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via Udemy |
Go to Course: https://www.udemy.com/course/streamlit-for-snowflake/
Certainly! Here's a comprehensive review and recommendation for the course on Coursera: --- **Course Review: Mastering Streamlit & Snowflake Integration with an Industry Expert** As someone who values practical, industry-relevant training, I highly recommend this course for data professionals, developers, and data enthusiasts eager to enhance their skills in building, deploying, and managing data-driven web applications using Streamlit and Snowflake. **Why You Can Trust the Instructor:** The instructor is a recognized Snowflake expert in Canada, chosen for the esteemed Data Superhero program, and a former SnowPro Certification SME. With four SnowPro certifications and dozens of other certifications in Data Science, Machine Learning, and Cloud architectures, they bring a wealth of real-world experience. They’ve worked extensively with clients, designing innovative apps and solutions with Snowflake and Streamlit, which adds credibility and practical insights to this course. **What You Will Learn:** This course offers a comprehensive journey, starting with the fundamentals of creating interactive web apps with Streamlit, deploying them on community cloud, and connecting seamlessly to Snowflake using various methods such as Snowflake’s Python Connector and Snowpark. Key skills include: - Building both simple and complex web applications - Connecting and integrating Snowflake data with Streamlit apps - Using DataFrame API, stored procedures, and hierarchical viewers within Snowflake - Prototyping data science, machine learning, and data analysis scenarios - Deploying these apps as native Snowflake or Streamlit apps, sharing with teams and clients The first half is an intensive Streamlit bootcamp covering all core features like widgets, layout, themes, and session management. The latter half dives into Snowflake-centric development, including native app framework, Snowpark for Python, and advanced integrations like ChatGPT and visualization tools. **Real-Life Application Focus:** One of the highlights is the practical projects—building hierarchical data viewers, metadata viewers, ER diagrams, chatbots, and dashboards with advanced visualizations like Vega-Lite, Altair, and Plotly. These projects are designed to reflect real-world client needs, providing you with tangible skills that can be directly applied in professional scenarios. **What’s Not Included:** This course doesn’t focus on deep Snowflake internals, advanced data science, or programming beyond Python and SQL. It’s primarily focused on application development and deployment, making it ideal for those looking to build and deploy impactful data apps quickly. **Should You Enroll?** Absolutely. If you're interested in bridging data science with application deployment on Snowflake, or want to develop interactive dashboards and apps that leverage Snowflake’s platform, this course is invaluable. The instructor’s extensive industry experience and practical projects make it different from theoretical courses—it's rooted in what works in the real world. **Final Verdict:** This course is a must-attend for data professionals who want to skill up in building integrated, deployable web apps with Streamlit and Snowflake. Whether you're looking to streamline your data workflows, create client-facing dashboards, or prototype innovative data solutions, this course provides the tools and knowledge to do so effectively. --- Feel free to reach out if you'd like a shorter summary or specific details!
Why You Can Trust MeI was the only Snowflake technical expert from Canada selected for their Data Superhero program in Jan 2022.Former SnowPro Certification SME (Subject Matter Expert) - many exam questions have been created by me.Passed four SnowPro certification exams to date (with no retakes): Core, Architect, Data Engineer, Data Analyst.Dozens of other certifications in Data Science and Machine Learning, Cloud Solution Architectures, Databases, etc.Dozens of apps designed and implemented with Streamlit and Snowflake on my blog on Medium.Specialized in Snowflake for several years, I served dozens of clients and implemented many real-life projects.What You Will LearnHow to create simple to complex web applications in Streamlit.How to deploy for free local Streamlit web apps to the Streamlit Community Cloud.How to connect to Snowflake from Streamlit apps, through either the Python Connector or a Snowpark session.How to use the DataFrame API and push Python code as stored procedure with Snowpark.How to extend Snowflake's capabilities, with a hierarchical data viewer and a hierarchical metadata viewer.How to prototype with Streamlit apps data science, machine learning and data analysis scenarios.How to deploy a Streamlit web app as a Streamlit in Snowflake App.How to deploy a Streamlit web app as a Snowflake Native App.How to use the Snowflake Native App Framework to build or use apps with Streamlit.We'll build several apps in Python from scratch, we'll then convert them to local single or multi-page Streamlit web apps, deploy and share them on the Streamlit Community Cloud, deploy them in Snowflake as stored procs or Streamlit Apps, share them as Native Apps with other Snowflake accounts...What Streamlit Areas You Will Learn AboutInput and Output Controls (Interactive Widgets, Display Text controls, etc.).Layout Components (sidebar, container, expander, tabs, etc.) and Forms.Events and Page Reruns.Data Caching, Session State and Callbacks.Theming and Configuration, TOML Secrets.First half of the course will be an end-to-end complete Streamlit bootcamp, with everything you need to know about Streamlit.What Snowflake Areas You Will Learn AboutCreating a free Snowflake account and using the Snowflake web UI at the basic level.Connecting to Snowflake with SnowSQL, and executing SQL scripts with this command-line interface.Connecting to Snowflake with the Snowflake Connector for Python.Connecting to Snowflake with Snowpark for Python.Using Snowpark to push Python code as stored procedures.Using Snowpark to generate SQL queries with the DataFrame API.Writing and deploying Streamlit in Snowflake Apps.Writing and deploying Snowflake Native Apps, with the Snowflake Native App Framework.Integrating Snowflake with ChatGPT, external dashboards, data science and machine learning libraries.Second half of the course will be all about Snowflake client apps, Snowpark, Streamlit in Snowflake Apps and Native Apps.What is NOT Included in This CourseIn-depth knowledge of Snowflake.In-depth data science, data analytics and machine learning.Programming in languages other than Python and SQL.Main focus will be on all sorts of applications in Python using Streamlit, to connect and deploy the code to Streamlit Cloud or Snowflake in all possible ways.Real-Life Applications You Will Learn To BuildHierarchical Data Viewer, for CSV files and Snowflake tabular data, using JSON, graphs, animations, recursive queries.Hierarchical Metadata Viewer, for Snowflake object dependencies and data lineage.Entity-Relationship Diagram Viewer for Snowflake.Chatbot Agent with OpenAI's ChatGPT, used as a SQL query generator for Snowflake Marketplace datasets.Dashboards for Snowflake data, with Vega-Lite, Altair and Plotly charts.Machine Learning scenarios, with Model Training and Predictions.Data enrichment of IP addresses using external free services.I sold tools similar to many of these to real-life clients and Snowflake partners!Enroll today, to keep this course forever!