Curriculum catalog · 20 programs

Full course catalog

Every program, with the audience it serves, the problem it solves, and the evidence learners leave with.

Course descriptions are published for evaluation. The curriculum itself — modules, materials, and delivery assets — is proprietary to LevelUp Economy and available under license.

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AI adoption workshops

7 courses

ADPT-01 · 1 day

Generative AI Fundamentals

A practical introduction to how generative AI works, where it helps, where it fails, and how professionals can use tools safely for research, drafting, analysis, and everyday productivity.

Who it’s for: AI-curious professionals, workforce teams, educators, nonprofit staff, and public-sector groups that need a grounded starting point.
Problem it solves: Teams are experimenting with AI tools without shared language, safety norms, or repeatable workflow habits.

Outcomes

Explain core AI concepts in plain language
Use AI for common knowledge-work tasks
Recognize hallucination and verification risks
Apply safe-use norms to everyday work

Modules

How generative AI works
Strengths, limits, and verification
Prompting for daily workflows
Safe use guidelines

Artifacts

Tested prompt set
Workflow map
Verification checklist
Team use norms

ADPT-03 · 1 day

Practical Prompt Engineering

Hands-on practice turning vague requests into reliable AI workflows using context, constraints, examples, iteration, evaluation, and reusable prompt patterns.

Who it’s for: Professionals, educators, analysts, operators, and teams that want more reliable AI results from common tools.
Problem it solves: Most AI use fails because requests are vague, context is missing, and outputs are not evaluated systematically.

Outcomes

Write clearer prompts for real tasks
Use examples and constraints effectively
Iterate and evaluate outputs
Create reusable prompt patterns

Modules

Prompt anatomy
Context and constraints
Examples and iteration
Evaluation routines

Artifacts

Prompt library
Before-and-after examples
Evaluation rubric
Reusable workflow prompts

ADPT-04 · 1 day

AI for Small Business and Entrepreneurs

A founder-friendly workshop for using AI to research markets, sharpen offers, create content, improve operations, test ideas, and build lightweight systems.

Who it’s for: Founders, small business owners, operators, entrepreneurship students, chambers, accelerators, and ecosystem builders.
Problem it solves: Small teams need practical leverage from AI without enterprise budgets, complex procurement, or vague strategy work.

Outcomes

Use AI for market and customer research
Improve offers and messaging
Prototype lightweight operating systems
Test ideas with faster feedback loops

Modules

Market and customer insight
Offer and content development
Operations and automation
Experiment design

Artifacts

Customer research brief
AI-assisted content pack
Operations improvement map
Experiment plan

ADPT-07 · 1 day

AI-Assisted Prototyping and Coding

A builder-oriented session for using AI coding tools to scope, generate, debug, and refine lightweight software prototypes while still practicing architecture, quality, security, and version-control judgment.

Who it’s for: Product builders, entrepreneurs, technical beginners, designers, operators, and teams exploring AI-assisted software creation.
Problem it solves: AI can speed software work, but learners still need architecture, quality, security, and version-control judgment.

Outcomes

Use AI coding tools productively
Break ideas into buildable tasks
Debug and refine generated code
Recognize quality and security limits

Modules

AI coding workflow
Planning and scaffolding
Debugging and refinement
Quality, security, and Git

Artifacts

Prototype plan
Working mini-build
Debug notes
Repository or handoff checklist

ADPT-11 · 1 day

Building and Evolving Custom GPTs

Participants design focused AI assistants with clear jobs, instructions, knowledge sources, guardrails, testing routines, and improvement plans for real workflows.

Who it’s for: Teams, educators, managers, operators, entrepreneurs, and service providers who want focused assistants for repeatable workflows.
Problem it solves: Custom assistants often fail because they lack a clear job, useful context, guardrails, testing, and improvement routines.

Outcomes

Define a useful assistant job
Write structured instructions
Test assistant behavior
Plan ongoing improvement and governance

Modules

Assistant use-case design
Instructions and knowledge
Guardrails and testing
Iteration and ownership

Artifacts

Custom GPT concept
Instruction set
Testing checklist
Improvement plan

ADPT-12 · 1 day

Become Your Team's AI Champion

A train-the-champion course for internal advocates who need to coach peers, model responsible use, identify use cases, and support adoption without becoming bottlenecks.

Who it’s for: Managers, team leads, peer coaches, internal champions, faculty leads, and early adopters supporting responsible AI use.
Problem it solves: AI adoption stalls when everyone waits for central experts or when early adopters cannot coach peers safely and consistently.

Outcomes

Coach peers on practical AI workflows
Model responsible experimentation
Identify team use cases
Support adoption without centralizing all expertise

Modules

Champion role and norms
Peer coaching practice
Use-case spotting
Adoption rituals and escalation

Artifacts

Champion playbook
Coaching prompts
Use-case log
Team adoption plan

ADPT-13 · 1 day

AI at Work: From Curiosity to Capability

A standalone workplace AI session that helps AI-curious professionals move beyond one-off prompting into repeatable workflows for better drafting, research, analysis, and planning.

Who it’s for: AI-curious professionals, employers, public agencies, institutions, and teams that need practical workplace AI habits.
Problem it solves: People try AI once or twice, but do not turn it into reliable workflows that improve real work quality or speed.

Outcomes

Build repeatable AI workflows
Improve drafting and research habits
Use AI for planning and analysis
Evaluate outputs before use

Modules

Workplace AI use cases
Workflow design
Research and drafting practice
Output review and next steps

Artifacts

Personal workflow map
Prompt pack
Review checklist
30-day AI practice plan

AI leadership and strategy

5 courses

LEAD-02 · 1 day

Generative AI Executive Briefing

A one-day executive briefing that gives leaders a grounded view of generative AI, where it changes work, what risks need attention, and which decisions should come before broader rollout.

Who it’s for: Executives, senior managers, agency leaders, board members, and program sponsors who need a concise strategic orientation before deeper adoption work.
Problem it solves: Leaders need shared language and a clear view of opportunity, risk, and decision points before AI tools spread informally across the organization.

Outcomes

Explain AI opportunity and risk at leadership level
Identify immediate executive decisions
Name early workflow and governance priorities
Set expectations for deeper implementation work

Modules

Executive AI landscape
Work, roles, and service delivery
Risk and governance decisions
Briefing-to-action next steps

Artifacts

Executive decision map
Risk and opportunity notes
Priority question list
Next-step briefing agenda

LEAD-05 · 1 day

AI Strategy and Use-Case Prioritization

Teams map real work, identify high-value AI opportunities, score use cases by feasibility and risk, and leave with a prioritized implementation plan.

Who it’s for: Leadership teams, managers, transformation leads, public-sector teams, and employers moving from exploration to implementation.
Problem it solves: Organizations often chase scattered AI experiments instead of prioritizing use cases by value, feasibility, risk, and readiness.

Outcomes

Map work into AI opportunity areas
Score use cases with shared criteria
Identify data and governance dependencies
Sequence pilots into an action plan

Modules

Workflow mapping
Use-case discovery
Prioritization scoring
Pilot planning

Artifacts

Use-case inventory
Prioritization matrix
Readiness notes
Pilot roadmap

LEAD-06 · 1 day

Responsible AI, Governance, and Risk

A practical governance primer covering data sensitivity, bias, accuracy, IP, transparency, human review, policy norms, and risk controls that make adoption safer.

Who it’s for: Leaders, managers, compliance teams, educators, public institutions, employers, and organizations setting AI norms.
Problem it solves: AI adoption can create reputational, legal, operational, and equity risks when teams lack practical guardrails.

Outcomes

Recognize common AI risk categories
Apply human review and transparency norms
Create practical usage guardrails
Connect governance to implementation decisions

Modules

Risk categories
Data and IP considerations
Bias, accuracy, and review
Policy and controls

Artifacts

AI risk checklist
Use policy draft
Review protocol
Governance action notes

LEAD-14 · 1 week

AI Leadership Implementation Intensive

A one-week implementation intensive where leaders move from AI awareness into use-case selection, workflow redesign, governance routines, change management, and value measurement.

Who it’s for: Managers, executives, agency leaders, entrepreneurs, institutional teams, and implementation owners responsible for AI adoption.
Problem it solves: Leaders need enough depth to guide teams through adoption, redesign work, govern responsibly, and measure value.

Outcomes

Guide AI adoption with practical strategy
Redesign priority workflows with teams
Set governance routines and adoption norms
Build an implementation roadmap with measures

Modules

AI strategy and organizational context
Workflow redesign and operating models
Governance routines and change management
Implementation roadmap and measurement

Artifacts

Leadership AI brief
Workflow redesign plan
Governance routine map
Measured implementation roadmap

LEAD-15 · 1 month

AI Mini MBA

A live, applied executive learning experience that helps leaders use AI for strategy, roadmapping, decision-making, organizational change, customer insight, and team performance.

Who it’s for: Executives, entrepreneurs, ecosystem leaders, senior teams, and business professionals who need a structured business lens on AI.
Problem it solves: Leaders need to connect AI to strategy, customers, operating models, team performance, and measurable business change.

Outcomes

Use AI for business model and market analysis
Apply AI to strategy and decision-making
Redesign workflows and team practices
Present an executive implementation roadmap

Modules

AI and business model change
Customer insight and strategy
Operations and team performance
Capstone roadmap

Artifacts

AI-enabled analysis
Strategic roadmap
Organizational change plan
Executive presentation

Digital readiness and cyber resilience

4 courses

READY-08 · 1 day

Cybersecurity Awareness and Digital Hygiene

A non-technical security course on passwords, phishing, device safety, secure collaboration, AI-enabled threats, personal data protection, and responsible digital habits.

Who it’s for: Non-technical staff, students, small businesses, public-sector teams, and community learners who need practical security habits.
Problem it solves: AI-enabled threats, phishing, weak passwords, and unsafe collaboration practices create risk for individuals and organizations.

Outcomes

Identify common cyber and AI-enabled threats
Improve password and device practices
Use safer collaboration habits
Protect personal and organizational data

Modules

Threat landscape
Phishing and social engineering
Device and account hygiene
Data and collaboration safety

Artifacts

Security habit checklist
Phishing recognition examples
Personal security plan
Team hygiene commitments

READY-10 · 1 day

Technology Career Readiness

A career-focused workshop helping learners translate technical practice into resumes, portfolios, interviews, professional communication, and credible signals for employers.

Who it’s for: Learners entering technical pathways, job seekers, workforce participants, and students translating skill-building into employment signals.
Problem it solves: Many learners complete training without knowing how to present work, interview, communicate, or show credible evidence to employers.

Outcomes

Translate learning into employer-facing evidence
Improve resumes and project descriptions
Practice interview communication
Build a practical career action plan

Modules

Career signals
Resume and portfolio story
Interview practice
Professional communication

Artifacts

Resume bullets
Portfolio narrative
Interview response bank
Career action plan

READY-16 · 1 month

Foundations of Digital Literacy and Coding

A bridge program for learners building confidence with computers, the web, coding concepts, AI tools, digital collaboration, and the habits needed for technical learning.

Who it’s for: Beginning learners, community cohorts, workforce participants, students, and adults building confidence for technical learning.
Problem it solves: Learners often enter technical programs without the digital fluency, confidence, vocabulary, and habits needed to persist.

Outcomes

Build digital confidence and vocabulary
Understand basic web and coding concepts
Use AI and collaboration tools responsibly
Prepare for deeper technical pathways

Modules

Digital confidence and tools
Web and coding concepts
AI and collaboration basics
Learning habits and readiness

Artifacts

Digital skills checklist
Intro coding exercises
Collaboration profile
Readiness plan

READY-17 · 1 month

Digital Venture and Tech Career Readiness

A practical pathway for learners exploring tech careers, freelancing, and venture creation through problem discovery, digital tools, portfolio artifacts, job readiness, and pitching.

Who it’s for: Learners exploring tech careers, aspiring founders, entrepreneurship programs, workforce cohorts, and youth or adult upskilling initiatives.
Problem it solves: Learners need a practical bridge between digital tools, career readiness, venture thinking, and visible work products.

Outcomes

Discover problems worth solving
Use digital tools for venture and career work
Create portfolio artifacts
Practice pitching and employer-facing communication

Modules

Problem discovery
Digital tools and prototypes
Portfolio and job readiness
Pitching and communication

Artifacts

Problem brief
Digital prototype or workflow
Portfolio assets
Pitch or interview narrative

Technical AI and engineering pathways

4 courses

TECH-09 · 1 day

Git and GitHub Fundamentals

An applied introduction to repositories, commits, branches, pull requests, collaboration norms, documentation, and the portfolio value of visible technical work.

Who it’s for: Technical learners, bootcamp students, analysts, junior developers, instructors, and teams new to collaborative software workflows.
Problem it solves: Learners and teams need visible, professional collaboration habits before their technical work becomes credible to employers.

Outcomes

Use core Git and GitHub workflows
Collaborate through branches and pull requests
Document technical work
Build employer-visible portfolio signals

Modules

Repositories and commits
Branches and pull requests
Collaboration norms
Documentation and portfolio signals

Artifacts

GitHub repository
Pull request
README draft
Collaboration workflow checklist

TECH-18 · 18 weeks

Applied AI and Machine Learning Systems

A systems-build pathway with 2-week pre-work plus 16 instructor-led weeks. Learners build GitHub-based pipelines, SQL and analytics workflows, predictive models, NLP systems, RAG, knowledge graphs, FastAPI services, Docker deployments, monitoring, and a capstone.

Who it’s for: Emerging engineers, data-capable learners, universities, workforce partners, and employers building applied AI talent pipelines.
Problem it solves: Partners need deeper AI talent pathways where learners can build, evaluate, deploy, and explain real systems, not just complete isolated notebooks.

Outcomes

Build reproducible data and ML workflows
Apply NLP, RAG, and knowledge graph patterns
Deploy API-based AI services
Present a capstone with technical and business rationale

Modules

Python, GitHub, SQL, and analytics
Predictive modeling and evaluation
NLP, RAG, and knowledge graphs
APIs, Docker, monitoring, and capstone

Artifacts

GitHub portfolio
Data and ML pipelines
RAG or NLP system
Deployed capstone briefing

TECH-19 · 6 months

AI Product Engineering and Full-Stack Development

A six-month product engineering pathway covering front-end and back-end development, databases, APIs, GitHub workflows, testing, deployment, AI-assisted coding, model/API integration, and portfolio-ready intelligent product builds.

Who it’s for: Learners preparing for software engineering roles, workforce cohorts, technical upskilling programs, and institutions building AI-enabled developer pathways.
Problem it solves: Modern software programs need to teach full-stack engineering alongside AI-assisted development, API integration, and intelligent product patterns.

Outcomes

Build full-stack applications
Integrate AI APIs and model-driven features
Use GitHub, testing, and deployment workflows
Ship portfolio-ready AI product builds

Modules

Front-end and UX foundations
Back-end, databases, and APIs
AI-assisted coding and model/API integration
Testing, deployment, and product portfolio

Artifacts

Full-stack app
AI feature integration
Tested repository
Deployed portfolio project

TECH-20 · 6 months

Python Backend and Automation Engineering

A six-month Python pathway focused on programming fundamentals, automation, data handling, APIs, backend patterns, testing, tooling, and applied projects that prepare learners for backend, data, and AI-adjacent roles.

Who it’s for: New technical learners, analysts moving into engineering, workforce partners, and institutions building a practical Python talent pipeline.
Problem it solves: Learners need durable engineering habits in Python before moving into automation, data, backend, AI, or software roles.

Outcomes

Write reliable Python programs
Automate and handle data
Build APIs and backend patterns
Use testing, documentation, and tooling

Modules

Syntax, control flow, and data structures
Files, APIs, and automation
Backend patterns and testing
Applied projects and portfolio

Artifacts

Python project portfolio
Automation scripts
API or backend project
Tests and documentation