STEM

Applied Machine Learning (with PyTorch)

Fall 2022

This is a course in applied machine learning with PyTorch.

Systems Assurance (Cryptography)

Fall 2022

This is an introductory course to Cryptography. This course covers the implementation of systems assurance with computing systems. Topics include confidentiality, integrity, authentication, non-repudiation, intrusion detection, physical security, and encryption. Encryption algorithms: secret key, DES, PKI, RSA, SSL/TLS, and more. Extensive laboratory exercises are assigned.

Software Assurance

Fall 2022

This course covers defensive programming techniques, bounds analysis, error handling, advanced testing techniques, detailed code auditing, software specification in a trusted assured environment. Extensive laboratory exercises are assigned. Topics: buffer overflows, format string vulnerabilities, web SOP, XSS, CSRF, web worms, race conditions, e-commerce security, and more.  

Practical Deep Learning

Spring 2022

This is a course in Deep Learning

Machine Learning Foundations

Spring 2022

This course provides a basic introduction to the machine learning pipeline and related concepts. Topics covered include: Machine learning uses and applications; data set requirements; data pre-processing; data annotation, and validation; data representation formats; features and feature representation and extraction; the vector space model; traditional machine learning algorithms; machine learning algorithms and programming; ML evaluation methods; introduction to deep learning algorithms; big data; reinforcement learning; Unsupervised learning; statistical significance analysis; and other special topics.

Assured Systems Design and Implementation (Network Security)

Spring 2022

This course covers the design and implementation of assured systems in an enterprise environment. Topics include: Systems design and implementation, network security threats and controls, and special topics.

Linux: Systems Administration and Management

Spring 2022

Topics include: workstations, servers, services, data centers, disaster recovery, security policy, network administration, helpdesks, debugging, upgrades, namespaces, system maintenance management, email and printing services, system backup, remote access, IT support, scripting with bash and Python for system management.

Intro to Comp Algorithms and Logic (with Python)

Fall 2020

This course covers introductory topics in programming using the Python language. 

Distributed Application Development

Spring 2021

This course is a project oriented course in multi-tier application development, interface design and implementation, component based application development, and configuration of multi-tier applications. Extensive laboratory exercises are assigned. 

Applied Machine Learning (with Tensorflow)

Fall 2020

This is a course in Machine Learning

Machine Learning for Cyber Security

Summer 2019

This is a course in machine learning for cyber security. Topics include: the basic ML approach, features and feature extraction, data set formats, supervised and unsupervised machine learning, applications of machine learning to cyber security: IOT, Malware, IDS, etc.

rcalix@pnw.edu