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Artificial intelligence (AI) is rapidly transforming businesses across all industries. In a world where AI and data are interwoven, it can be difficult to establish teams that include different roles and skills vital to your success. In this webinar, we will explore the intricate tapestry of roles within Data & AI teams, shedding light on the essential skills and key objectives associated with each. We will also discuss our comprehensive training courses in the Data & AI domain, helping you tailor your skills development to improve and advance in your role. 

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In today's ever-changing cybersecurity landscape, it's crucial to have a highly qualified and competent workforce. No matter the size of the organization, data safety is essential and can only be achieved through a proven set of skills and tools. This webinar will provide a brief overview of the NICE Framework and how it can be used to establish cybersecurity competency models, map jobs to roles, and deploy assessments to determine your organization's cybersecurity readiness. We will also discuss the right learning path for you and offer sample assessments.

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The business world is changing at an alarming rate, and the need to keep yourself and your team up to date with the latest skills and technologies is vital to organizational success. From cybersecurity to leadership to project management, this webinar will cover a wide range of in-demand skills and related topics across all industries. Learn how important it is to acquire these skills, and what it could mean for your professional role and career. Tune in to get all this and more, all in one watch.

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Artificial intelligence (AI) is rapidly transforming the business landscape, and organizations that want to stay ahead of the curve need to understand how to implement AI effectively. This webinar will provide you with the practical insights you need to successfully integrate AI into your organization.

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A leading healthcare provider, employing more than 200,000 employees and serving 12.5 million people across the United States, follows a unique and strategic business model that combines health coverage and care delivery into a coordinated experience.

Each section represents a key stage in the machine learning process.

• Training data is fed into a machine learning algorithm. This data trains the system, e.g., labeled images to teach a system to recognize cats.
•  The algorithm analyzes the data to find patterns and relationships, adjusting its internal parameters to optimize pattern detection.
•  Now that it's optimized, the model can predict or decide things using new, unseen data.
•  Over time, the system continues to learn from new data to improve its model.

• Sample Bias happens when the data is collected. The sample may need to be bigger and more representative to teach AI how the real world looks.
• Prejudice Bias comes from real-world prejudices, which influence how the data is created.
• Exclusion Bias occurs if the modeler leaves the data out because they don’t see the outliers or the dimension as necessary.
• Algorithmic Bias is built into the model’s code and happens during the computation process. It may push specific results over others.

THE AI ENGINEER'S ROADMAP

Navigating the route from interest to impact in artificial intelligence engineering

Align your workforce with cyber security frameworks to protect your organization against cyber threats.

There is a trend of organizations focusing on complete automation, whether it means creating their own unique, tailored applications or automating manual workflows. Join certified AWS, Microsoft and Google Cloud Expert, Keith Pealstrom as we discuss how to use Microsoft's Power Apps and Power Automate to streamline your everyday task, build custom apps, automate workflows, and increase workforce productivity.