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Upcoming Events

Join our webinars and live training sessions to learn how to build a data-driven organization. Even if you can’t attend live, we encourage you to register to receive a link to the on-demand recording.

For previously recorded webinars, view our on-demand webinars.

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Live Training

Analyzing Ticket Sales Data with Amazon Redshift

In this live training, we’ll be analyzing ticket sales data through Amazon Redshift, a data warehouse product that is part of Amazon Web Services. Even though Redshift’s underlying technology is vastly different from classical relational databases, we can also run queries using SQL. Using DataCamp Workspace, we will connect to a redshift cluster and start with some initial exploration of the data. Next, we move on to answering increasingly complex analytics questions using common techniques like joining, grouping, and aggregating the data. To top it all off, we will create an insightful visualization that shows the highest-grossing events in the dataset. Filip will provide a template workspace for you so you can easily follow along as he’s coding up the model.

Thursday, June 30th, 11:00 AM ET
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Webinar

DataCamp for Business in Action: Learn, Apply, Recruit

In just 30 minutes, discover how DataCamp for Business can help you future-proof your workforce, simplify recruitment, and empower every employee with the data science and data literacy skills they need to grow your business. In this session, you’ll also learn how Rolls-Royce, and a UK governing body use DataCamp, and see how easy it is to run a data literacy upskilling program that works. This short session is open to team managers, Learning and Development (L&D) experts, or senior leadership who are ready to end data illiteracy. Register to save your seat and find out how to make data your organization’s superpower.

Thursday, July 7—10 AM BST, 12 PM ET, and 11 AM AEDT
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Live Training

How to Explain Black-Box Machine Learning Models

Interpretable machine learning is needed because machine learning by itself is incomplete as a solution. The complex problems we solve with machine learning require linear algebra, calculus, and statistics precisely because we don’t understand all of the problem space we’re trying to solve. One of the most significant issues is that given the high accuracy of our machine learning solutions, we tend to increase our confidence level to the point we fully understand the problem. Then, we are misled into thinking our solution covers all of the problem space. By explaining a model’s decisions, we can cover gaps in our understanding of the problem. Black-box machine learning models are thought to be impenetrable. However, with inputs and outputs alone, a lot can be learned about the reasoning behind their predictions. In this session, we will cover the importance of model interpretation and explain various methods and their classifications, including feature importance, feature summary, and local explanations.

Tuesday, July 12th, 11:00 AM ET
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Webinar

Customer Story: How the Novartis L&D Team Scaled Their Data Training

In this webinar, Kemi Philips, Head of Capability Building - Data Science and Artificial Intelligence, presents her story of running a large-scale data academy. She discusses the challenges and successes of the program, along with practical tips for how to scale training at your organization.

Thursday, July 14, 11:00 am ET
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Webinar

Fighting Churn with Data

Customer churn is a headache for every company. If you cannot retain your customers, then you cannot stay in business. Making use of data to understand the reasons for customer churn, and to test ways of improving retention can have dramatic benefits to your organization's finances. In this webinar, you'll learn how to make use of data to solve your churn problems.

Thursday, July 28, 11:00 am ET
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