTA 3A-AP-16). Code.org AI Foundations and most district programs introduce Python in Semester 1 before ML modules in Semester 2. Students targeting ML engineering careers should also learn basic statistics and linear algebra concepts.

How does high school AI curriculum align with AP exams?

AI Foundations aligns with AP Computer Science Principles topics including data, algorithms, and computing's impact on society. AP CSP does not require ML implementation, but AI units strengthen Big Idea 7 (Global Impact). Schools offering AP CSA can extend with ML libraries (scikit-learn, TensorFlow Lite) as post-AP electives.

High School AI Curriculum Grades 9–12 Guide 2026 | explainx.ai Blog

High school AI education in 2026 sits at a crossroads. States from California to Georgia are publishing AI learning priorities; Code.org has launched AI Foundations as a full-year pathway; and students arrive already using ChatGPT, Claude, and Gemini for homework—often without understanding how those systems work or fail.

This guide is a complete grades 9–12 AI curriculum blueprint: course structures, free resources, Python project sequences, standards alignment, ethics modules, and capstone designs for college-bound and career-ready students.

TL;DR: High School AI Curriculum

Question	Answer
Primary free course	Code.org AI Foundations (full-year, grades 9–12)
Standards frameworks	AI4K12, CSTA, ISTE, NGSS HS-ETS1
Core language	Python (Semester 1 foundation → Semester 2 ML/AI)
Key skills	ML training, prompt engineering, data analysis, ethical evaluation
AP alignment	AP Computer Science Principles (Big Idea 7: Global Impact)
Capstone	Portfolio project + written societal impact analysis

What High School Graduates Should Demonstrate

The AI4K12 high school grade-band charts and California's 2025 AI guidance converge on these outcomes by grade 12:

Competency	Example Demonstration
Train & evaluate ML models	Build a classifier in Python; report precision/recall
Engineer prompts systematically	Use structured templates for research and code tasks
Analyze societal impact	Written audit of facial recognition in a real deployment
Design AI-supported workflows	Multi-step pipeline: data → model → interface → test
Practice responsible use	Cite AI assistance; verify outputs; document limitations
Communicate technically	Present capstone to non-technical audience

These map to ISTE standards 1.7 (collaboration with AI tools), CSTA 3A-AP-16 (Python programs), and NGSS HS-ETS1-2/4 (engineering design with evidence).

Course Structure Options

Option 1: Full-Year AI Foundations (Recommended)

Credits: 1.0
Resource: Code.org AI Foundations
Schedule: Daily 45–55 min or block schedule equivalent

Semester	Focus	Outcomes
Semester 1	Core CS + Python fundamentals	Variables, functions, data structures, APIs
Semester 2	AI understanding, creation, ethics	ML training, generative AI, responsible judgment

Code.org includes an embedded AI Teaching Assistant for educators—critical for districts without dedicated CS staff.

Option 2: Semester AI Elective (Post-Algebra)

Credits: 0.5
Prerequisite: Intro CS or concurrent enrollment
Duration: 18 weeks

Condensed map:

Weeks 1–4: ML fundamentals + Python (NumPy, pandas intro)
Weeks 5–8: Supervised learning projects (scikit-learn)
Weeks 9–11: Generative AI + prompt engineering
Weeks 12–14: Ethics & policy case studies
Weeks 15–18: Capstone

Option 3: AI Literacy Requirement (Non-CS Track)

Credits: 0.25–0.5
Audience: All students, not just CS concentrators
Resource: MIT Day of AI high school units + TeachAI toolkit

Focus on AI4K12 Big Idea 5 (Societal Impact) and media literacy—not coding. Suitable for graduation requirements in "digital citizenship" or "21st century skills."

Full-Year Curriculum Map (Option 1 Detail)

Semester 1: Computing Foundations

Unit	Weeks	Topics	Projects
Intro to CS & Python	1–4	Variables, loops, functions	Calculator, text adventure
Data & APIs	5–8	JSON, CSV, REST APIs	Weather data fetcher
Algorithms & Efficiency	9–12	Big-O intro, sorting, searching	Algorithm comparison lab
Web & Interfaces	13–18	HTML/CSS/JS basics or Streamlit	Simple data dashboard

Semester 2: Artificial Intelligence

Unit	Weeks	Topics	Projects
How ML Works	1–3	Features, labels, train/test split	Iris classifier (scikit-learn)
Data Science for AI	4–6	pandas, visualization, cleaning	Kaggle-style dataset analysis
Neural Networks (Conceptual)	7–9	Perceptrons, layers, backprop overview	TensorFlow Playground exploration
Generative AI & LLMs	10–12	Transformers (high level), prompting, RAG	School FAQ chatbot with citations
Computer Vision & NLP	13–15	CV pipelines, sentiment analysis	Image tagger or review classifier
Ethics & Capstone	16–18	Bias audits, policy, environmental cost	Student choice capstone

Supplementary modules: Code.org "Coding with AI," "Exploring Generative AI," and MIT Day of AI "The Brain Behind the Bot" (ages 14–18).

Prompt Engineering as a High School Skill

Prompt engineering belongs in high school CS—not as a replacement for programming, but as a structured literacy skill parallel to essay writing.

Curriculum module (2 weeks):

Lesson	Skill	Exercise
1	Role, context, constraint	Rewrite vague prompts with explicit structure
2	Chain-of-thought	Compare zero-shot vs. step-by-step math solutions
3	Verification & citation	Require sources; catch hallucinations on known facts
4	Code prompting	Generate + test + debug Python functions
5	Multi-step workflows	Research → outline → draft → fact-check pipeline
6	Policy & disclosure	School AI-use policy co-authoring

Connect to practitioner workflows covered in our Claude Code guides—students who learn structured prompting in high school adapt faster to professional AI tools.

Ethics & Policy Module (Required)

High schoolers face real decisions: Is ChatGPT use cheating? Can they trust AI tutors? Should their school ban facial recognition?

Case study library:

Topic	Source / Hook	Discussion Question
Algorithmic hiring	Amazon recruiting tool (2018)	What data would you need to audit fairness?
Facial recognition	NYC tenant surveillance bans	Privacy vs. security tradeoffs
Academic integrity	District AI policies (2024–2026)	When is AI assistance learning vs. substitution?
Deepfakes	NY synthetic performer law	Who is responsible for labeled AI content?
Environmental impact	Training cost of large models	Should companies disclose energy use?
Open vs. closed models	Open-weight vs. API-only	What are tradeoffs for society?

Use Blakeley H. Payne's MIT ethics curriculum as the backbone; extend with current events.

Capstone Project Menu

Project Type	Difficulty	Skills Demonstrated	Portfolio Value
Community classifier	Medium	Data collection, ML, evaluation	GitHub + writeup
RAG school assistant	Medium–High	Embeddings, prompting, UI	Deployed demo
AI system audit	Medium	Research, ethics, writing	Policy brief
Accessibility tool	High	CV/NLP + user testing	Real users impacted
Generative art with consent	Medium	Gen AI + IP discussion	Creative + analytical

Rubric dimensions: Technical correctness (30%), documentation (20%), ethical analysis (25%), presentation (15%), iteration evidence (10%).

AP & Dual-Enrollment Alignment

Exam/Program	AI Curriculum Overlap	Gap to Fill
AP CSP	Data, algorithms, global impact	ML implementation not required—add as enrichment
AP CSA	Java OOP foundation	Post-AP Python ML elective recommended
IB Computer Science	HL option topics include AI	Check current syllabus for case study requirements
Dual enrollment CS	Varies by community college	Map to CS2023 AI knowledge area (see college guide)

Free & Low-Cost Resources

Resource	Type	Best Use
Code.org AI Foundations	Full course	Primary curriculum
MIT Day of AI	Modular units	Ethics, gen AI supplements
TeachAI Toolkit	Policy + lessons	District-wide rollout
Kaggle Learn	Micro-courses	Advanced students
Google Colab	Python environment	Free GPU for projects
Fast.ai	Advanced MOOC	Post-course enrichment

Teacher Requirements & PD

High school AI courses typically require:

Credential: CS teaching certification or district waiver with PD completion
Minimum PD: Code.org AI Foundations facilitator training + 1 ML project completed personally
Ongoing: Quarterly updates—generative AI landscape shifts faster than traditional CS

Districts without CS teachers can partner with regional CS hubs (CSTA chapters, university outreach) for co-teaching models.

K–12 & Beyond: The Full Pathway

Stage	Guide
K–5	AI Curriculum for Kids
6–8	AI Curriculum for Middle School
9–12	This guide
Undergraduate	AI Curriculum for College Students

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Summary

High school AI curriculum in 2026 must be technical, ethical, and practical. Code.org AI Foundations provides a free, full-year starting point; Python ML projects build real skill; prompt engineering and ethics modules prepare students for college and work—not just for passing exams.

The goal is not to produce ML PhDs from every classroom. It is to graduate students who can build, evaluate, and govern AI systems they will encounter in every career path.

AI Curriculum for High School (Grades 9–12): Complete Guide (2026)

TL;DR: High School AI Curriculum

What High School Graduates Should Demonstrate

Course Structure Options

Option 1: Full-Year AI Foundations (Recommended)

Option 2: Semester AI Elective (Post-Algebra)

Option 3: AI Literacy Requirement (Non-CS Track)

Full-Year Curriculum Map (Option 1 Detail)

Semester 1: Computing Foundations

Semester 2: Artificial Intelligence

Prompt Engineering as a High School Skill

Ethics & Policy Module (Required)

Capstone Project Menu

AP & Dual-Enrollment Alignment

Free & Low-Cost Resources

Teacher Requirements & PD

K–12 & Beyond: The Full Pathway

Summary

Related Reading

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AI Curriculum for College Students: Undergraduate Guide (2026)

AI Curriculum for Kids (K–5): Complete Elementary Guide (2026)

AI Curriculum for Middle School (Grades 6–8): Complete Guide (2026)