Program Overview

Overview of the Robert H. Buckman College of Engineering Online Education Program

The Robert H. Buckman College of Engineering Online Education Program offers a range of online degrees, certificates, and courses in various fields of engineering. The program is designed to provide students with a comprehensive education in their chosen field, with a focus on practical application and real-world problem-solving.

Doctoral Programs

• Doctor of Engineering

Master Programs

• Aeronautics & Astronautics
• Autonomy
• Biomedical Engineering
• Civil Engineering
• Dual Degree MSE+MBA
• Electrical & Computer Engineering
• Engineering Education
• Industrial Engineering
• Interdisciplinary Engineering
• Internet of Things
• Mechanical Engineering
• Microelectronics and Semiconductors
• Nuclear Engineering
• Robotics
• Software Engineering
• Systems Engineering

Graduate Certifications

• Applied Heat Transfer
• Digital Signal Processing
• Hypersonics
• International Development
• Microelectronics and Semiconductors
• Noise Control
• Regulatory Affairs and Regulatory Science for Medical Devices
• Systems
• Teaching and Learning in Engineering

Courses

The program offers a variety of courses in different fields of engineering, including:

• Semiconductor Fabrication 101
• Additive Manufacturing
• Design for Security
• Data Science
• Building Water Essentials
• Model-Based Systems Engineering
• Product Safety: An Introduction for Effective Engineering Design
• Small Modular and Advanced Reactor (SMR/AR) Technology
• Systems Engineering Processes and Professional Competencies

Professional Certifications

• Lean Six Sigma Green Belt
• Lean Principles
• Lean Six Sigma Black Belt
• Lean Six Sigma Green Belt Refresher
• Agile Project Management
• Project Management Essentials
• PMP Exam Preparation

Big Data for Reliability and Security

Course Description

This course builds an understanding of techniques for meeting reliability and security requirements in connected computing systems, covering not only traditional threats but new threats posed by big data and large-scale systems. Students will learn big data analytic and machine learning techniques for improving reliability and security and develop software to apply to real-world datasets under realistic conditions.

Prerequisites

• Knowledge of Python
• Introductory Statistics

Course Outcome

The course covers foundational material on reliability and security, data analytic techniques for dependability, big data security and insecurity, and case studies and challenge problems.

Topics Include

Foundational Material on Reliability and Security

• Introduction: Motivation, System view of reliable and secure design, Terminology
• Security landscape for connected systems: Traditional threats, new threats due to large-scale systems, new threats due to big data
• Reliability landscape for connected systems: Traditional concerns, new concerns due to large-scale systems, new concerns due to big data

Data Analytic Techniques for Dependability

• Supervised and unsupervised learning techniques
• Neural Networks building blocks
• Techniques for dealing with large-scale data; regularization, feature engineering, dimensionality reduction, etc.
• What is our tool chest of data analytic techniques: what to use and when
• Data analytic techniques used for reliability and security: strengths, weaknesses opportunities

Big Data Security and Insecurity

• Attacks against big data algorithms: evasion and poisoning attacks
• White box and black box attacks
• Defenses: Adversarial training, defensive distillation, adversarial example detection
• Machine learning at scale: Federated learning
• Federated learning for security and privacy

Case Studies and Challenge Problems

• Case studies on adversarial Machine Learning: Image and video manipulation
• Systems for big data processing: Spark, TensorFlow on the cluster, TensorFlow Light. Benchmarks for big data processing
• Challenge problems
  • Challenge problem 1: Predicting computer system failures
  • Challenge problem 2: Proximity detection through Bluetooth signals

CEUs

• 1.5 CEUs are awarded upon completion of the course

Student Resources

The program provides various resources to support student success, including:

• Student Resources
• Academic Calendar
• Buying Textbooks
• Disability Resource Center
• Library
• Online Writing Lab
• Access to courses
• Registration deadlines
• Exam process
• Finding an exam proctor
• Student responsibilities

Program Details

The Robert H. Buckman College of Engineering Online Education Program is committed to providing a high-quality education that prepares students for success in their chosen field. With a range of programs and courses available, students can choose the path that best fits their needs and goals. The program is designed to be flexible and accessible, with online courses and degree programs that can be completed from anywhere in the world.