This course provides Big Data concept and applications of Big Data analytics in different fields such as agriculture, manufacturing, marketing, online retailing, health care and banking. The objective of this course is to familiarize student with Big Data analysis as a tool for addressing the application in different fields. The course begins with a basic introduction to big data, as well as associated technical, conceptual and ethical challenges. Strengths and limitations of big data research are discussed in depth using real-world examples. The next part is analysis implementation of actual cases by introducing and applying special algorithms in different fields, familiar with applications of data exploration software as STATISTICA (v13) and its data miner. These specific algorithms include association rules, decision tree, clustering, and classification. Students then engage in case study exercises in which small groups of students develop and present a big data concept for a specific real-world case. Attending this course, students will have an opportunity to access to real data from different industries and know how to analysis the data with problem based learning. The goal by the end of this semester is for student to have “analytics portfolio” consisting of data analytics skill that students can use for their future career.