Technical AI and engineering pathways
TECH-1818 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.
Course profile
Problem solved
Curriculum that turns interest into usable capability.
Partners need deeper AI talent pathways where learners can build, evaluate, deploy, and explain real systems, not just complete isolated notebooks.
What learners produce
Artifacts that can be inspected, coached, and improved.
- GitHub portfolio
- Data and ML pipelines
- RAG or NLP system
- Deployed capstone briefing
Why license it
Built for delivery, adaptation, and local relevance.
- AI.SPIRE-style engineer upskilling
- University extension pathway
- Workforce AI certificate
- Employer talent pipeline
Course architecture
What the course covers.
Each LevelUp course combines practical instruction, guided application, and evidence of learning that partners can adapt to local economic priorities.
Module 01
Python, GitHub, SQL, and analytics
Module 02
Predictive modeling and evaluation
Module 03
NLP, RAG, and knowledge graphs
Module 04
APIs, Docker, monitoring, and capstone
Learning outcomes
What participants can do afterwards.
- 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
Bring this course to your community
License, adapt, or embed this curriculum inside a broader talent system.
LevelUp can support curriculum licensing, instructor enablement, partner delivery design, and employer-aligned implementation planning.