Introduction to Analytics and Artificial Intelligence

What You'll Learn

• check_circle• A brief overview of the history of analyzing data, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.
• check_circle• A look at data stores, which are growing exponentially, and the challenges of wrangling “big data.”
• check_circle• Understanding of data mining—what it entails, different approaches, and who’s leading the way.
• check_circle• A two-part discussion of business intelligence, including the principles of sound dashboard design and data presentation.
• check_circle• The key differences between the four types of analytics—diagnostic, descriptive, predictive, and prescriptive—and how they relate to and build upon each other, and how they apply to various industries.
• check_circle• An overview of specific analytics processes and models.
• check_circle• A first look at AI, its evolution, its functions, and what it can do for businesses today.
• check_circle• An exploration of machine learning—how systems can learn from data, identify patterns, and make decisions with little human intervention.
• check_circle• A survey of deep learning technologies, including a variety of neural networks.
• check_circle• An overview of the most important machine learning data modeling techniques
• check_circle• A practical and honest appraisal of the analytics and AI landscape today and moving forward, including the tremendous promise and the potential pitfalls.
• check_circle• Resources for continued study on these topics.