Build and deploy real AI Applications from Week 1
Graduate with a production-ready projects and a portfolio for employers
Learn live alongside a cohort of other builders
Only 20 seats available. Applications close May 21 or when full.
20 Spots Available
Entrepreneurial builders
You have ideas for products or tools, but need the skills to bring them to life
Turn your ideas into real, working AI applications you can launch, test, and iterate on without relying on others.
Executives, operators & upskillers
You want to automate workflows, build internal tools, and create leverage in your role
Build custom AI solutions that save time, increase output, and make you exponentially more valuable at work.
Career switchers & job seekers
You need real projects and a portfolio that proves you can build, not just a certificate
Graduate with deployed projects and a clear “I built this” story that stands out to employers immediately.
Industry Partners
Live, Instructor-Led Sessions
10 weeks of live learning with industry professionals — interactive format for questions and personalized feedback.
2 live sessions per week
Production-Ready Portfolio
Build and deploy multiple AI applications over 10 weeks. Walk away with real projects you can demo to employers, backed by a university digital badge.
3 deployable apps
Peer Cohort Community
Get built-in accountability, peer code review, and a network you can keep building with long after the program ends.
Max 20 students per cohort
University Digital Badge
Earn a recognized credential upon completion. Add it to your LinkedIn profile and share with employers as verified proof of your AI & ML experience.
Employer-recognized credential
Trusted by 1,800+ Circuit Stream students globally
This course focuses on practical AI and machine learning skills you can apply immediately through hands-on projects and guided instruction. You’ll build real AI systems, from recommendation engines to RAG‑powered applications, using the same tools and workflows used in industry today.
Trusted by 1,800+ Circuit Stream students globally
Python
Learn Python for AI, data engineering with Pandas and NumPy, and classical machine learning techniques.
Deep Learning
Implement neural networks, embeddings, tokenization, and multimodal models to work with images, text, and combined data sources.
RAG Systems
Build product-ready AI applications using vector databases, semantic search, and retrieval‑augmented generation (RAG).
Capstone Project
Graduate with a deployed, portfolio‑ready AI web app that demonstrates end‑to‑end system design.
What we'll cover
~30 min
1
Your goals
Career direction and lifestyle fit
2
Your options
Program paths and honest trade-offs
3
Your plan
Clear next steps, yours to keep
Every skill you learn, you'll apply to a real project. No abstract theory. No tool you won't use.
Build AI Applications with Python. Write clean, production-quality Python for machine learning and AI development — the language of the industry.
Design & Train Machine Learning Models. Build, tune, and evaluate ML models for real-world prediction and classification tasks — not just theory.
Work with Neural Networks & Deep Learning. Understand and implement deep learning architectures — CNNs, RNNs, transformers — for complex real-world Al tasks.
Build with LLMS, RAG & Al Agent Frameworks. Build LLM-powered applications using LangChain, OpenAl API, and modern Al agent tooling used in production today.
Engineer & Process Production Data. Clean, transform, and pipeline real-world datasets — the unglamorous skill that separates working engineers from hobbyists.
Deploy Al Systems to Production. Package and ship Al systems to real environments — not just a Jupyter notebook on your laptop. Your portfolio runs live.
Claude
OpenAI
Gemini
Streamlit
PyTorch
VS Code
Jupyter
Python
GitHub
Jupyter
NumPy
Pandas
Python
Increase in job postings for AI engineers over the past two years.
Lightcast AI Job Market Report
Salary premium for roles requiring AI skills — roughly $18k more per year.
Lightcast AI Job Market Report
125%
Average job posting increase for AI/ML — leading all skill categories.
SHRM 2026 Labor Demand Review
Your Employer May Cover This
Many companies offer professional development budgets — and this program qualifies for education reimbursement at most organizations. We make it easy to make the case to your manager.
Download a pre-written employer letter template explaining the program and its business value — ready to send to your manager or HR.
Request a formal invoice in the format your employer's finance team needs — we handle the paperwork.
Ask about team enrollment rates for groups of 3 or more — we offer volume pricing for corporate cohorts.
Join the companies already upskilling their teams with Circuit Stream from startups to enterprise.
Employer Letter Template
PDF • Ready to customize • 1 page
CS
September 2026
Program Director, Circuit Stream
28%
of students used employer funding
$2,500
typical L&D budget per employee
48h
avg. manager approval time
TEAM RATES
Explore the financial assistance options available to help fund your learning — or book a consultation for personalized guidance.
Recognized Funding Partners
Download The Program Outline
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Frequently Asked Questions
Got more questions? Chat with our team
Do I need coding experience?
Is this live or self-paced?
What will I have at the end?
Will I learn machine learning or just ChatGPT stuff?
What’s the time commitment?
I’m not trying to be an ML engineer. Is this still useful?
When are the next cohorts?