Winter 2024 Working Connections

Program Policies

The goal of the National IT Innovation Center’s (NITIC) online Working Connections professional development is to provide IT faculty attendees with the expertise needed to teach their track content in a subsequent semester, bringing the most current information to their classrooms either as a stand-alone course or as supplemental information to an existing course.

Key Details:

• Cost: There is no fee to attend; tuition is FREE
• Format: This is a synchronous virtual event.  Attendees are expected to sign on and participate together in real time all week.
• Eligibility: Working Connections is intended for faculty currently teaching IT credit courses (full-time or adjunct) or are an administrator at a regionally accredited U.S. community college, technical college, or university.  Attendees are expected to use what they learn in their track to teach or supervise a class in the next two semesters.
• Tracks: Class tracks last for the entire duration of Working Connections. Attendees may only select one track.

Important Points:

1. Registering: You can only apply to register one time per person.
2. Attendance Limitations: Because of limited space and budget, we only allow TWO faculty members per school to attend.  Additional interested faculty beyond the first two will be added to a wait list.  If space permits, the “wait listers” will be registered the week prior to the event.
3. Mandatory Survey: All attendees are required to complete a survey before the end of the event.
4. Certificate of Completion: Only those who attend every session morning and afternoon are eligible to receive a Certificate of Completion. Instructors will call roll every morning and afternoon.
5. Track Capacity: Seating capacity varies by track and instructor, but typically, tracks are capped at 20 attendees.
6.  Time Zones: Be sure to check for time zone differences. You are responsible for ensuring you do not miss your track.

Cancellation Policy

If you must cancel your registration, please notify Mark Dempsey at mdempsey@collin.edu immediately. The last day to make any registration change (request to change tracks or cancel) is Friday, November 22.

Because it is a priority of NSF grant funding that all available seats are filled, attendees who register but then fail to show up without providing advance notice may not be eligible for future Working Connections events. Please let us know right away if you’re not able to attend.

Securing Critical Infrastructure

Week 1: Tuesday, December 10 – Thursday December 12, 10:00 AM – 1 PM; 2 PM – 6:30 PM ET

Description

Critical infrastructure like water treatment plants and air traffic control towers are under constant attack by hostile nations and securing them is a national priority. This workshop covers industrial automation systems, network security monitoring, incident response, and machine learning. Participants will perform many hands-on projects configuring systems, attacking them, and defending them.

All class materials are freely available on the Web and may be easily used in other classes.

Objectives

• Identify the main Operational Technology network protocols and their weaknesses
• Detect intrusions and respond effectively to them
• Build machine learning systems and defend them

Pre-requisites

Participants should understand networking at the Network+ level.

At-home Computer Requirements

Participants should have a computer with at least two monitors, so they can easily read instructions while performing projects. Webcam and dual monitors recommended but not required.

Reference

NIST SP 800-82r3: Guide to Operational Technology (OT) Security (free)

https://www.nist.gov/news-events/news/2023/09/nist-publishes-guide-operational-technology-ot-security

Please note that content is subject to change or modification based on the unique needs of the track participants in attendance.

Agenda

Tue, Dec 10 – Operational Technology

• Preparing Windows and Linux Servers
• Implementing Modbus
• Configuring OpenPLC
• Using Ladder Logic
• Examining DNP3 Traffic
• Simulating a factory with FactoryIO
• Destroying a factory with Metasploit
• Network Security Monitoring
• Threat Hunting with Splunk

Wed, Dec 11 – Incident Response            

• Threat Intelligence (The ATT&CK Matrix)
• Threat Hunting (Using Zeek to analyze network traffic; Detecting ransomware with Splunk and Sysmon)
• Analyzing Attacks (Using Velociraptor; Using VirusTotal; Using Yara to classify files; Prefetch forensics to identify recent processes)
• Network Forensics (Using Nmap to identify network processes; Analyzing an attack with Wireshark; Packet crafting with Scapy; Using Packettotal to analyze network malware)

Thurs, Dec 12 – Machine Learning

• Understanding Prompts (ML 130: Prompt Injection)
• Google Learning (GL_Badges: Google Learning)
• Security Risks (ML 150: OWASP Machine Learning Security Top Ten; ML 151: OWASP Top 10 for LLM Applications; ML 152: Microsoft Copilot Security)
• Awareness: Demonstrating Capabilities (ML 100: Machine Learning with TensorFlow; ML 101: Computer Vision; ML 102: Breaking a CAPTCHA; ML 103: Deblurring Images)
• Technical: Inner Components (ML 104: Analyzing Input Data; ML 105: Classification; ML 112: Support Vector Machines; ML 113: Decision Trees; ML 114: Ensemble Learning and Random Forests; ML 115: Dimensionality Reduction; ML 116: k-Means Clustering)
• Attacks (ML 106: Data Poisoning; ML 107: Evasion Attack with SecML; ML 108: Evasion Attack on MNIST dataset; ML 109: Poisoning Labels with SecML; ML 110: Poisoning by Gradients; ML 111: Poisoning the MNIST dataset)
• Defenses (ML 140: Deep Neural Rejection)
• Large Language Models (ML 120: Bloom LLM; ML 121: Prompt Engineering Concepts; ML 122: Comparing LLMs on Colab; ML 123: Running Llama 3 Locally; ML 124: Evaluating an LLM with Trulens; ML 126: Building RAGs; ML 127: Encoding Text with BERT; ML 128: Using AnythingLLM to Embed Custom Data; ML 129: Embedding Words with BERT)

Instructor

Sam Bowne has been teaching computer networking and security classes at City College San Francisco since 2000. He has given talks and hands-on trainings at DEF CON, DEF CON China, Black Hat USA, HOPE, BSidesSF, BSidesLV, RSA, and many other conferences and colleges. He founded Infosec Decoded, Inc., and does corporate training and consulting for several Fortune 100 companies, on topics including Incident Response and Secure Coding.

Formal education: B.S. and Ph.D. in Physics Industry credentials:

Infosec: CISSP, Certified Ethical Hacker, Security+, Defcon Black Badge, Splunk Core Certified User
Networking: Network+, Certified Fiber Optic Technician, HE IPv6 Sage, CCENT, IPv6 Forum Silver & Gold, Juniper JN0-101, Wireshark WCNA
Microsoft: MCP, MCDST, MCTS: Vista

Intro to Data Analytics and Visualization

Week 1: Tuesday, December 10 – Thursday December 12, 10:00 AM – 1 PM; 2 PM – 6:30 PM ET

Description

Data Analytics is a hot topic these days.  Skills such as data analysis, transformation and visualization are essential skills in almost every profession.  Data literacy is not only a skill for top data scientists; It is a must-have skill for almost everyone. This workshop is an introductory session to the world of Data Analytics and Data Visualization.  It is a brief overview of the Fundamentals of Data Analytics and Programming course offered to undergraduate students at the Maricopa Community Colleges, using the textbook “Data Analytics Made Easy” by Andrea De Mauro.  Elements of Tableau’s Desktop Fundamentals course will also be presented. Participants of the workshop will gain hands-on experience using leading data visualization tools Power BI and Tableau.  There will be instructor-led walkthroughs and hands-on labs using both tools.

Objectives

At the completion of this track, the participants will be able to…

• Install Power BI Desktop and Tableau Desktop.
• Understand Power BI and Tableau operations and terminology.
• Data cleanse and prepare datasets for Power BI and Tableau.
• Visualize data through reports and views.
• Create dashboards and storyboards using Power BI and Tableau.

Pre-requisites

• Open mind and eager to learn.
• Basic Excel knowledge will be helpful.

Required Textbook

“Data Analytics Made Easy” by Andrea De Mauro;  “Tableau Desktop Fundamentals” by Tableau for Academics.  Both will be provided for free to workshop participants.

At-home Computer Requirements

• Strong internet connection
• For class interaction, a webcam is recommended but not required
• Prior to December 10, participants will need Power BI Desktop and Tableau Desktop installed.  Additional directions will be provided.

Please note that content is subject to change or modification based on the unique needs of the track participants in attendance.

Agenda

Tue, Dec. 10:

• Chapters 1-3, 6 De Mauro, Power BI
• Introductions
• Overview of course material used
• What is Data Analytics?
• Installation of Power BI Desktop: Getting Started with Power BI.  Connect to Data, Transform Data.
• Lab: Sales Dashboard Tutorial.

Wed, Dec. 11:

• Power BI + Tableau Desktop Fundamentals)
• Power Query
• Designing a Data Model
• Using DAX Calculations
• Design and Enhance Reports in Power BI Desktop
• Implement Advanced Data Visualizations in Power BI

Thurs, Dec. 12:

• Tableau Desktop Fundamentals
• Installation of Tableau Desktop
• Trailhead Configuring and Setting Up Data
• Foundations of Chart Visualization
• Common Charts in Tableau
• Project:  Sales Analysis
• Sorting and Grouping
• Calculations
• Maps
• Views and Customizations
• Tableau Story Boards
• Optional Project:  Bicycle Rider Dashboard

Instructor

Chris Santo is a Professor in the Mathematics, Computer Science and Engineering Division of Scottsdale Community College in Scottsdale, AZ, part of the Maricopa Community College District, where he teaches a variety of courses including Java Programming, Data Structures, Survey of Programming Languages, Precalculus, Data Analytics, Tableau, Power BI, and Data Analytics for Python.  Chris has taught Mathematics, Computer Science and Computer Information Systems courses for the Maricopa Community Colleges for 16 years.

Mr. Santo has 30 years of experience in industry, holding various roles in computer lab management, systems administration, project management, database development, application development and IT management.

Using Generative AI Tools with Prompt Design for Classrooms

Week 2: Tuesday, December 17 – Thursday December 19, 10:00 AM – 1 PM; 2 PM – 6:30 PM ET

Description

This course will cover the basics of Generative AI (Gen AI) concepts and how generative models work in different applications. Fundamentals of different Large Language Models (LLM) and training methods used will be discussed. To have a good output from LLM based Generative AI tools, the user requires technique and knowledge of proper prompting to get the desired output. Prompt Engineering techniques, capabilities and limitations of LLM will be demonstrated and discussed with hands-on activities. In this workshop setting, participants will understand the concepts of Generative AI tools (ChatGPT, Gemini, Perplexity, etc.) and learn to use such tools using hands-on/demonstration activities for creating text, images, audio, and video content for classroom setting. Participants will also understand generative AI’s capabilities and limitations. Ethical consideration and use of such Gen AI tools in the classroom will also be discussed.

Objectives

• At the completion of this track, the participants will be able to…
• Understanding of how generative models functions and impact on education and in the classroom
• Learn to use generative AI tools with prompt design techniques for creating new content.
• Learn techniques to use such tools in the classroom effectively.

Pre-requisites

Open mind.

Required Textbook

None. The instructor will provide information to create accounts on different generative tools a week before the session starts. Free open-source tools will be used in this course.  Subscription based Gen AI tools will be demonstrated but are not required for students to purchase.

At-home Computer Requirements

Computer with High-Speed Internet Services is recommended. Most of the tools are in cloud and will require internet access.  Depending on the internet speed, some activities (mostly video related) may take time on your PC. Webcam and dual monitors recommended but not required.

Please note that content is subject to change or modification based on the unique needs of the track participants in attendance.

Agenda

Tue, Dec. 17:

• Introduction
• Course Overview (PPT)
• GenAI Tools – Account Setups
• What is AI and ML?
• What is GenAI? Hands-on Activities – ChatGPT/Gemini (Text -Text)
• Hands-on Activities – ChatGPT/Gemini (Text -Text). Use of tools in higher
  education.

Wed, Dec. 18

• Prompt Engineering Advanced
• Hands-On Activities – ChatGPT, Gemini, Claude, Perplexity, CoPilot (using
  effectively and ethically in the classroom)
• Hands-On Activities. Ethical usage in Higher Education

Thurs, Dec. 19

• Image/Video/Audio/Podcast
  GenAI Tools – Account Setups
• Text to Image/Video/Audio concepts. Copyright of new content limitations.
• Hands-On Activities – Text to Image/Video/Audio; Image to Image,
• Hands-on Activities – Image/Video/Audio (Create 3 assignments of using
  Image/Video/Audio for your class)

Instructor

Dr. Rajiv Malkan is a Professor in the Computer and Information Technology Department of Lone Star College – Montgomery in Houston, TX, where he teaches a variety of courses including Business Computer Applications, Programming Languages and Business and Management.

Dr. Malkan has over 30 years of leadership contributions in higher education within multiple settings. He has engaged in leadership roles including Founding Dean, Division Chair in transforming education. His involvement in driving key initiatives spans education delivery, thought leadership, grant writing, global partnerships and engagements on emerging trends. He has proven expertise in college accreditation & state compliance, including Dual Credit/Pathways initiatives for academic & workforce programs.

Dr. Malkan’s academic credentials include two master’s degrees, a doctorate in Higher Education Leadership, and he was the recipient of the prestigious Kellogg Fellowship in Leadership Development. He is active in various professional organizations and is continuing his ambitions in cyber security and incorporating data driven decision-making in higher education organizations. He presents at various conferences on data analytics and while executes on awarded grants, serving in community colleges and corporate education.

AI for Instructors

Week 2: Tuesday, December 17 – Thursday December 19, 10:00 AM – 1 PM; 2 PM – 6:30 PM ET

Description

This intensive three-day workshop introduces instructors to the rapidly evolving fields of Artificial Intelligence (AI) and Machine Learning (ML). Designed to equip educators with essential knowledge and practical skills, it focuses on integrating AI technologies into your curriculum and preparing students for emerging industry demands. Participants will gain confidence in incorporating AI concepts and tools into their teaching, regardless of their prior programming experience. You’ll leave with practical strategies to enhance your curriculum and better prepare your students for the future AI-integrated landscape.

Objectives

• Explain fundamental AI concepts, including machine learning, neural networks, and algorithms, along with their real-world applications across business operations and industrial processes
• Effectively use common AI tools and platforms in an educational context
• Identify and articulate both the potential and limitations of AI in teaching and learning

Pre-requisites

None, but some Python experience is recommended

Textbook

None

At-home Computer Requirements

Broadband internet connection, microphone, and tablet, PC, or laptop required.  Webcam and dual monitors recommended but not required.

Please note that content is subject to change or modification based on the unique needs of the track participants in attendance.

Agenda 

Tue, Dec. 17:

• Introduction to Artificial Intelligence
  Overview of AI Applications
• Demystifying AI: Concepts and Terminology
  Introduction to Python for AI
  Overview of AI Algorithms
• Introduction to Deep Learning

Wed, Dec. 18:

• Introduction to Generative AI
• Basics of Prompt Engineering
• AI in the Classroom
• Implementing AI in the Curriculum
• Ethics of AI

Thurs, Dec. 19:

• AI Tools for Instructors
• Data Analytics and Visualization for AI
• Computer Vision
• Limitations of AI
• Emerging Trends and Opportunities

Instructor

Wade Huber is a computer science faculty member at Chandler-Gilbert Community College, where he recently contributed to developing the college’s Artificial Intelligence bachelor’s degree program. With over 25 years of experience as a software engineer and 20 years teaching at the community college level, Wade brings a wealth of practical knowledge to the classroom. His extensive background spans software engineering in the telecommunications, semiconductor, and medical device manufacturing industries, providing him with practical insights into AI applications across various sectors. Wade holds a B.S. from Trinity University and an M.S. in Computer Science from The University of Texas at Dallas.

Introduction to Containers and Microservices

Week 2: Tuesday, December 17 – Thursday December 19, 10:00 AM – 1 PM; 2 PM – 6:30 PM ET

Description

Introduction to Containers and Microservices class provides participants with essential skills and knowledge in microservices architectures, focusing on containerization. Through lectures and hands-on labs, participants will learn the core concepts of container runtimes, storage, networking, and the automation of deployment processes.

Objectives

• Understand the concept of containers and their role in modern software development.
• Summarize the container lifecycle
• Implement container best practices and collaboration tools

Pre-requisites

Linux basics and Virtualization basics

Required Textbook

It will be provided

At-home Computer Requirements

Required: A computer with a minimum of 8GB of RAM

Ideal: A virtual machine with Linux “Fedora Server” with at least 2CPUs, 4GB of RAM, and a 40GB hard drive. Set-up directions will be provided after registration closes; Webcam and dual monitors recommended but not required

Please note that content is subject to change or modification based on the unique needs of the track participants in attendance.

Agenda

Tue, Dec. 17:

• Module 0 – Ways of Working
• Module 1 – Introduction to microservices
• Module 2 – Installation and commands
• Module 3 – Container Images
• Q&A

Wed, Dec. 18

• Module 4 – Container Files
• Module 5 – Storage
• Module 6 – Networking
• Q&A

Thurs, Dec. 19:

• Module 7 – Logging & Monitoring
• Module 8 – Orchestration
• Q&A

Other topics this track will cover include:

• Differentiate between containers and virtual machines and understand their benefits and use cases.
• Install and configure container runtime engines, such as Docker or Podman.
• Create and manage container images using Dockerfile or equivalent methods.
• Manage container networks and establish communication between containers.
• Utilize container orchestration tools like Docker Compose or Kubernetes to manage multi-container applications.
• Mount volumes and manage persistent storage within containers.
• Monitor container performance and troubleshoot common container-related issues.
• Explore container registries and understand their role in image distribution and management.
• Collaborate with teammates using container sharing and collaboration techniques.
• Understand the concepts of container orchestration and scalability.

Instructor

Professor Juan Medina is a seasoned IT professional and educator with over 20 years of experience in the technology industry. He has been teaching Linux successfully at Collin College since 2019, where he also developed a cutting-edge Cloud course focusing on Containers and Microservices. His professional career spans work with major organizations such as Red Hat (Currently Ansible Solutions Architect), IBM, Dell, and Perot Systems. He is well known for his creativity, proactive approach, and sense of responsibility. Professor Medina specializes in designing, implementing, maintaining, and troubleshooting Linux and Unix infrastructure environments and specializes in Ansible Automation Enterprise solutions.