Generative AI systems
AI customer segmentation agents, AI time-series forecasting agents, and SQL-writing BI agents with Python, LangGraph, and LangChain.
Move fromdata sciencetools to AI/MLarchitecture depth.
A practical campaign page for professionals who want hands-on projects across Python, R, forecasting, customer analytics, AI agents, MLOps, and business applications.
- 80+
- labs in the vault
- 1x
- new lab each month
- $99.99
- monthly option shown
AI agentsPython, LangGraph, LangChain
ForecastingARIMA, Nixtla, Modeltime
Business MLCLV, churn, pricing, MMM
ProductionDash, Shiny, APIs, MLOps
Built from the source offer.
Business Science describes Learning Labs Pro as 1-hour data science projects released monthly, with live coding and demonstrations across intermediate and advanced R and Python topics.
Project library
Use the vault to build an architecture-level skill stack.
Based on the source page, these are the ten strongest labs to lead the sales story: AI agents, forecasting, marketing analytics, causal ML, app delivery, and production automation.
01 / 10
AI Customer Segmentation Agent with Python
A LangGraph and LangChain project that turns customer analytics into an agent workflow for segmentation and decision support.
- Generative AI
- Python
- Customer analytics
Forecasting and analytics
Machine learning forecasting, ARIMA, macroeconomic analysis, cashflow forecasting, modeltime, Nixtla, Polars, and PyMC marketing.
Business applications
Customer lifetime value, marketing mix modeling, price optimization, customer segmentation, churn, A/B testing, and attribution.
Production data science
ETL automation, MLOps, Docker, MLFlow, APIs, Targets, Shiny, Dash, and production-ready app patterns for data teams.
Why this angle sells
People do not just need tutorials. They need project depth.
The content should position Learning Labs Pro as a lower-cost, continuous learning path for people who already know the basics and need applied project judgment: architecting data products, choosing models, automating workflows, and shipping business-facing AI/ML work.
- Short enough to complete beside work.
- Deep enough to support portfolio and client conversations.
- Broad enough to connect data engineering, analytics, ML, AI apps, and deployment.
Registrant capture
Start with your goal, then continue to secure checkout.
Register your interest in Learning Labs Pro and tell us what you want to build next. The labs are designed for practical depth across AI agents, forecasting, analytics, MLOps, Shiny, Dash, R, and Python.