CSC 105 Introduction to Computer Science Professor Batchelor

The purpose of this course is to introduce you to data analytics and data visualization. Data Analytics refers to the use of the computer to analyze complex information about an organization and its competitors for use in planning and decision making in business, science and engineering. Data analytics is one of the current “hot topics”. It is an area which is growing despite the economic downturn in technology, as companies and organizations realize that they must improve their understanding of their capabilities and those of the competition if the quality of their decisions is to be competitive. The vast amount of data now available to organizations adds to the complexity of data analytics. Analytical models and methods, and visualization software which we will study in this course, help accomplish the synthesis of this data into useful information.

Topics Covered Data Analytics and computation: Excel Data Visualization: Tableau Database design and query analysis: Access Optimization software: Solver Programming concepts: Python Data Mining: XLMiner (if time permits) Decision Analysis: TreePlan (if time permits)

COURSE GRADING Student performance will be evaluated on the following basis: Major software project20% Case Studies/labs and Attendance 5% Average of Midterm exams40% Final exam 35% 100 EXAMS The 2 midterm exams will be conducted during the regular class period or lab. The final exam will be given during the scheduled final exam schedule. All exams will be online. The final exam is non-cumulative and covers only material from the second exam on

Lecture and Lab Lecture: Your involvement in class discussions and activities are crucial for your development as a professional. be prompt and regular in attendance and current with the assigned readings. I will expect you to ask questions during class, state your viewpoints and opinions, and be prepared to answer questions from the readings and discuss the case studies. Lab: You are expected to attend every class and lab Be ON TIME. Lab activities often begin with a demo. When you are late it is your responsibility to catch up (without bothering other students). With appropriate documentation, I will excuse absences due to illness and/or emergencies (such as death in the family.) If you miss a lab or lecture do not expect me to bring you up to date. However, I will be happy to help you if you have an excused absence OR if you do not understand the lecture or lab material. Ignorance of an announcement made in class is no excuse for failure to meet an assignment

COURSE LEARNING OBJECTIVES To gain an understanding of how managers use data analytics to formulate and solve business problems and to support managerial decision making. To become familiar with the processes needed to develop, report, and analyze business data. To learn how to use and apply selected data analytics software. To become familiar with basic structured programming constructs and module design. Object-oriented programming concepts will also be covered in the course.

SOFTWARE PROJECT The course requires the completion of a software project using any of the below: Excel, Access, Tableau, and Excel Solver, PowerPivot, PowerView or Python Or any other data analytics software of your choice All of the projects are completed individually or in teams of 2-3 students. In addition there will be one final project presentation.final project presentation.