Understand the importance of data network effects in your AI strategy

About

When building an AI strategy, you cannot rely only on algorithms. A solid AI strategy is primarily based on data. This training will help you understand data in winning AI strategies and in the creation of new competitive advantages.

Objectives

In the age of AI-driven organizations, successful B2C products often have one thing in common: The importance of data. In this training, we will help you build winning data-driven strategies for your products as well as understand how to create successful AI business models.

Content


1. What are data network effects?

- What is data moat

- Data culture & expectations

- Importance of building strong data acquisition processes

- Relationship with data & Closed Loop System

- Improvements in AI accuracy vs Time

- Types of Data you could collect

- AI Learning Curves

2. Importance of Data Strategy

- Creating new AI business models

- How to build bridges between technologies (AIoT)

- Improvement of AI strategies

- How to increase the data value of your organization

- Introduction to Synthetic Data

- Small Data and Dataset

3. Use cases

- Use case #1 : Amazon ecosystem

- Use case #2 : Xiaomi AIoT Strategy

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Basic Training: 2 to 3 hoursAdvanced Training: Basic Training + 3 hours of uses cases
French / English
Basic Training - starting from 70€ to 200€ (per participant)
Advanced Training - on demand
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