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Introduction to Big Data Analytics (AIP 301)

This course will provide you with an introduction to the world of Big Data Analytics/Data Science with focus on major concepts in the field, the most prominent tools and examples from areas of application of Data Science.

Who Benefits
Big Data Analytics application is growing from limited application in IT industry into a mature transferable skill that can benefit variety of other areas. The figure below (Which by the way is generated by a big data analytics application) explains the influence of this field in different industries.
If you are working in any of the above industries either as an employee or as a founder of a startup company, Big Data Analytics can benefit your business through:
  • Re-developing your product
  • Perfoming Risk Analysis
  • Creating new revenue streams
  • Customizing your website in real-time
  • Reducing Maintenance Costs
  • Offering Tailored Healthcare
  • Offering Enterprise-wide Insights

Course Content
  • What is Data Science?
  • What is Machine Learning?
  • What is Big Data?
  • What is Big Data Analytics?
  • Making an old dog do old tricks - Machine Learning is Statistics
  • Relevant Statistical Algorithms - Classifications (LDA, QDA, SVM), Regression, Deep Learning (Neural Networks), Random Forest
  • Relevant Capabilities to carry out Big data analytics - Python, R, Scala
  • Working with unstructured and Big data: Preprocessing, Feature Selection, Post Analysis
  • Big Data Infrastructure - Hadoop, Spark
  • Visualization for Big Data Analytics

Outcome
By successful completion of this course, you will gain an intermediate knowledge and skill sets for understanding and solving problems in Data Science. This course is also the prerequisite for our Advanced Big Data Analytics with focus on more advanced topics in the field.

Course Dates

CRN# Course Cost Start Date Duration Location

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