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Practical deep dives on LLMs, RAG, agents, MLOps, AutoML, data systems, and Python for production ML.

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Structured Data Extraction from Text with LLMs
LLMs & Agents
New
Structured Data Extraction from Text with LLMs
Jun 2026

Use Python, Pydantic, and the Instructor library to extract structured data from unstructured text. Parse invoices and job postings into typed, validated Python objects — reliably and at scale.

Python
LLMs
Pydantic
AI Agents with LangGraph for Data Analysis
LLMs & Agents
New
AI Agents with LangGraph for Data Analysis
Jun 2026

Build an autonomous data analysis agent using LangGraph. Learn how agents differ from RAG, and implement the ReAct loop with tools for querying and summarizing data.

LangGraph
LangChain
Python
Orchestrate ML Pipelines with Prefect
MLOps
New
Orchestrate ML Pipelines with Prefect
Jun 2026

Go from fragile training scripts to robust, observable ML workflows using Prefect. Schedule retraining, handle failures gracefully, and monitor every run.

Prefect
Python
MLOps
ML Model Monitoring in Production with Evidently
MLOps
New
ML Model Monitoring in Production with Evidently
Jun 2026

Learn how to detect data drift and model degradation in production using Evidently AI. Build automated reports and alerts before your model silently fails.

Evidently
Python
MLOps
Your First Machine Learning Model with Scikit-learn
Machine Learning
New
Your First Machine Learning Model with Scikit-learn
May 2026

A step-by-step guide to building your first ML model: data exploration, preprocessing, cross-validation, hyperparameter tuning, and evaluation — all with scikit-learn.

Python
scikit-learn
machine learning
Operations Research
Operations Research
How to Solve Scheduling Problems in Python
May 2026

Use pyworkforce to assign work shifts and minimize the gap between required and scheduled resources, with built-in support for preferences, banned shifts, and rest rules.

Python
pyworkforce
scheduling
Building an AI or data platform?

Products, platforms, and open-source software for AI, Data Engineering, and Machine Learning.

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Building an ecosystem of products and open-source software for AI, Data Engineering, and Machine Learning.

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