Courses and Syllabus
Machine Learning
The course helps you gain an advanced level understanding of Machine Learning application and algorithm like regression, clustering, classification, and prediction. It also covers deep learning and Spark Machine learning. The course includes 2 industry-based projects on designing recommendation and prediction system. It’s best suited for data scientists and analytics professionals.
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>>Machine Learning with Matlab
>>Machine Learning with Python
>>Machine Learning with R
Python Language
Python is a general-purpose language, which means it can be used to build just about anything, which will be made easy with the right tools/libraries.
Professionally, Python is great for backend web development, data analysis, artificial intelligence, and scientific computing. Many developers have also used Python to build productivity tools, games, and desktop apps, so there are plenty of resources to help you learn how to do those as well.
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Artificial Intelligence
This course will present advanced topics in Artificial Intelligence (AI). We will begin by defining the term "software agent� and discussing how software agents differ from programs in general. We will then take a look at those problems in the field of AI that tend to receive the most attention. Different researchers approach these problems differently. In this course, we will focus on how to build and search graph data structures needed to create software agents, an approach that you will find useful for solving many problems in AI. We will also learn to "break down� larger problems into a number of more specific, manageable sub-problems. In the latter portion of this course, we will review the study of logic and conceptualize the differences between propositional logic, first-order logic, fuzzy logic, and default logic. After learning about statistical tools commonly used in AI and about the basic symbol system used to represent knowledge, we will focus on artificial neural network and machine learning, which are essential components of computational and statistical methods, and theoretical computer science. The course will then conclude with a study of the Turing machine and a discussion of the questionable claims that human thinking is a symbol manipulation.
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