A four-year instructional curriculum from digital literacy to cloud architecture, cybersecurity, AI, and coding. District-adaptable, cumulative, and career-focused.
A district-adaptable four-year instructional curriculum for high school students interested in information technology, networking, cybersecurity, cloud computing, artificial intelligence, coding, and data science. The sequence is intentionally cumulative: computer literacy → hardware & OS → networking → cybersecurity → cloud, AI & coding → workplace experience.
Each one-credit course spans a full academic year
Cybersecurity, Networking & Cloud, Software & AI, Support & SysAdmin
2-credit capstone with supervised work-based learning
1 Credit • Prerequisite: None • Introductory course developing computer literacy, communication, workplace, and IT skills
| Module | Main Topics |
|---|---|
| 1. Introduction to IT | What IT is, IT careers, computer systems, emerging technology, ethics |
| 2. Computer Hardware | CPU, RAM, motherboard, storage, input/output devices, peripherals |
| 3. Operating Systems | Windows, Linux basics, files/folders, user accounts, permissions |
| 4. Software Applications | Productivity software, word processing, spreadsheets, presentations |
| 5. Networking Basics | LAN/WAN, IP addresses, routers, switches, Wi-Fi, Internet basics |
| 6. Cybersecurity Fundamentals | Malware, phishing, passwords, MFA, social engineering, safe computing |
| 7. Data and Information | Data storage, databases, backups, privacy, data quality |
| 8. Programming Concepts | Algorithms, variables, logic, loops, basic scripting concepts |
| 9. Web and Digital Media | Websites, HTML basics, digital content, graphics, copyright |
| 10. IT Troubleshooting | Identifying problems, troubleshooting process, documentation |
| 11. Professional Skills | Communication, teamwork, customer service, technical documentation |
| 12. Careers and Certifications | IT career paths, résumés, interviews, industry certifications |
1 Credit • Prerequisite: Principles of IT • Hands-on computer support, repair, OS administration, and help-desk skills
| Module | Main Topics |
|---|---|
| 1. PC Architecture | CPU, motherboard, chipsets, RAM, buses |
| 2. Storage Technologies | HDD, SSD, NVMe, RAID, removable storage |
| 3. Power Systems | Power supplies, voltage, UPS, electrical safety |
| 4. Building a Computer | Component selection, installation, BIOS/UEFI |
| 5. OS Installation | Windows installation, drivers, partitions, updates |
| 6. Windows Administration | Users/groups, permissions, services, Event Viewer |
| 7. Linux Basics | CLI, files, permissions, processes |
| 8. Peripheral Devices | Printers, monitors, scanners, USB/Bluetooth devices |
| 9. Mobile Devices | Phones, tablets, laptops, hardware troubleshooting |
| 10. Networking for Technicians | TCP/IP, Wi-Fi, DNS, DHCP, connectivity testing |
| 11. Security | Malware prevention, account security, patching, endpoint protection |
| 12. Troubleshooting | Hardware/software diagnosis, logs, tools, ticketing |
| 13. Customer Support | Help desk procedures, communication, escalation |
| 14. Preventive Maintenance | Backups, patching, cleaning, asset management |
1 Credit • Prerequisite: Principles of IT recommended • Core security vocabulary, risk, defense, identity, cryptography, and incident response
| Module | Main Topics |
|---|---|
| 1. Introduction to Cybersecurity | CIA triad, threats, vulnerabilities, risks |
| 2. Cyber Ethics and Law | Responsible use, privacy, cybercrime, legal issues |
| 3. Threat Actors | Hackers, insiders, cybercriminals, nation-state actors |
| 4. Malware | Viruses, worms, ransomware, trojans |
| 5. Social Engineering | Phishing, spear phishing, impersonation |
| 6. Authentication | Passwords, MFA, biometrics |
| 7. Identity & Access Management | Users, groups, permissions, least privilege, RBAC |
| 8. Network Security | Firewalls, IDS/IPS, segmentation, VPN |
| 9. Endpoint Security | Antivirus, EDR concepts, patching, device security |
| 10. Cryptography | Encryption, hashing, certificates, PKI basics |
| 11. Web Security | Common web risks, safe browsing, HTTPS |
| 12. Vulnerability Management | Scanning, patching, risk prioritization |
| 13. Security Monitoring | Logs, alerts, SIEM concepts |
| 14. Incident Response | Identify, contain, eradicate, recover |
| 15. Business Continuity | Backup, disaster recovery, RPO/RTO basics |
| 16. Cybersecurity Careers | SOC analyst, security engineer, IAM, forensics |
1 Credit • Prerequisite: Computer Maintenance • Essential for cybersecurity — security makes much more sense after networking
| Module | Main Topics |
|---|---|
| 1. Networking Fundamentals | LAN, WAN, PAN, network models |
| 2. OSI and TCP/IP Models | 7-layer OSI model, TCP/IP stack |
| 3. Network Media | Ethernet, fiber, copper, wireless |
| 4. Ethernet and Switching | MAC addresses, switches, VLAN concepts |
| 5. IP Addressing | IPv4, IPv6, subnet masks |
| 6. Subnetting | Network IDs, host ranges, CIDR |
| 7. Routing | Routers, default gateway, routing tables |
| 8. Core Network Services | DNS, DHCP, NTP |
| 9. Wireless Networking | Wi-Fi standards, SSID, channels, security |
| 10. Network Security | Firewalls, ACLs, segmentation, VPNs |
| 11. Network Devices | Routers, switches, APs, firewalls |
| 12. Network Troubleshooting | ping, tracert, ipconfig, nslookup |
| 13. Network Monitoring | Logs, packet capture, SNMP |
| 14. Cloud Networking | Virtual networks, cloud connectivity basics |
| 15. Network Design Project | Design a small-business network |
1 Credit • Prerequisite: Foundations of Cybersecurity recommended • Lawful, ethical, methodical handling of digital evidence
| Module | Main Topics |
|---|---|
| 1. Introduction to Digital Forensics | Purpose, investigations, evidence |
| 2. Legal and Ethical Issues | Warrants, privacy, acceptable evidence |
| 3. Chain of Custody | Documentation and evidence handling |
| 4. Storage and File Systems | NTFS, FAT, partitions, deleted files |
| 5. Disk Imaging | Forensic copies, hashes, integrity |
| 6. Windows Forensics | Registry, logs, user artifacts |
| 7. Browser Forensics | History, cookies, downloads |
| 8. Email Forensics | Headers, metadata, phishing analysis |
| 9. Network Forensics | Logs, packets, connection records |
| 10. Mobile Forensics | Phones, tablets, app artifacts |
| 11. Memory Forensics | RAM concepts and volatile evidence |
| 12. Malware Investigation | Suspicious files and behavior |
| 13. Timeline Analysis | Reconstructing events |
| 14. Reporting | Writing an investigation report |
| 15. Final Investigation | Complete simulated forensic case |
1 Credit • Prerequisite: Foundations of Cybersecurity • Applied project: design a complete security environment
| Module | Main Topics |
|---|---|
| 1. Security Architecture Review | Assets, users, networks, controls |
| 2. Risk Assessment | Threat, vulnerability, likelihood, impact |
| 3. Vulnerability Assessment | Scanning and interpreting findings |
| 4. Network Defense | Firewalls, segmentation, monitoring |
| 5. Identity Security | Authentication, permissions, least privilege |
| 6. Threat Detection | Logs, SIEM, indicators of compromise |
| 7. Incident Response | Investigation and response exercises |
| 8. Digital Forensics | Evidence collection and analysis |
| 9. Security Policy | Policies, procedures, compliance |
| 10. Capstone Project | Design or assess a complete security environment |
| 11. Presentation | Present findings and recommendations |
1 Credit • Prerequisite: Networking recommended • Cloud models, virtualization, identity, security, monitoring, and architecture design
| Module | Main Topics |
|---|---|
| 1. Cloud Fundamentals | IaaS, PaaS, SaaS, deployment models, benefits and tradeoffs |
| 2. Virtualization | Virtual machines, containers, resource allocation |
| 3. Compute Services | VMs, serverless concepts, managed compute, scaling |
| 4. Cloud Storage | Object, block, file storage, databases, backup, encryption |
| 5. Cloud Networking | Virtual networks, subnets, security groups, load balancing |
| 6. Cloud IAM | Identities, roles, policies, MFA, federation, least privilege |
| 7. Security & Compliance | Shared responsibility, logging, encryption, vulnerability management |
| 8. Monitoring | Metrics, logs, alerts, dashboards |
| 9. Cost Management | Cost drivers, tagging, budgets, right-sizing |
| 10. Automation | Infrastructure as code, templates, scripting, repeatability |
| 11. Resilience | High availability, regions/zones, failover, RPO/RTO |
| 12. Cloud Architecture Project | Design a secure cloud solution for a fictional business |
2 Credits • Prerequisite: At least two prior IT courses • Supervised workplace or project-based experience
| Module | Main Topics |
|---|---|
| 1. Workplace Safety & Ethics | Professional conduct, confidentiality |
| 2. Help Desk Operations | Ticketing, escalation, documentation |
| 3. Technical Support | Hardware/software troubleshooting |
| 4. Networking Support | Connectivity and network troubleshooting |
| 5. System Administration | Accounts, permissions, devices |
| 6. Cybersecurity Operations | Security alerts, access controls, patching |
| 7. Project Management | Planning, milestones, documentation |
| 8. Customer Service | User interaction and communication |
| 9. Career Development | Résumé, interview, certification planning |
| 10. Work-Based Project | Internship or substantial IT project |
| 11. Portfolio | Document projects and skills |
| 12. Final Presentation | Present accomplishments |
A structured programming and software development sequence that runs alongside or integrates with the core IT & cybersecurity track. Students progress from computational thinking through advanced data structures and team-based projects.
1 Credit • Grades 9–12 • Prerequisite: None • First computer science course — designed for absolute beginners
| Module | Main Topics |
|---|---|
| 1. Computational Thinking | Decomposition, pattern recognition, abstraction, algorithmic thinking |
| 2. Everyday Computing | How computers work in daily life, input/output, digital vs. analog |
| 3. Hardware Fundamentals | CPU, storage, peripherals, binary representation, how data is stored |
| 4. Introduction to Programming | Block-based coding (Scratch or similar), sequences, events, loops |
| 5. Text-Based Programming | Python or similar language basics — variables, print, input, expressions |
| 6. Selection & Logic | If/else statements, Boolean operators, conditions, decision-making |
| 7. Iteration & Loops | For loops, while loops, counting, accumulating, loop patterns |
| 8. Functions & Reusability | Defining functions, parameters, return values, modular design |
| 9. Web Basics | HTML structure, basic CSS, JavaScript alerts/prompts, publishing a page |
| 10. Digital Citizenship | Online safety, privacy, copyright, responsible technology use |
| 11. Problem Solving | Designing solutions, pseudocode, flowcharts, testing strategies |
| 12. CS Careers & Next Steps | Software development, cybersecurity, data science, AI career paths |
1 Credit • Grades 10–11 • Prerequisite: Algebra I (required or corequisite) • Core programming — design and implement programs that solve problems
| Module | Main Topics |
|---|---|
| 1. Programming Style & Setup | IDEs, code formatting, comments, naming conventions, project structure |
| 2. Variables & Data Types | Integers, floats, strings, Booleans, type conversion, constants |
| 3. Operators & Expressions | Arithmetic, comparison, logical operators, order of operations |
| 4. Selection Structures | If/elif/else, nested conditionals, switch/match, decision tables |
| 5. Iteration Structures | For, while, do-while concepts, nested loops, loop control |
| 6. Functions & Subroutines | Parameters, return values, scope, function composition, libraries |
| 7. Arrays & Lists | Declaring, accessing, traversing, searching, modifying collections |
| 8. String Processing | Indexing, slicing, concatenation, formatting, parsing text |
| 9. Object-Oriented Basics | Classes, objects, attributes, methods, constructors, encapsulation |
| 10. Number Systems | Binary, decimal, hexadecimal, conversions, how computers represent data |
| 11. Testing & Debugging | Test cases, boundary testing, debugging techniques, error types |
| 12. Program Design & Presentation | Plan, build, test, document, and present a complete program |
1 Credit • Grades 11–12 • Prerequisite: Computer Science I + Algebra I • Advanced OOP, data structures, algorithms, and team projects
| Module | Main Topics |
|---|---|
| 1. OOP — Abstraction & Encapsulation | Access modifiers, getters/setters, data hiding, interface design |
| 2. OOP — Inheritance | Superclasses, subclasses, method overriding, class hierarchies |
| 3. OOP — Polymorphism | Dynamic dispatch, interfaces, abstract classes, design patterns |
| 4. Arrays & 2D Arrays | Multi-dimensional arrays, matrix operations, grid-based problems |
| 5. Lists & Collections | ArrayLists, dynamic sizing, iterators, choosing the right structure |
| 6. File I/O | Reading/writing files, CSV, text parsing, persistent storage |
| 7. String Algorithms | Pattern matching, tokenizing, formatting, regular expressions basics |
| 8. Recursion | Base cases, recursive calls, stack behavior, recursive vs. iterative |
| 9. Searching Algorithms | Linear search, binary search, performance comparison |
| 10. Sorting Algorithms | Selection, bubble, insertion, merge sort, Big-O analysis |
| 11. Boolean Algebra & Logic | Truth tables, simplification, logic gates, circuit concepts |
| 12. Nested Structures & Projects | Objects within objects, complex data models, team-based development |
1 Credit • Grade 12 • Prerequisite: Computer Science II or AP Computer Science A • Advanced data structures, software engineering, and capstone projects
| Module | Main Topics |
|---|---|
| 1. Advanced Data Structures | Linked lists, stacks, queues, hash tables, trees, graphs |
| 2. Algorithm Analysis | Time and space complexity, Big-O notation, optimization strategies |
| 3. Software Design Principles | Design patterns, SOLID principles, modularity, separation of concerns |
| 4. Version Control & Collaboration | Git workflows, branching, pull requests, code reviews, team practices |
| 5. Database Integration | SQL basics, CRUD operations, connecting applications to databases |
| 6. APIs & Web Services | REST concepts, consuming APIs, JSON, building simple services |
| 7. Testing & Quality | Unit testing, integration testing, test-driven development concepts |
| 8. Industry Practices | Agile methodology, sprints, documentation, deployment basics |
| 9. Emerging Technologies | AI/ML integration, cloud services, containerization, open-source |
| 10. Capstone Project | Independent or team project — plan, design, implement, test, and present a substantial application |
1 Credit • Grades 10–12 • Prerequisite: Fundamentals of CS or equivalent recommended • Broader than AP CSA — explores the big ideas of computing
| Module | Main Topics |
|---|---|
| 1. Creative Development | Collaboration, program design, development process, documentation |
| 2. Data | Binary, data compression, extracting information from data, visualization |
| 3. Algorithms & Programming | Variables, expressions, conditionals, iteration, procedures, libraries |
| 4. Computer Systems & Networks | The Internet, protocols, routing, fault tolerance, parallel computing |
| 5. Impact of Computing | Digital divide, bias in computing, legal/ethical issues, crowdsourcing |
| 6. Cybersecurity | Encryption, authentication, phishing, malware, data privacy, trust models |
| 7. Create Performance Task | Design, develop, and submit a program with written responses for the AP exam |
1–2 Credits • Grades 11–12 • Prerequisite: CS I or AP CSP + Algebra I strongly recommended • Java-focused, rigorous — prepares students for the AP exam
| Module | Main Topics |
|---|---|
| 1. Primitive Types | int, double, Boolean, casting, arithmetic expressions |
| 2. Using Objects | String class, wrapper classes, calling methods, Math class |
| 3. Boolean Expressions & If | Relational/logical operators, if/else, compound conditions |
| 4. Iteration | While loops, for loops, nested loops, loop analysis |
| 5. Writing Classes | Constructors, instance variables, methods, access control, scope |
| 6. Arrays | Declaring, traversing, inserting, deleting, array algorithms |
| 7. ArrayLists | Dynamic lists, add/remove/set, traversal, autoboxing |
| 8. 2D Arrays | Row-major traversal, matrix processing, nested iterations |
| 9. Inheritance | Superclass/subclass, overriding, polymorphism, Object class |
| 10. Recursion | Recursive methods, base cases, tracing recursive calls, efficiency |
| 11. Searching & Sorting | Sequential search, binary search, selection sort, insertion sort, merge sort |
| 12. AP Exam Preparation | Free-response practice, multiple-choice strategies, timed coding exercises |
1 Credit • Grades 10–12 • Prerequisite: Fundamentals of CS or CS I recommended • Apply programming skills to interactive game development
| Module | Main Topics |
|---|---|
| 1. Game Design Fundamentals | Game genres, mechanics, player experience, storyboarding, prototyping |
| 2. Development Environment | Game engines (Unity, Godot, or similar), project setup, asset management |
| 3. 2D Graphics & Sprites | Coordinate systems, sprites, animation, collision detection, tile maps |
| 4. Player Input & Controls | Keyboard, mouse, touch input, controller mapping, responsive controls |
| 5. Game Physics | Movement, gravity, velocity, acceleration, basic physics engines |
| 6. Game Logic & State | Game loops, state machines, scoring, levels, win/lose conditions |
| 7. Audio & Visual Effects | Sound effects, background music, particle effects, UI/HUD design |
| 8. AI in Games | Enemy behavior, pathfinding, decision trees, difficulty scaling |
| 9. Multiplayer Concepts | Local multiplayer, networking basics, turn-based vs. real-time |
| 10. Testing & Playtesting | Bug tracking, user feedback, iterating on design, performance |
| 11. Publishing & Distribution | Building for platforms, packaging, game stores, licensing |
| 12. Game Capstone | Design, develop, test, and present an original game |
1 Credit • Grades 10–12 • Prerequisite: CS I or AP CSP recommended • Design and build apps for mobile devices
| Module | Main Topics |
|---|---|
| 1. Mobile Platforms | iOS vs. Android, cross-platform tools, app ecosystem, design guidelines |
| 2. UI/UX Design | User interface elements, layouts, navigation, accessibility, wireframing |
| 3. Development Setup | IDE setup, emulators, project structure, build/run workflow |
| 4. App Architecture | Views, controllers, data binding, component lifecycle, state management |
| 5. User Input & Forms | Text fields, buttons, pickers, validation, gesture recognition |
| 6. Data Storage | Local storage, databases, preferences, file system, caching |
| 7. Networking & APIs | HTTP requests, REST APIs, JSON parsing, loading remote data |
| 8. Media & Sensors | Camera, GPS, accelerometer, maps, push notifications |
| 9. Security & Privacy | Secure storage, authentication, permissions, privacy policies |
| 10. Testing & Debugging | Device testing, emulator testing, crash reporting, performance |
| 11. Publishing | App store requirements, screenshots, descriptions, review process |
| 12. App Capstone | Design, build, test, and present an original mobile application |
0.5–1 Credit • Grades 9–12 • Prerequisite: None • Build responsive, accessible websites from scratch
| Module | Main Topics |
|---|---|
| 1. How the Web Works | Browsers, servers, URLs, HTTP, domains, hosting |
| 2. HTML Foundations | Elements, attributes, semantic tags, forms, tables, links, images |
| 3. CSS Styling | Selectors, properties, box model, colors, typography, layout |
| 4. Responsive Design | Media queries, flexbox, grid, mobile-first approach, breakpoints |
| 5. Accessibility | Alt text, ARIA, keyboard navigation, color contrast, screen readers |
| 6. JavaScript Basics | Variables, events, DOM manipulation, interactivity, form validation |
| 7. Advanced JavaScript | Functions, arrays, objects, fetch API, dynamic content loading |
| 8. Design Principles | Visual hierarchy, whitespace, color theory, typography, consistency |
| 9. Content Management | CMS concepts, templates, static site generators, blogging platforms |
| 10. Web Security | HTTPS, XSS awareness, input sanitization, safe authentication |
| 11. Performance & SEO | Page speed, image optimization, meta tags, search indexing |
| 12. Web Portfolio Project | Design and publish a multi-page personal or business website |
These courses complement both the core IT/cybersecurity sequence and the computer science track. They focus on emerging technologies, applied security, data analysis, and physical computing.
1 Credit • Grade 9–11 • Prerequisite: None • Build problem-solving skills through hands-on coding in Python, web technologies, and automation
| Module | Main Topics |
|---|---|
| 1. Computational Thinking | Decomposition, pattern recognition, abstraction, algorithms |
| 2. Python Basics | Variables, data types, input/output, operators, expressions |
| 3. Control Flow | Conditionals (if/elif/else), Boolean logic, nested conditions |
| 4. Loops & Iteration | For loops, while loops, break/continue, iteration patterns |
| 5. Functions | Defining functions, parameters, return values, scope, reusability |
| 6. Data Structures | Lists, tuples, dictionaries, sets, string manipulation |
| 7. File Handling | Reading/writing files, CSV processing, data parsing |
| 8. Error Handling & Debugging | Try/except, debugging strategies, testing, code review |
| 9. Web Fundamentals | HTML, CSS, responsive design, accessibility, publishing |
| 10. JavaScript Basics | Variables, events, DOM manipulation, interactive pages |
| 11. APIs & Data | What APIs are, JSON, fetching data, building simple apps |
| 12. Version Control | Git basics, repositories, commits, collaboration with GitHub |
| 13. Automation Projects | Scripting repetitive tasks, file organizers, data converters |
| 14. Final Coding Project | Plan, build, test, document, and present a complete application |
1 Credit • Grade 10–12 • Prerequisite: Programming Fundamentals + Foundations of Cybersecurity • Security-focused coding, automation, and tool building
| Module | Main Topics |
|---|---|
| 1. Security Scripting with Python | Python review, security libraries, scripting for defenders |
| 2. Network Scanning & Recon | Socket programming, port scanning concepts, network discovery (authorized labs only) |
| 3. Log Parsing & Analysis | Reading log files, regex, extracting indicators, anomaly detection |
| 4. Password Security | Hashing algorithms, salting, password strength testing, secure storage |
| 5. Web Security Testing | OWASP Top 10 awareness, input validation, XSS/SQLi concepts, secure coding |
| 6. Encryption in Practice | Implementing symmetric/asymmetric encryption, file encryption, certificates |
| 7. API Security | Authentication tokens, API keys, rate limiting, secure API calls |
| 8. Automation for Security Ops | Automating backups, patch checks, account audits, alert processing |
| 9. PowerShell for Windows Security | PowerShell basics, Active Directory queries, security auditing scripts |
| 10. Bash for Linux Security | Shell scripting, cron jobs, file integrity checks, system hardening |
| 11. Building Security Tools | File integrity monitor, simple vulnerability scanner, log aggregator |
| 12. Capture-the-Flag Challenges | CTF concepts, web challenges, crypto challenges, forensics challenges |
| 13. Responsible Disclosure & Ethics | Bug bounty concepts, ethical reporting, legal boundaries, career paths |
| 14. Security Tool Capstone | Design, build, test, and present an original security tool or automation |
1 Credit • Grade 10–12 • Prerequisite: Programming Fundamentals recommended • AI concepts, machine learning, ethics, and practical applications
| Module | Main Topics |
|---|---|
| 1. What Is AI? | History, definitions, narrow vs. general AI, current capabilities and limitations |
| 2. How Machines Learn | Training data, models, supervised vs. unsupervised learning, reinforcement learning |
| 3. Data for AI | Data collection, cleaning, labeling, bias in datasets, data quality |
| 4. Classification & Prediction | Decision trees, pattern recognition, spam filters, recommendation systems |
| 5. Natural Language Processing | Text analysis, sentiment analysis, chatbots, language models, prompt engineering |
| 6. Computer Vision | Image recognition, object detection, facial recognition, medical imaging |
| 7. Generative AI | How LLMs work, image generation, text generation, creative applications |
| 8. AI Ethics & Bias | Fairness, transparency, accountability, deepfakes, misinformation, job displacement |
| 9. AI & Privacy | Data collection concerns, surveillance, consent, regulation concepts (GDPR, COPPA) |
| 10. AI in Cybersecurity | Threat detection, anomaly detection, AI-powered attacks, defending against AI threats |
| 11. AI Tools & Workflows | Using AI responsibly in schoolwork, careers, research, coding, and productivity |
| 12. Building with AI APIs | Calling AI APIs, integrating AI into applications, prompt design, output validation |
| 13. AI & Society | Healthcare, transportation, education, environment, accessibility, economic impact |
| 14. AI Capstone Project | Identify a problem, apply AI concepts, build a prototype or analysis, present findings |
1 Credit • Grade 10–12 • Prerequisite: Programming Fundamentals recommended • Collect, analyze, visualize, and communicate data-driven insights
| Module | Main Topics |
|---|---|
| 1. What Is Data Science? | Data-driven decisions, roles, tools, real-world examples |
| 2. Data Collection | Surveys, APIs, web scraping concepts, public datasets, ethical sourcing |
| 3. Data Cleaning | Missing values, duplicates, formatting, outliers, data quality |
| 4. Spreadsheet Analytics | Advanced formulas, pivot tables, conditional formatting, dashboards |
| 5. Statistics Fundamentals | Mean, median, mode, standard deviation, distributions, correlation |
| 6. Data Visualization | Charts, graphs, heatmaps, design principles, storytelling with data |
| 7. Python for Data | Pandas, NumPy, data manipulation, filtering, grouping, aggregation |
| 8. Data Visualization with Code | Matplotlib, Plotly, creating interactive charts and dashboards |
| 9. Databases & SQL | Relational databases, SQL queries, joins, filtering, data extraction |
| 10. Exploratory Data Analysis | Hypothesis formation, pattern discovery, correlation vs. causation |
| 11. Data Privacy & Ethics | PII, anonymization, consent, bias in analysis, responsible reporting |
| 12. Data in Cybersecurity | Log analysis, security metrics, threat intelligence data, SIEM dashboards |
| 13. Communicating Results | Reports, presentations, executive summaries, audience-appropriate language |
| 14. Data Science Capstone | End-to-end project: collect, clean, analyze, visualize, and present findings |
1 Credit • Grade 10–12 • Prerequisite: Principles of IT • Physical computing, IoT devices, sensors, and the security of connected systems
| Module | Main Topics |
|---|---|
| 1. Introduction to IoT | What IoT is, smart devices, sensors, actuators, real-world applications |
| 2. Microcontrollers | Arduino or Raspberry Pi basics, GPIO pins, setup, first programs |
| 3. Sensors & Input | Temperature, motion, light, humidity sensors, reading analog/digital data |
| 4. Output & Actuators | LEDs, motors, relays, displays, controlling physical devices with code |
| 5. IoT Networking | Wi-Fi, Bluetooth, MQTT protocol, connecting devices to the Internet |
| 6. Data from Devices | Logging sensor data, cloud dashboards, real-time monitoring |
| 7. IoT Security Risks | Default credentials, unpatched firmware, data exposure, botnets |
| 8. Securing IoT Devices | Network segmentation, firmware updates, encryption, access control |
| 9. Smart Home & Wearables | Smart speakers, cameras, health devices, privacy implications |
| 10. Industrial IoT | SCADA/ICS concepts, critical infrastructure, safety vs. security |
| 11. Robotics Fundamentals | Motors, servos, sensors, autonomous movement, obstacle avoidance |
| 12. IoT Capstone Project | Build and secure a connected device or smart system, present findings |
Principles → Maintenance + Cybersecurity → Networking + Forensics → Capstone + Practicum
Principles → Maintenance → Networking → Cloud Computing + Practicum
Principles → Fundamentals of CS → CS I → AI + Data Science → Practicum
Fundamentals of CS → CS I → CS II / AP CSA → CS III + Practicum
Fundamentals of CS → CS I → Game Programming or Mobile App Dev → Practicum
Principles → Programming → Networking → Robotics, IoT & Embedded Security + Practicum
Principles → Maintenance → Networking → Practicum with help-desk focus
This curriculum is designed as a district-adaptable instructional map. Local course availability, instructor expertise, equipment, prerequisites, and certification partnerships should determine the final course selections and pacing. Each one-credit course covers approximately 36 instructional weeks. Suggested grading: 40% hands-on labs, 30% projects and documentation, 20% quizzes, 10% professional skills.