Open to Full-Time MSBA and MSMA Students
(Internship and Non-Internship Track)
As AI continues to revolutionize the analytics industry, we understand the critical need to equip our MS Business Analytics and Marketing Analytics students with the latest, cutting-edge skills. The Advanced Certificate of Achievement signifies to prospective employers a higher level of proficiency in AI. By obtaining this advanced certification, students will be exceptionally well-prepared to thrive in today's dynamic and ever-evolving business landscape.
Specialize in AI.
This Advanced Certificate of Achievement represents a technical competence in AI for business students. To earn it, an MS Business Analytics or Marketing Analytics student must complete 7.5 credits.
Students are required to take both of the following two courses (each worth 2.5 credits):
- GBA 479: Generative AI and Business Applications
This course covers the design and development of Generative AI-enhanced business applications. We will discuss a framework for integrating Gen AI tools and capabilities into business processes, tasks, and workflows. Students will learn how to program with Gen AI tools and LLMs using Python and APIs, build Gen AI-driven systems that execute dynamic tasks, and develop multi-agent architectures for complex workflows. The course also covers the use of Retrieval-Augmented Generation (RAG) to access private knowledge bases built on organizational data. By the end of the course, students will be equipped with the technical and conceptual skills to design and build generative AI applications tailored to modern business needs.
- CIS 433: AI and Deep Learning
Artificial intelligence (AI) was born in the middle of the 20th century as a branch of computer science. The early approach of symbolic AI has now been largely supplanted by machine learning. The recent breakthrough in artificial neural networks, rebranded as deep learning, represents the state-of-the-art of machine learning in many tasks, including computer vision and natural language processing. This has in turn triggered an unprecedented enthusiasm and huge investment in AI in the business world as well as in society at large. This course introduces the field of AI to business students with a particular emphasis on deep learning, which is driving the current AI revolution.
The course consists of three modules. The first module establishes the foundation of AI and deep learning. The second module introduces major neural network architectures widely used in practice. The third module touches on generative AI, which is particularly promising in recent years. The course emphasizes experiential learning and contains many hands-on projects using TensorFlow broadly and Keras in particular.
Specific learning objectives include:
- Learn the fundamentals of deep learning, including its origin, theory, and training techniques.
- Learn the modern network architectures including dense network, convolutional network, recurrent network, and transformer.
- Learn major algorithms of generative AI such as variational autoencoder, generative adversarial network, and diffusion models.
- Learn TensorFlow Data API.
- Learn the three approaches of building models in Keras.
- Learn Conv2D layer to build convolutional network.
- Learn LSTM and GRU layers to build recurrent neural network.
- Learn the implementation of transformer.
- Learn the implementation of variational autoencoder.
- Learn the implementation of generative adversarial network.
- Learn the implementation of denoising diffusion implicit model.
Students also choose an additional course from below:
- GBA 478: Introduction to AI and Business
GBA478 covers the application of generative AI technologies across diverse business contexts. The course will help you understand how to integrate Generative AI into today’s business workflows, providing frameworks to decide when and how to use it effectively. You’ll gain hands-on experience designing Generative AI tools to create business value and programming basic LLM-driven applications in Python. Finally, the course will ask you to become conversant with the big questions about Generative AI, to debate the moral, philosophical, and ethical challenges inherent in these systems and technologies.
- FIN 478: Introduction to AI and Finance
FIN478 covers the application of generative AI technologies across diverse business contexts. The course will help you understand how to integrate Generative AI into today’s business workflows, providing frameworks to decide when and how to use it effectively. You’ll gain hands-on experience designing Generative AI tools to create business value and programming basic LLM-driven applications in Python. Finally, the course will ask you to become conversant with the big questions about Generative AI, to debate the moral, philosophical, and ethical challenges inherent in these systems and technologies.
Benefits
• Receive a Certificate of Achievement in AI
• Class credits count toward certificate and degree
• Optional benefit with no additional cost or time to complete*
• Maintains STEM designation
• Signals expertise and career focus to corporate recruiters
*Students can only count credits from a master’s degree toward one advanced certificate of achievement. More than one advanced certificate during a master’s degree requires additional credits; accordingly, the student may incur additional costs.
Generative AI at Simon
At Simon, we provide our students with state-of-the-art training in generative AI, shaping leaders for the fast-paced business landscape of today. We're leading the way in integrating AI throughout our curriculum and extracurricular activities, reaffirming our status as a pioneer business education.