APOGEE UNIVERSITY
Welcome to the ApogeePlex Synergy Zone! We are excited to introduce you to Data Visualization and Machine Learning.
In the next few days we will teach you how Tableau Software can help turn your mucho data into cool viz's & trusted knowledge and why all the hype around Machine Learning is real!
Administrivia
- Review and Submit the APOGEE University Enrollment Form
- Review and Agree to Comply with the APOGEE IT & Electronics Communications Policy
- Please Input and Submit the APOGEE University - Training Survey
Data Visualization Training
Tableau Essentials (DSV-101/102)
Course(s) Summary:
A 2 day hands-on, class room course that teaches students data visualization techniques and the application of best practices.
Day 1: Tableau Essentials 1: Emerging Data Viz students will learn, interact with datasets and apply techniques using Tableau Software.
Day 2: Tableau Essentials 2: Students apply more advanced data concepts and viz techniques to make compelling charts and dashboards!
You'll soon have all the tools to make compelling charts and dashboards and be ready to pass and certify your Tableau expertise:
Tableau Desktop Specialist Tableau Desktop Certified Associate.
Below please find the meaningful links for the day. If you have any questions please don’t hesitate reach out to any APOGEE-nius for help!
Exercises & Instructions:
TABLEAU ESSENTIALS I (AU-DSV101)
- Exercise 1 - SIMPSONS Part 1
- Exercise 2 - SIMPSONS Part 2
- Exercise 3 - Airbnb
- Exercise 4 - UK Car Accidents
- Exercise 5 - Global Terrorism: Dual Axis Map
- Exercise 6 - Creating Dashboards
TABLEAU ESSENTIALS II (AU-DSV102)
- Exercise 7 - Mililtary Spending Waffles
- Exercise 8 - Boston Homes
- Exercise 9 - Arms Traffic
- Exercise 10 - Global Terrorism: Time Based Data
- Exercise 11 - Crimean Ship Paths
- Exercise 12 - Twitter HeatMap
- Exercise 13 - Global Terrorism: Filter Actions
Machine Learning Training
Intro to Machine Learning (AU-DSM101)
- Exercise 1 - Regression Techniques
- Exercise 2 - Dimensionality and Overfitting
- Exercise 3 - Probabilistic Learning
- Exercise 4 - Neural Networks
- Exercise 5 - Deep Learning and Hardware
- Exercise 6 - Unsupervised Learning