19. smart
In 1960 beschikte 10% van de Nederlandse
huishoudens over een koelkast.
De prijzen lagen op dat moment rond de 500 tot
700 gulden, afhankelijk van de literinhoud.
Het Zaanse levensmiddelenbedrijf bestelde in
1962 20.000 koelkasten tegen kwantumkorting
bij de Duitse fabrikant Liebherr.
Albert Heijn verkocht deze apparaten tegen de
helft van de winkelprijs.
binnen een maand was de hele partij verkocht.
20. smart 3 of 6 maanden Datascience & AI opleiding
Start elke 3 maanden vanaf 1/10/2018
http://www.futureskillslab.nl/
37. Monday Tuesday Wednesday Thursday Friday Legenda
Date Focus area Class / 09:00 - 17:00 Online / 09:00 - 17:00 Online / 09:00 - 17:00 Class / 09:00 - 17:00
Class / 09:00 -
17:00
Coach
Before the course
starts
Pre: Get started with Data Science Introduction to Data Science Introduction to Data Science Introduction to Data Science Introduction to Data Science
Introduction to
Data Science
In house
Week 1: Analyze and Visualize Data Soft skills (Barbara) Soft skills (Hasan)
Analyze and Visualize Data with
Excel / Analyze and Visualize Data
with PowerBI
Analyze and Visualize Data with Excel /
Analyze and Visualize Data with PowerBI
Garage day Work at home
Week 2: Communicate Data Insights
Analyze and Visualize Data with Excel
/ Analyze and Visualize Data with
PowerBI
Analytics Storytelling for Impact Analytics Storytelling for Impact Analytics Storytelling for Impact Garage day
Week 3: Ethics and Law in Data and Analytics Soft skills (Barbara) Ethics and Law in Data and Analytics Ethics and Law in Data and Analytics Ethics and Law in Data and Analytics Garage day
Week 4: Query Relational Data Querying Data with Transact-SQL Querying Data with Transact-SQL Querying Data with Transact-SQL Querying Data with Transact-SQL Garage day
Week 5: Explore Data with Code
Introduction to R for Data Science /
Introduction to Python for Data
Science
Introduction to R for Data Science /
Introduction to Python for Data Science
Introduction to R for Data Science /
Introduction to Python for Data
Science
Introduction to R for Data Science /
Introduction to Python for Data Science
Garage day
Week 6: Essential Maths Soft skills (Barbara)
Essential Math for Machine Learning: R /
Python Edition
Essential Math for Machine Learning:
R / Python Edition
Essential Math for Machine Learning: R /
Python Edition
Garage day
Week 7: cont’d
Essential Math for Machine Learning:
R / Python Edition
Essential Math for Machine Learning: R /
Python Edition
Essential Math for Machine Learning:
R / Python Edition
Essential Math for Machine Learning: R /
Python Edition
Garage day
Week 8: Plan and Conduct Data Studies Soft skills (Barbara)
Data Science Research Methods: R /
Python Edition
Data Science Research Methods: R /
Python Edition
Data Science Research Methods: R /
Python Edition
Garage day
Week 9: Build Machine Learning Models
Data Science Research Methods: R /
Python Edition
Principles of Machine Learning: R /
Python Edition
Principles of Machine Learning: R /
Python Edition
Principles of Machine Learning: R /
Python Edition
Garage day
(enroll for
capstone)
Week 10: cont’d
Principles of Machine Learning: R /
Python Edition
Principles of Machine Learning: R /
Python Edition
Principles of Machine Learning: R /
Python Edition
Principles of Machine Learning: R / Python
Edition
Garage day (work
on capstone)
Week 11: Build Predictive Solutions at Scale Soft skills (Barbara)
Predictive Analytics with Spark in Azure /
Analyze Big Data with Microsoft R /
Developing Big Data Solutions with Azure
Machine Learning
Predictive Analytics with Spark in
Azure / Analyze Big Data with
Microsoft R / Developing Big Data
Solutions with Azure Machine
Learning
Predictive Analytics with Spark in Azure /
Analyze Big Data with Microsoft R /
Developing Big Data Solutions with Azure
Machine Learning
Garage day (work
on capstone)
Week 12: Build Predictive Solutions at Scale Capstone Capstone Capstone Capstone Garage day
Requirements:
- Windows OS
- Windows Live ID
- O365 account
- Azure tenant (trial)
Full-time program – 3 months
38. Monday Tuesday Wednesday Thursday Friday
Date Focus area Online / 09:00 - 17:00 Online / 09:00 - 17:00 Online / 09:00 - 17:00 Class / 09:00 - 17:00 Class / 09:00 - 17:00
Week 1-2: Get started with Data Science Introduction to Data Science Introduction to Data Science
Week 3-4: Analyze and Visualize Data
Analyze and Visualize Data with Excel / Analyze and
Visualize Data with PowerBI
Analyze and Visualize Data with Excel /
Analyze and Visualize Data with PowerBI
Week 5-6: Communicate Data Insights Analytics Storytelling for Impact Analytics Storytelling for Impact
Week 7-8: Ethics and Law in Data and Analytics Ethics and Law in Data and Analytics Ethics and Law in Data and Analytics
Week 9-10: Query Relational Data Querying Data with Transact-SQL Querying Data with Transact-SQL
Week 11-12: Explore Data with Code
Introduction to R for Data Science / Introduction to
Python for Data Science
Introduction to R for Data Science /
Introduction to Python for Data Science
Week 13-16: Essential Maths
Essential Math for Machine Learning: R / Python
Edition
Essential Math for Machine Learning: R /
Python Edition
Week 17-18: Plan and Conduct Data Studies Data Science Research Methods: R / Python Edition
Data Science Research Methods: R / Python
Edition
Week 19-22: Build Machine Learning Models Principles of Machine Learning: R / Python Edition
Principles of Machine Learning: R / Python
Edition
Week 23-24: Build Predictive Solutions at Scale
Predictive Analytics with Spark in Azure / Analyze Big
Data with Microsoft R / Developing Big Data Solutions
with Azure Machine Learning
Predictive Analytics with Spark in Azure /
Analyze Big Data with Microsoft R /
Developing Big Data Solutions with Azure
Machine Learning
Week 25-26: Capstone (depending on starting
moment -> 4 times a year)
Capstone Capstone
Requirements:
- Windows OS
- Windows Live ID
- O365 account
- Azure tenant (trial)
Part-time program – 6 months
Optional: soft skills workshops