jpmorganchase/python-training

Dash is Plotly's open-source Python framework for turning data-science code into web apps, pairing Python callbacks with Plotly.js charts and a React frontend on top of a Flask server. It's aimed at people who already work in pandas and Plotly and want a real, interactive UI around that work without adding a JavaScript build step to their workflow.

Apache Superset is a self-hosted, open source platform for exploring data and building dashboards, pairing a no-code chart builder with a full SQL Editor and a semantic layer for reusable metrics.

30 Days Of Python is a free GitHub curriculum by Asabeneh Yetayeh that breaks Python into 30 daily topics, from syntax basics through web scraping, MongoDB, and building an API. The README pitches it at beginners and working professionals, admits the timeline realistically runs past 100 days, and points to a Telegram group and companion YouTube channel for support.

scikit-learn is an open-source Python module for machine learning at scikit-learn/scikit-learn, layered on top of SciPy and covering classification, regression, clustering, and dimensionality reduction. The project traces back to a 2007 Google Summer of Code effort by David Cournapeau, was known early on as scikits.learn, and is now kept up by a volunteer community with backing from several organizations, distributed under the BSD-3-Clause license.