Artificial Intelligence Bundle - Healthcare
- Overview
- Admissions
- Academics
- What You'll Learn
- Benefits
🌟 All Louisville programs offered through Bisk Amplified are now ACE-College Credit Recognized!
This four-course program from the University of Louisville offers a comprehensive introduction to cybersecurity and artificial intelligence (AI) fundamentals tailored to the healthcare industry. Delivered virtually and asynchronously, the program combines theoretical insights with real-world applications and expert-guided learning. Participants gain in-depth knowledge of coding, data structures, and advanced AI techniques, positioning them to address critical challenges in healthcare cybersecurity.
Who Should Register
Who Should Register
This program is ideal for:
- Healthcare professionals looking to integrate AI into their operations.
- Cybersecurity specialists seeking industry-specific knowledge.
- Individuals interested in exploring AI and robotics applications in healthcare.
Why Choose Louisville
Founded in 1798, the University of Louisville (UofL) is a leading institution recognized as both a Research 1 and Community Engaged university by the Carnegie Foundation. UofL’s commitment to innovation, education, and global connectivity ensures students gain unparalleled opportunities to thrive. With a focus on shaping a better future, UofL prepares learners to excel in the rapidly evolving fields of healthcare, cybersecurity, and AI.
Admission Requirements
Must be 18 years of age or older.
Curriculum
Curriculum Details
Courses in the suggested order:
Coding
This module provides an introduction to problem-solving techniques and the computer program development process through coding in a high-level language. Topics include: program structure; data types; variables; operations; expressions; input/output; sequence, selection, and repetition; functions; data structures; and software design techniques. Concepts are reinforced with many programming laboratory-exercises throughout the course.
Artificial Intelligence
This module provides an overview of the fundamental techniques and approaches in artificial intelligence. Topics include the history of AI; knowledge and reasoning; problem solving; learning approaches; practical considerations; and responsible AI. The module uses case studies from cybersecurity and healthcare applications.
Cognitive Computing
This module provides lectures and labs on deep learning and machine learning using combination of tools such as cognitive services APIs, Deep Learning frameworks and libraries. Two major breakthroughs for cognitive computing in healthcare are: 1) consumer/user engagement (e.g. IBM Watson social network Welltok) and 2) discovery applications, such as drug discovery and analysis of human health. Internet of Medical Things integrates sensors and AI algorithms, which are vulnerable to cyber-attacks. Examples of attacks are: 1) access by malicious actors; 2) loss or corruption of enterprise information and patent data. Topics include: Neural Networks, Convolutional Neural Network (CNN), Long – Short Term Memory (LSTM), Natural Language Processing (NLP) and Deep Reinforcement Learning (Deep RL).
Robotics Process Automation Analysis
This module provides lectures and labs on the system architecture enabling robotics and common use cases for robotics in healthcare. Topics include: Distinguish the characteristics of operating systems enabling robotics; Distinguish the characteristics of operating systems enabling robotics; Common threats and cyber-attacks to robotic systems; The ethical issues related to the use of robotics and the need for cybersecurity to enable trust in robotic operations.
What You'll Learn
Participants will develop:
Python and Data Analytics Skills:
Gain foundational programming knowledge and data structure expertise.
AI and Chatbot Familiarity:
Explore AI fundamentals and the use of chatbots in healthcare settings.
Cybersecurity Awareness:
Understand vulnerabilities in healthcare systems and learn strategies to mitigate cyber-attacks.
Graduates will be equipped to:
- Design and implement AI-driven cybersecurity solutions for healthcare.
- Utilize machine learning and cognitive computing tools to solve healthcare challenges.
- Develop and safeguard robotic process automation (RPA) systems in medical applications.
- Pursue roles in healthcare IT, cybersecurity analysis, and AI development.