A structured, project-first track where students learn AI workflows and ship real outcomes across media and code.
Students progress from guided AI creation into deeper product work: planning MVP scope, generating and refining code, debugging effectively, and presenting polished project outcomes. The program includes trailer production, web game/app builds, mobile and 3D project expansion, and a final capstone showcase.
Students explore the capabilities and limitations of GenAI tools across different media types (text, image, video, audio). They learn ethical considerations, responsible use guidelines, and how AI fits into creative and technical workflows. Hands-on exercises with ChatGPT, Claude, and Gemini introduce conversational AI interaction patterns.
Students learn structured prompt writing: clear instructions, context setting, constraint application, and output formatting. They practice iterative refinement by comparing outputs, identifying weaknesses, and adjusting prompts for better results. Exercises cover text generation, image creation with descriptive prompts, and consistency across multiple generations.
Students plan a 1-2 minute video trailer by breaking narratives into scenes, defining visual concepts, and creating storyboards. They use AI to generate concept art, test different visual styles, and refine scene descriptions. Students learn to organize assets, manage project files, and maintain creative consistency across multiple AI-generated elements.
Students create custom voiceovers using ElevenLabs with emotion and pacing control, then compose original background music with Suno by describing mood, genre, and instrumentation. They practice audio editing: trimming clips, adjusting volume levels, syncing audio to video timing, and exporting in appropriate formats. Final output integrates voice and music into trailer scenes.
Students define MVP scope for an interactive web game featuring store mechanics, currency systems, and upgrade paths. Using AI coding assistants (ChatGPT/Claude), they scaffold HTML/CSS/JavaScript structure, implement basic game loops, and test initial functionality. Students compare outputs from different AI tools, learning which assistants excel at different coding tasks.
Students expand game features: adding multiple upgrade tiers, implementing save/load functionality, creating UI feedback for player actions, and balancing game economy. They learn systematic debugging: reading error messages, using browser DevTools console, testing edge cases, and documenting fixes. Emphasis on iterative improvement and quality control workflows.
Students choose between two paths: (1) create a second web game with advanced mechanics like character progression or multiple levels, or (2) polish their existing build to production quality with animations, sound effects, and visual refinements. Both paths emphasize independent problem-solving and applying learned workflows without heavy instructor guidance.
Students complete final quality passes on both trailer and web projects: fixing remaining bugs, improving visual consistency, optimizing performance, and preparing presentation materials. They present projects to the class, explaining their creative process, technical decisions, challenges overcome, and lessons learned. Structured peer feedback session helps students reflect on their work.
Students analyze target users and define core value propositions for their mobile app. They create feature priority lists (must-have vs. nice-to-have), sketch basic wireframes, and plan a realistic development sequence. Introduction to product thinking: solving user problems, not just adding features. Students practice writing clear project requirements that guide AI-assisted development.
Students use Bolt.new and Lovable to generate initial app structure for a gamified habit tracker (Habitica-inspired). They set up navigation flows between screens, create basic component hierarchy, and implement responsive layouts. Learning focus: understanding generated code structure, identifying key files, and making intentional modifications rather than blind copy-pasting.
Students implement core habit tracking logic: creating tasks, marking completion, calculating streaks, and awarding points. They build reward systems with virtual currency, unlockable features, and progress visualization. Students learn data persistence using localStorage or simple backend integration, ensuring user progress saves between sessions. Emphasis on feature completeness over feature quantity.
Students apply systematic debugging methodology: reproducing bugs consistently, isolating problem areas, reading stack traces, and testing fixes thoroughly. They prioritize issues by severity (crashes vs. minor UI glitches) and user impact. Introduction to VS Code debugging tools, browser DevTools for mobile simulation, and maintaining a bug tracking log. Students practice explaining bugs clearly to AI assistants for better fix suggestions.
Students create interactive 3D scenes using Three.js and AI assistance. They set up basic 3D environments with lighting, cameras, and geometric objects. Learning activities include: positioning objects in 3D space, implementing orbit controls for user camera navigation, adding textures and materials, and understanding the render loop. Students create a simple interactive 3D world with clickable objects.
Students enhance their 3D world with responsive interactions: raycasting for object selection, hover effects, click handlers triggering animations, and state changes based on user input. They implement environmental triggers (proximity detection, collision zones) and audio feedback for actions. Students add particle effects, animations on object interaction, and UI overlays showing interaction hints.
Students build a Crossy Road-style 3D game featuring player movement (keyboard/touch controls), procedurally generated obstacles, collision detection, scoring systems, and game state management (start, playing, game over). They implement increasing difficulty, visual feedback for actions, and restart functionality. Focus on creating a complete game loop: setup → play → fail → restart, with polished transitions between states.
Students perform final QA on both mobile app and 3D game: comprehensive testing across devices, fixing critical bugs, optimizing performance (reducing lag, improving load times), and documenting features. They prepare demo presentations explaining technical architecture, development challenges, solutions implemented, and future improvement ideas. Students practice professional project presentation skills and receive structured feedback.
Students brainstorm original project ideas drawing from skills learned in Levels 1-2. They define their target audience, core problem being solved, and measurable success criteria. Students create a project proposal outlining: project type (web app, mobile app, 3D game, multimedia experience), primary features, technical requirements, and expected outcomes. Instructor provides feedback on scope feasibility and technical approach.
Students decompose their project into development milestones with clear deliverables for each phase. They select appropriate tools and platforms (Replit vs. VS Code, Bolt.new vs. manual coding, Three.js vs. 2D canvas), create detailed feature breakdowns, and identify technical risks requiring early validation. Students produce a written implementation plan including: architecture decisions, data flow diagrams, and week-by-week development schedule.
Students build a minimal working prototype demonstrating core functionality and validating key technical assumptions. Focus is on proving the concept works, not perfection. They test critical user interactions, verify chosen tools can deliver required features, and identify gaps in their technical knowledge. Students present prototypes for peer feedback, collecting suggestions that inform next development phases.
Students implement their first major feature set, establishing clean code architecture that supports future expansion. They set up proper project structure with organized files, implement core user flows from start to finish, and create reusable components/functions. Emphasis on building strong foundations: clear variable naming, modular code organization, and documentation of complex logic for future reference.
Students expand functionality with secondary features, polish existing implementations, and optimize user experience. They add advanced interactions, improve visual design with better UI/UX, implement data persistence or backend integration if needed, and create engaging feedback loops. Students practice balancing new feature development with code quality maintenance and bug fixing.
Students conduct comprehensive quality assurance: testing all features across different scenarios, fixing bugs by priority, optimizing performance (load times, frame rates, responsiveness), and refining visual consistency. They prepare showcase materials including screenshots, demo videos, project descriptions, and usage instructions. Students practice explaining technical work to non-technical audiences.
Students evaluate their development process through structured reflection: What worked well? What was harder than expected? What would they do differently? They document key learnings, technical skills gained, and problem-solving strategies developed. Students make final revisions based on self-assessment and testing feedback, ensuring their project represents their best work and demonstrates mastery of program skills.
Students deliver formal presentations of completed capstone projects to classmates, instructors, and invited guests (parents, peers from other programs). Presentations include: live demo, technical architecture explanation, development challenges and solutions, creative decisions and rationale, and future enhancement ideas. Students practice professional communication skills, respond to questions confidently, and celebrate their accomplishments with constructive peer recognition.
1-2 minute trailer with AI-generated scenes, custom voiceover, and original music composition.
Interactive browser game with store systems, upgrades, and progression mechanics.
Gamified habit tracker with rewards, streaks, and user persistence.
Browser-based 3D environment with camera controls, clickable objects, and animations.
Crossy Road-style game with player movement, obstacles, scoring, and game states.
Student-designed final project combining all learned skills into an original creation.
This program is designed to build practical skills, healthy technology habits, and visible progress. Instead of passive screen time, students create real outputs and learn how to think, plan, and solve problems with modern tools.
Students learn how to move from idea to working product using planning, coding, testing, and iteration.
Every project follows a repeatable process so children build confidence through clear milestones and feedback.
Students explain what they built, what went wrong, and what they improved, strengthening ownership and clarity.
Families can review concrete outcomes: trailer projects, web builds, advanced prototypes, and capstone work.
Students learn to define a clear build target, list must-have features, and sequence tasks before touching code.
Students move from vague prompts to structured prompts, compare outputs, and revise instructions for better results.
Students identify bugs by category (logic, UI, data flow), test fixes systematically, and verify improvements instead of guessing.
Students organize code into clearer blocks, use consistent naming, and maintain cleaner project files for easier maintenance.
Students evaluate builds from a user perspective, improve clarity of controls, and simplify confusing interactions.
Students present what they built, explain tool choices, and describe what changed between prototype and final version.
Students complete polished deliverables (trailer + interactive builds) that families can review and students can showcase.
Crafting effective prompts, iterating on outputs, and guiding AI tools to achieve specific creative goals.
Reading and modifying HTML, CSS, JavaScript, and Python to customize AI-generated outputs.
Breaking complex projects into manageable steps and combining multiple tools to achieve results.
Testing ideas quickly, gathering feedback, and refining projects based on user experience.
Explaining technical decisions, presenting projects clearly, and documenting creative processes.
Working with ChatGPT, Claude, Cursor, Replit, and modern development tools professionally.
No prior experience required for Level 1. Students learn through guided project work with AI assistance, making coding accessible even for complete beginners.
Weekly lessons are structured sessions focused on creative production, not passive consumption. Students build concrete projects with clear goals and checkpoints.
Each level builds on previous skills and workflows. We recommend starting at Level 1 unless your child has significant AI tool experience and completed projects.
Students can progress to other TechTutor programs (App Development, 3D Design, Game Programming) or continue building advanced capstone projects independently.
Students produce visible deliverables each level. Projects are presentable artifacts families can review, test, and share with friends and relatives.
Questions about enrollment or want to discuss your child's learning path?
Phone/WhatsApp/Zalo: 0902 776 753
Email: hello@techtutor.academy
Website: techtutor.academy
Hours: Mon-Fri 8:00-21:00 | Sat-Sun 8:00-20:00