Introduction in datascience and AI - Amsterdam Data Academy

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Welcome to the this learning module about the the most important concepts of datascience and AI. If you have any questions about this course, please get in contact with our customer service.

Course Content

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Introduction in datascience and AI – Course introduction Sample Lesson

Module 1: Key concepts 12 Topics | 1 Quiz

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Lesson Content

0% Complete 0/12 Steps

Module 1: What is the difference between datascience, AI and analytics – Video 1

Module 1: What is the difference between datascience, AI and analytics – Video 2

Module 1: What is the difference between datascience, AI and analytics – Video 3

Module 1: What is the difference between datascience, AI and analytics – Video 4

Module 1: What is the difference between datascience, AI and analytics – Video 5

Module 1: What is the difference between datascience, AI and analytics – Video 6

Module 1: What is the difference between datascience, AI and analytics – Video 7

Module 1: What is the difference between datascience, AI and analytics – Video 8

Module 1: What is the difference between datascience, AI and analytics – Video 9

Module 1: What is the difference between datascience, AI and analytics – Video 10

The theory behind Machine Learning

The applications of Machine Learning

Module 1: What is the difference between datascience, AI and analytics – Quiz

Live session 1: Kick-off & introduction

Module 2: Use cases of datascience and AI 7 Topics | 1 Quiz

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Lesson Content

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Recommendations engines

Churn modeling

Media mix modeling

Assignment 1 installation & tutorial

Download data files

Assignment Churn case

Assignment MMM case

Quiz: Machine Learning

Live session 2: Homework feedback

Module 3: Case study 2 Topics

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Final Assignment

Upload case result

Live session 3: Presentation time