Build and Deploy Projects with Streamlit Cloud
Hosted by Siddarth Ranganathan
What you'll learn
Best Practices and Setting up
Learn the essential tips and techniques for seamless and effective cloud deployment.
Deploy End-to-End Data Science Projects
Master the process of turning your models into fully functional, cloud-hosted applications.
Showcasing Your Work
Understand how to share your deployed projects and build a professional portfolio that stands out.
Why this topic matters
Deploying projects in the cloud is crucial for Data Scientists to build a strong portfolio. It enables them to showcase work as interactive, accessible applications for stakeholders and recruiters. By bridging the gap between model development and real-world usability, cloud deployment highlights their ability to deliver end-to-end solutions, enhancing professional credibility.
You'll learn from
Siddarth Ranganathan
Principal Data Science Manager at Microsoft
Siddarth brings 20 years of experience spanning Healthcare, eCommerce, and Tech. He currently leads a team of 20 data scientists and engineers, driving high-impact initiatives for Azure, delivering scalable solutions and measurable outcomes.
Go deeper with a course
AI-ML Projects for Data Professionals
Manisha Arora and Siddarth Ranganathan
Data Science Lead, Google | Founder, PrepVector |
MIT, UT Austin & Univ of Cincinnati. Director of Data Science, Microsoft | Founder, PrepVector | USC Marshall
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