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Implementing Big Data & Artificial Intelligence (AI) for Business Professionals is an introductory-level course that delves into the core AI and how AI can be practically exploited in the modern business sense.

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Unlimited Duration

Last Updated

March 24, 2021

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Certification

This course introduces AI from a practical applied business perspective.

In this course you learn about:

· Learn which data is most useful to collect now and why it’s important to start collecting that data as soon as possible

· Understand the intersection between big data, data science and AI (Machine Learning / Deep Learning) and how they can help you reach your business goals and gain a competitive advantage.

· Understand the factors that go into choosing a Data Science system, including whether to go with a cloud-based solution

· Explore common tools and technologies to aid in making informed decisions

· Gain the skills required to build your DS/ AI team

Course Curriculum

      • How Big Data exploded and what has changed to make “data” the new “oil” 00:00:00
      • The history of AI to ML to DL and an introduction to Neural Networks. 00:00:00
      • What it means to be data driven and how our paradigm is changing 00:00:00
      • 20+ of the most common business use cases 00:00:00
      • Overview of the key concepts related to Data Science to include open source, distributed computing, and cloud computing 00:00:00
        • Use Data Science to guide strategy based on insights into your customers, your product performance, your competition, and additional factors 00:00:00
        • Step by step instructions for scoping your data science initiative based on your business goals, stakeholder input, putting together project teams, and determining the most relevant metrics 00:00:00
        • How to select models and the importance of agile to realize business value 00:00:00
        • Choosing your technology for your proposed use case 00:00:00
        • The key roles that need to be filled in Big Data and Data Science programs and considerations for outsourcing roles 00:00:00
        • Principles in privacy, data protection, regulatory compliance and data governance and their impact on legal, reputational, and internal perspectives. 00:00:00
        • Discussions of 00:00:00
        • Explore a high-profile project failure and best practices for Data Science success 00:00:00
        • What the Future Hold 00:00:00

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