by World-Class Snowflake Expert, former Data Superhero and SnowPro Certification SME

What you'll learn

Build, debug and deploy data-driven applications with Streamlit

Deploy Streamlit web apps into Snowflake, as Streamlit in Snowflake Apps

Share and deploy Streamlit web apps as Snowflake Native Apps

Deploy Python code with Snowpark as Snowflake stored procedures and UDFs

Connect to Snowflake from a Streamlit web application

Build real-life applications with Streamlit and Snowflake

Design and deploy to Snowflake data science, data analysis and ML apps with Streamlit

Process and access hierarchical data and metadata in Snowflake

Requirements

Basic knowledge of SQL and relational databases

Basic knowledge of Python programming

No prior knowledge of Streamlit or Snowflake is expected

Basic knowledge of working with a version-control code repository such as GitHub

No prior knowledge of data science, data analytics or machine learning is expected

Description

Why You Can Trust MeI was the only Snowflake technical expert from Canada selected for their Data Superhero program in 2021.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!