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AI and Applied Technology Training

Learn the foundations.
Build the application.
Take it to market.

This program is designed for serious beginners who want to move into practical capability fast. In the first 5 months, students learn the foundations and build AI-powered applications. In the next 3 months, they learn how to position, package, protect, and take those products to market.

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8 Months

full two-phase journey

Months 1 - 5

technical foundations, AI engineering, and product build

Months 6 - 8

branding, business systems, legal basics, and market launch

Program At A Glance

How the track is organized

A compact build path from software foundations into applied AI systems and a market-facing capstone.

Phase 1

Frontend, backend, full-stack, AI foundations

12 weeks

Phase 2

RAG, orchestration, local models, business applications

4 weeks

Phase 3

Capstone build, deployment, positioning, launch

4 weeks

End result

  • A working application students actually own
  • A clear audience and commercial use case
  • A capstone they can launch, pitch, or sell

Curriculum Promise

What Learners Can Realistically Achieve

1

Beginner to builder-seller

The promise is not theory for theory’s sake. The program is built to turn serious beginners into people who can build useful AI-powered applications and package them as real offers.

2

Build products people can pay for

Students learn frontend, backend, full-stack thinking, RAG systems, orchestration workflows, chatbots, local models, and practical AI business applications that can serve customers, teams, and real market needs.

3

Immediate gain matters

By the end, learners should leave with a working capstone, clearer technical confidence, and a product or service they can position, demonstrate, and potentially sell.

Why This Matters

Build Applications You Can Take To Market

In this market, people respond fastest to products that solve immediate problems and create visible value. That is why the track is not just about learning AI. It is about learning how to build your own application, shape it into a useful offer, and move it toward the right audience.

1

Build your own application

Instead of only learning tools, students are guided to create useful apps, assistants, workflows, and AI-powered services they can own.

2

Position it for a real audience

Products are not treated like school exercises. Students learn to identify who the product is for, what pain it solves, and why someone should pay attention.

3

Turn skill into market value

The goal is to move from technical learning to something monetizable, employable, or founder-ready through better communication, packaging, and launch thinking.

First 3 Months

Foundations Before Specialization

The first three months are where learners build the software and systems base that makes applied AI engineering possible. Without this layer, advanced tooling becomes shallow and fragile.

Frontend fundamentals with React, Next.js, interfaces, state, forms, and user flows

Backend fundamentals with APIs, authentication, databases, integrations, and deployment

Full-stack product thinking so learners understand how complete systems are assembled

AI engineering foundations including prompting, embeddings, RAG, tool use, evaluation, and workflow design

Skills Map

What Students Touch During The Program

ReactNext.jsNode.jsDatabasesAPIsRAGEmbeddingsVector SearchTool CallingAI AgentsChatbotsLocal ModelsAutomationAI Business AppsDeploymentCapstone Launch

Your Learning Map

The 5-Month Build Journey

You get an accelerated path from software foundations into applied AI engineering and a capstone that can be shown, tested, and launched.

Month 1

Identity, Orientation, and Frontend Entry

Students begin by understanding the kind of builder they are becoming while learning the digital basics required to start creating product interfaces.

  • Internet, APIs, databases, and deployment basics
  • HTML, CSS, JavaScript foundations
  • React and Next.js entry
  • UI composition and user-flow thinking
Deliverable: A responsive frontend project with real user-facing flows.
Month 2

Backend Systems and Full-Stack Foundations

The second month helps learners understand how products work behind the scenes and how frontend and backend systems connect in real applications.

  • Node.js and backend fundamentals
  • APIs, auth, and CRUD systems
  • Database design and integration
  • Connecting interface to backend logic
Deliverable: A deployed full-stack application with auth and data flow.
Month 3

Applied AI Engineering Fundamentals

Once software foundations are in place, students move into AI engineering and learn how modern AI-powered systems are actually designed and connected.

  • LLM concepts for builders
  • Prompt systems and evaluation basics
  • Embeddings and vector databases
  • RAG pipelines and chatbot architecture
Deliverable: A functional AI assistant or document-aware RAG prototype.
Month 4

Advanced Workflows, Local Models, and Business Use Cases

Learners now go deeper into orchestration, retrieval quality, tool use, automation workflows, and practical AI business applications tied to real problems and real audiences.

  • Advanced RAG and retrieval quality
  • Orchestration pipelines and tool calling
  • Local model usage and private inference
  • AI workflows for support, analysis, and operations
Deliverable: A market-facing AI workflow or business application prototype with a clearer customer use case.
Month 5

Capstone Build, Positioning, and Launch

The final month is about turning learning into visible proof and market movement. Students refine, ship, present, position, and prepare their work for jobs, freelancing, client work, or founder-led execution.

  • Capstone scoping and execution
  • Testing, iteration, and deployment
  • Portfolio and demo storytelling
  • Market positioning and launch readiness
Deliverable: A polished capstone, portfolio proof, launch narrative, and a clearer path to market.

Stage Map

The Full Progression Around The Core Curriculum

The journey is split into two clear phases. The first phase focuses on technical formation and product building. The second phase helps students position, protect, package, and take what they built to the market.

Phase 1

Months 1 - 5

Technical formation and product build
1

Identity and Orientation

Students understand who they are becoming, what they want to build, and what kind of market value they want to create.

2

Foundations

Frontend, backend, full-stack, and AI engineering fundamentals create the technical base for serious product work.

3

Applied Theory

Students move from concept to implementation through practical builds, system thinking, and working prototypes.

4

Capstone Build

Knowledge becomes a product. Learners ship something tied to a real user, business problem, or commercial opportunity.

Phase 2

Months 6 - 8

Market positioning and go-to-market readiness
5

Personal Branding and Communication

Students learn how to explain what they built, communicate value clearly, and present themselves as credible builders.

6

Business Systems

Pricing, packaging, operations, revenue thinking, and customer framing help students understand how products become offers.

7

Legal and Compliance

Students are introduced to contracts, IP, responsible AI thinking, and basic legal awareness for safer product execution.

8

Market Launch and Graduation

The product is positioned for the market, the audience is clearer, and the learner leaves with a stronger path to traction or opportunity.

Final Outcome

By Graduation, Learners Should Leave With Proof

A deployed project, clearer technical confidence, stronger product intuition, and a more credible path into jobs, freelancing, founder-led execution, or building an application that can be positioned and sold to a real audience.

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