Introduction to Data Science and Machine Learning

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The course is an introductory course that covers a wide variety of topics at the intersection of data science and machine learning with a good balance between theory, numerical methods (coding), and applications. Designed for students and beginners seeking comprehension of the concepts, statistics, and mathematics underpinning data science and machine learning algorithms. The course starts from the basics, requiring no prerequisites for participants to begin their learning journey. The course covers basics related to data science, data visualization, regression methods, classification methods, unsupervised learning, and spectral clustering methods. You will gain familiarity with various data science and machine learning model concepts, including data journalism, data visualization and storytelling, linear and
non-linear regression, decision trees, random forests, neural networks, and clustering techniques.
Students who successfully complete this course will be able to:
• Apply quantitative modeling and data science analysis techniques to the solution of real-world problems.
• Communicate findings and effectively present results using data visualization techniques.
• Demonstrate knowledge of statistical data analysis techniques utilized in applied engineering problems.
• Apply principles of Data Science to the analysis of engineering problems.
• Employ cutting-edge programming languages and computational tools to analyze Big Data.
• Understand key concepts in the machine learning domain along with some in-depth understanding of classical machine learning algorithms
• Apply classic machine learning algorithms to build machine intelligence.





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Course Instructor 

Dr. Rahul Rai

CEO AIBrilliance
I am Dr. Rahul Rai. I am a Dean's Distinguished Professor in Automotive Engineering and Computer Science and Associate Director, Artificial Intelligence Research Institute in Science and Engineering (AIRISE) at Clemson University. I also have industrial research center experiences at United Technology Research Center and Palo Alto Research Center. I am the Founder and CEO of AI Brilliance, a company focused on empowering people to learn about data science, machine learning, and AI concepts.

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