ENGI 307 Data Analysis and Machine Learning

Revealing business and economic patterns and information hidden in data by transforming data using algebraic and statistical methods. Enabling computers to learn to predict and categorize events by using data.

This course will help students have the tools to reveal business and economic patterns and information hidden in data by transforming data using algebraic and statistical methods. It enables students to effectively use computers to learn to predict and categorize events by using data. Machine learning techniques are utilized to help students get familiar with various data analysis techniques using a computational environment.

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After reading the Course Syllabus and Student Expectations, the student will complete the related checklist found in the Course Overview.

Discussions are collaborative learning experiences. Therefore, the student is required to provide a thread in response to the provided prompt for each forum. Each thread must be at least 250 words and demonstrate course-related knowledge. In addition to the thread, the student is required to reply to 2 other classmates’ threads. Each reply must be at least 125 words. References must be cited in current APA format.

Lab Project Assignments (8)

The student will answer question(s) pertaining to a subject covered in the course.

Reading Report Assignments (7)

The student will write at least 250 words summarizing the chapter.

Each quiz will cover the Learn material for the assigned module. Each quiz will be open-book/open-notes, contain 5-10 questions, and will not have a time limit.