Artificial Intelligence Business Innovation, Graduate Certificate

Application Requirements

• Online application and $50 application fee
• College transcripts
• Personal statement
• Resume – Work experience preferred but not required.
• Video interview as part of the online application
• Additional requirements apply for international applicants

Learn more about the application process and what you will need to apply.

The program can be completed in as little as 9 months (2 semesters).

Two-Semester Program of Study

Required Courses

• IFI 8410 – Introduction to Programming & Predictive Analytics for Business
  This course prepares students to utilize both structured and unstructured data in decision making, and to use models to address business challenges such as reducing customer churn, predicting market demand and forecasting stock prices. After taking this class, students will be able to: (1) frame a business problem using predictive analytics, (2) ascertain how and when to use specific models to address business problems and (3) develop the necessary proficiency in Python and R to tackle those issues.
  View Sample Syllabus
• ENI 8010 – Innovation Studio 1: Innovation and Design Thinking
  Design thinking is taught as a systematic approach to innovation and creative problem-solving that can be used in many industries. In this course, students are introduced to resourceful problem discovery through methods of noticing, observing and analyzing data. Using a combination of the lean startup methodology and design thinking, students conduct experiments as well as interviews and test prototypes to verify the viability of proposed solutions. Further, ideation models are applied to conceptualize new-to-the-world technologies, business models, products, and services as potential business ventures. Students will become comfortable with ambiguity, experimentation and online collaboration.
  View Sample Syllabus
• IFI 8420 – Machine Learning and Deep Learning for Business
  This course provides an introduction to machine learning and artificial intelligence. Since unstructured data comprises a large and important source of information, students cover deep learning techniques to tackle complex problems involving images, text and recommendation systems. After taking this course, students will: (1) understand the basics of machine learning and its application to business problems, (2) be able to apply insights to complex AI projects and (3) understand the pros and cons of different techniques and their preferred business application scenarios.
  View Sample Syllabus

Elective Courses (Select One)

• ENI 8011 – Innovation Studio 2: Launch and Scale
  This experiential course is treated as a mini-accelerator. The class teaches “the entrepreneurial mindset” as well as how to apply that to launch and scale a business, develop solutions to business challenges or create new products and services that result in growth opportunities for an organization. Students explore a rigorous and disciplined approach to validating product market fit, building teams, developing viable business models and crafting messaging and pitches that resonate with the audience. Students apply these learnings on a remote team project. The challenge? Launching and scaling a business or solution, ideally generating revenue before the end of the semester. Every few weeks, students convene in the classroom to receive feedback and coaching on their approaches, results and future experiments.
  View Sample Syllabus
• IFI 8430 – Advanced Analytics Experience
  This course prepares students to proceed through the four stages of an analytics workflow: (1) business problem framing, (2) data preparation and exploration, (3) analytics methodologies and (4) presentation and visualization. Students explore and tackle analytics methods to solve issues such as pricing, analyzing customer review data, market segmentation, customer discovery and process improvement. Students learn how to collect and clean data, handle missing values, examine descriptive statistics, build different models as well as identify the most accurate and interpretable one and present insights from the model’s output.
  View Sample Syllabus
• FI 8092 - Artificial Intelligence and Machine Learning Applications in Finance
  Students will develop skills for applying modern machine learning methods and other analytics techniques (such as Python programming) to address practical problems encountered in asset management, corporation finance and financial institution settings. The techniques include tree regression, neutral network, textual analysis, web scraping, data visualization and model assessment and selection using cross-validation.

Georgia residents: $4,058 per semester
Non-Georgia residents: $8,912 per semester
Nonrefundable seat deposit: $250

Tuition is subject to change.

Please note: the above tuition rates apply to new non-degree-seeking students. Students who are enrolled in a cohort master's program will be charged at their current cohort tuition rate. Students who are enrolled in the Flexible MBA program will be charged at their current flexible tuition rate.

Financial Aid

Contact Graduate Student Financial Services
We are here to help you understand the cost of your program (including the financial aid cost of attendance (https://sfs.gsu.edu/resources/coa/)), the payment schedule and financing opportunities.

[email protected]
404-413-7086

The mission of the Graduate Certificate in Artificial Intelligence Business Innovation is to produce “citizen data scientists”—professionals who may not have deep programming skills but, with the right tools, are capable of leveraging advanced technologies as well as working with and leading teams of data scientists to create value and realize the potential of artificial intelligence.