Aspire     Data for Leaders and Decision-makers     Data for Leaders and Decision Makers Track 3: Raw Data To Insights

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Predictive analytics enable modern businesses to obtain important insights about the market and gaining a competitive advantage. Use this course to explore how predictive analytics could provide insights about the future, empowering businesses to make informed decisions.
Start by delving deeper into the concepts of deep learning, machine learning, and data. You'll then examine neural networks theory of operation and discover natural language processing (NLP) and computer vision applications. You'll wrap up the course by developing a deeper understanding of the future of analytics.
Once you've completed this course, you'll be able to identify how regression, classification, time-series analysis, and recommender engines can be used to drive business decisions. You'll also have a solid grasp of using machine learning and deep learning methodologies for predictive analytics.

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Objectives

Data Mining and Decision Making: Predictive Analytics for Business Strategies discover the key concepts covered in this course specify the role of deep learning and artificial neural networks when dealing with data describe how a neural network works recognize unique features of regression problems and how these can be applied to predictive analytics describe unique features of classification problems and how these can be applied to predictive analytics describe how time series analysis is used for predictive analytics specify the role of actionable recommender systems in predictive analytics outline the key advantages of using recurrent and convolutional neural network pipelines identify key advantages of using NLP techniques in predictive analytics pipelines recognize the key advantages of using computer vision in predictive analytics pipelines describe the future prospects of predictive analytics alongside its most promising fields of study summarize the key concepts covered in this course