Curriculum and Course Descriptions

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Course Descriptions

GC-AIM Curriculum Guide

Analytics and Information Management
Statistical and technical understanding are essential for the AIM professional. This course focuses on creating a solid foundation of technical skills, which will be applied in downstream courses. Topics will include programming concepts and logic, descriptive, predictive and prescriptive statistics, and data storage techniques. Prerequisites: None

Information Systems Ecosystem
Within the context of data analytics, this course teaches students to manage information as a strategic asset with the potential to create significant business value. Students will be exposed to various approaches to managing the capture, retention and disposition of information. Special emphasis will be placed on the legal/regulatory, ethical, risk management and cybersecurity requirements of managing information. Topics include the role of information systems in an organization, information systems governance (which is designed to ensure that IT investments create organizational value), data governance (which seeks to ensure that organizational data meet the standards for quality data), and strategies for identifying measurable sources of ROI. Prerequisites: None

Data Querying
Modern organizations use database management systems to store their critical business data. In this course, students learn to answer business questions using various data retrieval, manipulation and transformation tools. For instance, data retrieval for most data-driven business applications relies on Structured Query Language (SQL) - the international standard language for data manipulation and retrieval. To source the data required by analytics projects, students will learn to utilize SQL along with other data-related concepts and languages. Prerequisites: None

Predictive Analytics with Machine Learning
Artificial intelligence (AI) is the science of getting computers to learn and solve problems autonomously without being explicitly programmed (machine learning). In the past decade, through machine learning, AI has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Companies are increasingly applying AI technologies and techniques to uncover new business insights and assist managers with making better informed and timely decisions. This course will cover concepts and algorithms in artificial intelligence with an emphasis on machine learning. Students will learn about the most fundamental machine learning techniques, gain practice implementing them and applying them to new problems. Prerequisite: ISYS 610.

Behavioral Analytics with Visualization
E-commerce and social media have experienced rapid growth during the past decade. Billions of users have been generating and sharing a variety of social content including text, images, videos, and related metadata. Social media can be viewed as an indicator reflecting different aspects of the society, and organizations can combine this with their existing data to support organizational decision-making. In this course, students will learn how to analyze behavioral data and apply the analyses to answer business questions. Advanced regression techniques, network concepts, and social theories will be covered throughout the course. Prerequisite: ISYS 610.