Build a successful Data Science and AI practice in 7 steps

Congratulations on starting your own Data Science and AI practice, that’s a move that will help you have an impact on your organization.

But starting an AI practice is hard and not always clear. You will need the proper tools and support to reach your objectives.

Our 7-step framework is based on our long experience in the field working with several customers across multiple industries. In this framework, you will learn how to identify your organization weaknesses when it comes to data, identify projects with high value, prioritize them, scope a project and so on.

Introduction

Introduction

Step 1
Assess your level of maturity in data valuation
Step 2
Identify projects with high value to your organisation
Step 3
Define the feasibility of a Machine Learning project


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Step 4
Prioritize Machine Learning projects framework


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Step 5
Scope a project


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Step 6
Necessary profiles to build your team


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Step 7
Key to success in implementing a data science practice


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Step 8
Next Steps

Next Steps

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