Fall 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. 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.
2. Mandatory Survey: All attendees are required to complete a survey before the end of the event.
3. Certificate of Completion: Only those who attend every session are eligible to receive a Certificate of Completion. Instructors will call roll every morning and afternoon.
4. Track Capacity: Seating capacity varies by track and instructor, but typically, tracks are capped at 20 attendees.

AWS Academy Cloud Developing

Saturdays, October 5th – November 2nd from 11am-6pm ET

Description  

The AWS Academy Cloud Developing course is designed to help students gain technical expertise in development with cloud technologies. The curriculum is delivered through instructor-led or digital lectures, demos, activities, knowledge checks, and hands-on labs. Throughout the course, students will explore a scenario that provides opportunities to build a variety of infrastructures through a guided, hands-on approach. Students have access to lecture materials, online knowledge checks, and hands-on labs. 

This course helps you to prepare for the AWS Certified Developer Associate Exam and Certification.   

Objectives 

• Summarize key AWS Cloud and AWS Services, from a programmatic and development perspective.  
• Understand AWS Canvas LMS, and best practices on how to teach this specific course and certification 
• Identify how best to approach the Developer Associate Certification questions and exam, in an effort to eventually gain the AWS Certified Developer Associate certification.

Pre-requisites  

Students are advised, but not required, to have completed the AWS Academy Cloud Foundations course, and/or have already obtained the AWS Certified Cloud Practitioner Certification before this course.   

Students are advised, but not required, to have completed the AWS Academy Cloud Architecting course, and/or have already obtained the AWS Certified Solutions Architect Associate Certification before this course.  

Textbook information  

None required. (Some recommendations will be made during the course for future reference).  

Computer Needs 

Participants will need access to an internet connection to connect via Zoom or WebEX for the duration of the sessions. Participants will be created and provided access to the AWS Academy course in the Canvas Platform. 

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

Agenda

Week 1 – Introduction to AWS Cloud Developing (October 5)

• Module 0 – Welcome and Overview
• Module 1 – Welcome to AWS Academy Cloud Developing
• Module 2 – Introduction to Developing on AWS 

Week 2 – Developing Storage and NoSQL Solutions (October 12)

• Module 3 – Developing Storage Solutions
• Module 4 – Securing Access to Cloud Resources
• Module 5 – Developing Flexible NoSQL Solutions 

Week 3 – Developing REST APIs, Serverless, and Container solutions (October 19)

• Module 6 – Developing REST APIs
• Module 7 – Developing Event-Driven Serverless Solutions
• Module 8 – Introducing Containers and Container Services 

Week 4 – Developing for Scalability, Messaging, and Orchestration (October 26)

• Module 9 – Caching Information for Scalability
• Module 10 – Developing with Message Services
• Module 11 – Defining Workflows to Orchestrate Functions 

Week 5 – Developing for Security and Automation (November 2)

• Module 12 – Developing Secure Applications on AWS 
• Module 13 – Automating Deployment Using CI/CD Pipelines 
• Module 14 – Bridging to Certification 

Instructor

Asad Khan

Mr. Asad Ahmad Khan, MSIT is a Full Time Lecturer of Information Technology at Georgia Gwinnett College, part of the University System of Georgia. He is the former Program Director of the Networking Specialist program and Dean Liaison in the Computer Sciences Division at Gwinnett Technical College, where he served for almost 3 years in these roles, until July 2024. He currently teaches as a Part Time Faculty of Computer Sciences and AWS at Gwinnett Tech still. He has built and taught four different AWS courses for Gwinnett Tech, as an AWS Accredited Educator. He has taught AWS certification prep courses to students from across Georgia’s technical college system, state employees across Georgia’s state agencies, and instructors in the CCN for the last four years. He managed the AWS, CompTIA, and Microsoft Learn Academies for the college as well. He currently possesses 31 certificates in IT, including 16 in Cloud Computing (AWS, Azure, Google Cloud, CompTIA, and Oracle Cloud).  

AI Foundations Workshop

Fridays, October 4th – November 15th

• Half Days 2PM-6PM Eastern: 10/4, 10/18, 11/1, 11/15
• Full Days: 11AM-6PM Eastern: 10/11, 10/25, 11/8

Description

This immersive workshop explores the rapidly evolving fields of Artificial Intelligence (AI) and Machine Learning (ML), equipping educators with the knowledge and skills to integrate these technologies into your curriculum and prepare students for emerging industry demands. We will cover data preparation, classification algorithms, deep learning, image processing, and natural language processing. We will discuss the AI project lifecycle, from problem formulation to deployment Additionally, the course will provide a thorough overview of essential Python operations, making it accessible even to those without prior programming knowledge. Several AI tools will be introduced, including ChatGPT, Midjourney, Copilot, Claude, and many others.

Objectives

• Understand the scope and significance of Artificial Intelligence (AI), including its ethical, legal, and societal implications.
• Distinguish between and apply AI algorithms such as decision trees, clustering, and supervised, unsupervised, and reinforcement learning techniques,
• Understand the AI project lifecycle, from problem formulation to deployment, incorporating Machine Learning algorithms and Deep Learning methodologies.
• Explore AI applications across multiple domains, including Data Analytics, Computer Vision, Natural Language Processing, and Cybersecurity.
• Proficiently utilize and evaluate popular AI tools such as ChatGPT, GitHub Copilot, Teachable Machine, and Claude for educational and practical purposes.

Pre-requisites

• A Google account
• Beginner-level Python programming (conditionals, loops, using libraries) is recommended but not required.

Textbook

None

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

Agenda

Week 1 (October 4, Half Day)

• Introduction to Artificial Intelligence
• Overview of AI Applications
• Introduction to Python

Week 2 (October 11, Full Day)

• Demystifying AI
• AI Concepts and Terminology
• Algorithms for AI – Supervised learning techniques, decision trees, & clustering
• AI Ethics and Responsible Development

Week 3 (October 18, Half Day)

• Considering the Impact of AI
• Introduction to Generative AI
• Basics of Prompt Engineering

Week 4 (October 25, Full Day)

• Limitations of AI
• Algorithms for AI (Part 2) – Unsupervised learning techniques, reinforcement learning
• Data Preparation and Preprocessing for AI
• Data Analytics

Week 5 (November 1, Half Day)

• AI in the Classroom
• Data Visualization for AI

Week 6 (November 8, Full Day)

• Philosophy of AI
• Introduction to Deep Learning
• Deep Learning Applications

Week 7 (November 15, Half Day)

• AI Ethics, Legal Considerations, and Societal Impact
• Computer Vision
• Industrial Applications of AI (Robotics, Chatbots)
• The Future with AI

Instructor

Wade Huber

Wade Huber is a residential computer science faculty member at Chandler-Gilbert Community College, where he recently served on the committee developing CGCC’s Artificial Intelligence bachelor’s degree. He has over 25 years of experience as a software engineer in the telecom, semiconductor, and medical device manufacturing industries. During this time, he taught math and computer science as an adjunct professor. He holds a Bachelor of Science from Trinity University in San Antonio, TX, and a Master of Science in Computer Science from The University of Texas at Dallas.

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, September 27.

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.