La Salle’s B.S. in Computer Science to M.S. in Artificial Intelligence program offers an accelerated 5-year path to earn degrees in fast-growing fields. The bachelor’s program is a traditional computer science curriculum with a heavy focus on theory and mathematics. The master’s in AI program provides students with the ability to develop skills in machine learning, deep learning, natural language processing, and data analytics.
A student in this program is able to take two graduate level courses (6 credits/2 courses). The courses are counted towards the undergraduate 120 credit requirement, and if the course grade is B or higher, the course is also counted towards the graduate program. Students receive the bachelor’s degree and are able to complete the remaining 24 credits (8 courses) to earn the graduate degree.
Why Study Computer Science/Computer Information Science at La Salle?
La Salle’s B.S. in Computer Science to M.S. in Artificial Intelligence program offers an accelerated pathway for students to earn both degrees in five years, preparing them for successful careers in a rapidly growing field.
This course introduces students to the field of artificial intelligence (AI). Students will learn how big data and data mining techniques are utilized by machines to create the AI models used by autonomous aircraft and automobiles, personal assistants, IT security software, fraud investigations and credit bureaus. The course will review the history, present day use, and future of artificial intelligence. Through case studies and current events, students will examine the benefits and risks associated with AI. The course will cover issues related to AI and privacy, ethics, and machine bias. Neuromorphic computing, the Open Neural Network Exchange (ONNX), and data analytics will also be discussed.
AI 656: Deep Learning and Neural Networks
This course provides an in-depth exploration of deep learning, a subset of machine learning that focuses on neural networks with many layers (deep architectures). Students will learn the theory, methodologies, and practical implementations of deep learning model.
BSA 740: Data Visualization
One of the skills that characterize great business data analysts is the ability to communicate practical implications of quantitative analyses to any kind of audience member. In this course, students will learn how to visualize data, tell a story, and explore data by reviewing the core principles of data visualizing and dashboarding. The course aims to focus on effective and high impact visualizations of common data analyses to help them convey conclusions directly and clearly. Students will be able to get practiced in designing and persuasively presenting business “data stories” that use these visualizations, helping stakeholders make decisions and take action based on their business data capitalizing on design principles.
Meet the Faculty
Our faculty are experts in their field, prioritizing the success of students and providing a groundwork you to pursue your career of interest.
