Advanced Tools for Interactive Data Science
( 30 Modules )

Module #1
Introduction to Interactive Data Science
Overview of the importance of interactive data science and its applications

Module #2
Data Science Workflow
Understanding the data science workflow and the role of interactive tools

Module #3
Interactive Visualization
Introduction to interactive visualization and its importance in data science

Module #4
Tools for Interactive Data Science
Overview of popular tools for interactive data science (Python, R, JavaScript)

Module #5
Setting up your Environment
Installing and setting up necessary tools and libraries for interactive data science

Module #6
Introduction to Bokeh
Creating interactive visualizations with Bokeh in Python

Module #7
Advanced Bokeh Techniques
Using Bokehs advanced features for interactive visualization

Module #8
Introduction to Plotly
Creating interactive visualizations with Plotly in Python

Module #9
Advanced Plotly Techniques
Using Plotlys advanced features for interactive visualization

Module #10
Comparing Bokeh and Plotly
Choosing the right tool for your interactive visualization needs

Module #11
Introduction to Interactive Machine Learning
Overview of interactive machine learning and its applications

Module #12
TensorFlow.js for Interactive ML
Using TensorFlow.js for interactive machine learning in the browser

Module #13
PyTorch for Interactive ML
Using PyTorch for interactive machine learning in Python

Module #14
Rapid Prototyping with H2O.ai
Using H2O.ais rapid prototyping tools for interactive machine learning

Module #15
Deploying Interactive ML Models
Deploying interactive machine learning models to the web and mobile devices

Module #16
Introduction to Dash and Flask
Building web applications with Dash and Flask for interactive data science

Module #17
Building Interactive Dashboards
Creating interactive dashboards with Dash and Python

Module #18
Introduction to R Shiny
Building web applications with R Shiny for interactive data science

Module #19
Building Interactive R Shiny Apps
Creating interactive applications with R Shiny

Module #20
Comparing Dash and R Shiny
Choosing the right tool for your interactive data science needs

Module #21
Interactive Data Storytelling
Using interactive tools to tell data-driven stories

Module #22
Collaborative Data Science
Using interactive tools for collaborative data science

Module #23
Ethics in Interactive Data Science
Considering ethical implications of interactive data science

Module #24
Deploying Interactive Data Science Apps
Deploying interactive data science applications to the cloud and mobile devices

Module #25
Advanced Topics in Interactive Visualization
Exploring advanced topics in interactive visualization (AR, VR, 3D)

Module #26
Final Project Overview
Introduction to the final project and expectations

Module #27
Working on Your Final Project
Guided lab time to work on your final project

Module #28
Final Project Presentations
Presenting your final project to the class

Module #29
Conclusion and Next Steps
Conclusion of the course and next steps for continued learning

Module #30
Course Wrap-Up & Conclusion
Planning next steps in Advanced Tools for Interactive Data Science career

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Advanced Tools for Interactive Data Science ( 30 Modules )

Advanced Tools for Interactive Data Science
( 30 Modules )