Deploying Machine Learning on Cloud requires more than just code—it demands clean, organized, and scalable project structures. In this Masterclass, learn how to organize your Data Science & ML projects in PyCharm like a pro.
From managing datasets and scripts to virtual environments, Git integration, and modular pipelines, this session helps you build ML workflows that are collaborative, easy to debug, and deployment-ready. Perfect for beginners and intermediate learners exploring real-world data science practices.
📌 What You’ll Learn 1️⃣ Structuring Your Project Folder 2️⃣ Managing Virtual Environments 3️⃣ Naming Conventions & File Management 4️⃣ Using Git & Version Control in PyCharm
💡 Why it matters: Well-structured projects make ML deployment on Cloud faster, more reliable, and industry-ready.
🚀 Take the Next Step in Your Career Imarticus Learning’s programs are designed to help you turn skills into high-paying roles in Data Science & AI:
🎓 Postgraduate Program in Data Science and Analytics (PGA) – 6 months, 100% job assurance, 2,000+ hiring partners, 25+ projects, Python, Power BI, Tableau.
🎓 Executive Post Graduate Program in Data Science & AI (EPGP-DSAI) – 11 months, for professionals, 2,500+ hiring partners, 35+ projects, career transitions with avg. 52% salary hike.
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