Blockchain Bundle - Healthcare

Admission Requirements

Applicants must be at least 18 years of age.

Curriculum Details

Sample courses include:

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.

Data Mining
This module provides an overview of basic concepts in data mining and main methodologies and approaches used for knowledge discovery from data. Topics include the definition of data mining field; data mining process; data preprocessing; predictive and descriptive data mining; evaluation of data mining models; and privacy and security of data.  The module uses case studies from healthcare.

Blockchain
This course will be an introduction to Blockchain. There will be a modularized approach, to focus development on the skills for each aspect of blockchain. Labs based on practical applications e.g. bitcoins are incorporated.

What You'll Learn

Participants will develop:

• Python Skills: Master basic to advanced Python programming for problem-solving.
• AI Knowledge: Understand the history, principles, and ethical considerations of AI.
• Blockchain Expertise: Gain comprehensive knowledge of blockchain technology and its applications in healthcare.
• Data Mining Proficiency: Analyze and discover patterns in data for predictive and descriptive modeling.
• Cognitive Computing Skills: Leverage deep learning frameworks to enhance healthcare processes.
• Robotics and Automation Insights: Explore system architecture and cybersecurity measures for robotic systems in healthcare.

Graduates will be prepared to:

• Design secure blockchain systems for healthcare applications.
• Implement AI solutions to enhance decision-making and efficiency in healthcare.
• Analyze data for cybersecurity risk assessment and mitigation.
• Develop robotic process automation tools to streamline healthcare operations.
• Pursue roles such as Cybersecurity Specialist, Blockchain Developer, AI Analyst, or Healthcare Data Scientist.