Blockchain Bundle - Logistics

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 acquire:

• Python Skills: Foundational and advanced programming abilities.
• AI Knowledge: A comprehensive understanding of AI concepts and their applications in logistics and cybersecurity.
• Blockchain Expertise: Practical knowledge of blockchain technology and its role in securing logistics systems.
• Data Mining Skills: Methods for data analysis to enhance decision-making and security.
• Cognitive Computing Skills: Advanced machine learning techniques to optimize logistics operations.
• Robotics Process Automation Insights: Strategies to safeguard and integrate robotic systems in supply chain processes.

Graduates will be equipped to:

• Implement blockchain solutions to enhance transparency and security in logistics.
• Use AI and cognitive computing to optimize supply chain efficiency.
• Develop robust cybersecurity strategies for logistics systems and robotics.
• Pursue roles such as:
  • Blockchain Developer
  • Cybersecurity Specialist in Logistics
  • AI Analyst for Supply Chains
  • Logistics Data Scientist
  • Robotics Process Automation Consultant