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PyTorch, Shiny, Pandas & More-Build Interactive Data Science

Master Python Data Science by Creating Interactive Apps with Shiny, PyTorch, Pandas, Seaborn & Matplotlib

PyTorch, Shiny, Pandas & More-Build Interactive Data Science

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Description
Unlock the power of interactive data science with Interactive Data Science in Python — a comprehensive, beginner-friendly course designed to take you from novice to confident practitioner. We begin by exploring Shiny, the dynamic and popular web app framework for Python, where you'll learn how to build interactive dashboards, responsive data visualizations, and user-friendly interfaces using the classic Shiny library. Once you’ve gained solid skills, you’ll transition smoothly to Shiny Express, a modern, more streamlined toolkit that accelerates app development while maintaining full flexibility.

Alongside Shiny, you’ll dive deep into essential Python data science libraries like Pandas, Seaborn, and Matplotlib. You’ll master how to clean, analyze, visualize, and explore complex datasets with clarity and precision, empowering you to uncover patterns and tell compelling stories with data.

This course also introduces PyTorch basics from scratch — perfect for beginners eager to explore deep learning and neural networks. You’ll grasp fundamental machine learning concepts and get hands-on experience building your own models, preparing you to confidently tackle more advanced AI projects.

Throughout the course, you’ll engage with practical coding exercises, real-world datasets, and projects focused on creating interactive applications that captivate users and dynamically reveal insights. Whether you aspire to be a data scientist, analyst, or developer, this course will equip you with the skills and confidence to build powerful data-driven applications and understand foundational deep learning techniques in Python.

Jump in today and bring your data to life with interactive, intelligent applications!

Who this course is for:
  • Those who prefer learning through building interactive applications rather than theory alone.
  • Aspiring data scientists, analysts, and developers looking to build dynamic dashboards and web apps with Shiny.
  • Anyone interested in learning PyTorch basics
  • Beginners and intermediate Python users who want to dive into interactive data science and visualization.

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