Getting started also requires an understanding of your business, an appreciation for using data in a decision-making and a framework of what advantages using A.I. can offer.

For many businesses, there are three things that cause us all pain, that A.I. can help us with Dirty Data, Manual Processes and Outdated Information. 

To address these pain points, we will break down an A.I. framework we can use in our business into the following sections.

Section 1 – Good Data Governance requires us to collect, store, access, and analyze our data in an orderly way. Additionally, A.I. is not standalone software. A.I. is designed to be used as part of a well-organized system; to accomplish a set of tasks using algorithms. This allows us to use A.I. in three different areas of our business processes.

 Data is the currency of an A.I. driven organization.

 A.I. Process #1 - Augmentation

 A.I. Process #2 - Automation

 A.I. Process #3 - Machine Learning

Section 2 – Business Intelligence - A simple conversation about the data collected in a business, how it is stored and accessed, what can be done with it will lead you towards A.I. Demonstrate the ability to ride the A.I. wave, rather than be rolled over by it, which all starts with augmenting your data analytics.

Section 3 – Process Automation - Sometimes the most powerful function of A.I. in a business is simply automation. We have to be able to either delegate, outsource or automate every part of our business that is manual, human resource-heavy and/or repetitive. Automation saves time and money, but of course, can come at a human cost.

Section 4 – Influencing Customer Behaviour – Machine Learning involves building mathematical models that A.I. will use for predictive data analytics and for learning. We then merry ML with Data Storytelling to craft narratives that drive the desired outcome from our customers.

Participants will have a deeper understanding of A.I. terminology, including Big Data Analytics, Deep Learning, Natural Language Processing, Neural Networks, Predictive Modelling and Supervised Learning.

The end results of attending the one-day training will include the following:

1. An Assessment of your Current Analytics Maturity & a Plan to Level Up

2. A Map of your Data Lake, including Identified Data Silos

3. Learning about the Data Families/Skills Need for A.I.

4. A list of what manual processes you can Automate (Collection, Blending, Modelling, Analysis)

5. Tips on how to enhance your Data Visualization & Data Storytelling skills

6. Identify the Key Customer Behaviour Influencers you need to maximize business profits.

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