BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT DTSTART:20250309T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20251102T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20250816T123747Z UID:1DBBB212-CD41-41F3-880C-D082A6D4A924 DTSTART;TZID=America/New_York:20250920T133000 DTEND;TZID=America/New_York:20251101T163000 DESCRIPTION:September 20 through November 1\, 2025. Six Saturdays 1:30-4:30 pm (9/20\, 9/27\, 10/4\, 10/18\, 10/25\, 11/1).\n\nThe IEEE North Jersey S ection Communications Society Chapter is offering a course entitled\n"Prac tical Generative AI: A Hands-On Introduction for Technical Professionals". \n\nThis six-week introductory course in Generative AI is designed for a t echnical audience\nwith no prior specialization in AI or machine learning. It provides a practical\,\nhands-on approach to understanding how generat ive models like large language models (LLMs)\nwork and how they can be app lied across tasks involving text\, code\, images\, and video.\n\nThe cours e begins with foundational concepts\, including the evolution of generativ e AI\,\nand moves into core mechanics such as tokenization\, transformers\ , and prompt engineering.\nParticipants explore both the capabilities and limitations of tools like ChatGPT\,\nGoogle Gemini\, GitHub Copilot\, and various APIs. The course will include some suggested\nprojects using freel y tools such as Gemini and AWS.\n\nEach week combines a lecture with inter active demos and assignments to reinforce learning\nthrough real-world use cases. The latter weeks focus on building simple GenAI-powered\napps and understanding limitations such as bias\, hallucinations\, and data privacy .\nThe course wraps up with future directions in AI and equips participant s with the skills\nto responsibly use and to integrate generative models i nto their own technical workflows.\n\nThe IEEE North Jersey Section's Comm unications Society Chapter can arrange for providing IEEE CEUs - Continuin g Education Units (for a $5 charge) upon completion of the course. Course prices: $75 for Undergrad/Grad/Life/ComSoc members\, $100 for IEEE members \, $150 for non-IEEE members\n\nCo-sponsored by: Education Committee\n\nSp eaker(s): Thomas Long\, \n\nAgenda: \nAgenda: The primary objective of thi s course is to provide students with an understanding of\nGen AI\, tools a nd techniques used\, the wide variety of applications\, and an Agentic fut ure.\nThe material covered includes an introduction to the concepts and ho w to build applications\nusing these concepts. On the completion of the co urse\, students will learn:\n\nWeek 1: Introduction to Generative AI\nGoal : Ground the audience in what Generative AI is\, its evolution\, and why i t matters.\nTopics:\nHistory of generative models (GANs → Transformers)\ , Multi-modal use cases\,\nOverview of LLMs\, Economics\, and Regulatory l andscape.\n\nWeek 2: How Generative AI Works\nGoal: Demystify the architec ture and inner workings of generative models.\nTopics:\nReview of deep neu ral networks and core ideas like: tokenization\, embeddings\,\nattention\, transformers\, how to train an LLM. What is the differences between\nFine -tuning vs. pretraining vs. prompt engineering\, and how to deal with\nhal lucinations\, biases\, context windows\n\nWeek 3: Building with Generative AI APIs\nGoal: Equip learners to integrate LLMs into real-world apps.\nTo pics:\nWhat are the key APIs available to use (OpenAI\, Google Gemini\, AW S\, HuggingFace)\,\nUsing and calling models with Python\, Building a simp le GenAI-powered app (chatbot)\nand what is prompt templating and chaining \n\nWeek 4: Prompt Engineering for Developers\nGoal: Learn effective promp ting strategies for real-world applications.\nTopics:\nDifferent types inc lude Zero-shot\, few-shot\, chain-of-thought prompting\,\nCommon prompt en gineering mistakes\, System messages and role prompts\, and\nCode generati on with LLMs (Copilot\, Gemini+Colab\, GPT-4)\n\nWeek 5: Image & Video Gen eration\nGoal: Broaden the view beyond text\; explore image and video synt hesis.\nTopics:\nHow to do image generation using diffusion models (DALL· E\, Midjourney\, Stable Diffusion)\nHow to do video generation using Googl e Veo\n\nWeek 6: Generative AI Agents and Autonomous Workflows\nGoal: Intr oduce AI agents\, their architecture\, and how they orchestrate autonomous tasks using LLMs.\nTopics:\nWhat are AI agents and how to agents use tool s\, memory\, and planning.\nReal world use cases: research assistants\, wo rkflow automation\, task chaining\nRisks and guardrails: failure cases\, c ost\, ethical boundaries\, and\nwhat is AGI and the alignment problem?\n\n Technical Requirements :\n\nAccess to a tool such as ChatGPT or Google Gem ini will be necessary to complete most examples\nusing prompts. Coding dem os in this course will use the Python programming language and will\nbe di stributed in the form of Colab notebooks. During the latter portion of the course\,\ncoding demos will make use of the Google Gemini APIs. These exa mples can easily be adapted\nto other frameworks such OpenAI APIs\, etc.\n \nBasic programming skills and some familiarity with the Python language a re assummed.\nStudents are expected to be able to bring a laptop in order to use Google Colab Notebooks.\n\nThe course is intended to be subdivided into six sessions\, each three hours long for a total of 18\ncourse hours. Each lecture is further subdivided into lecture\, guided and independent project based\nexercises to build experience with hands-on techniques. CEU s will be made available.\n\nThis course will be held at FDU - Teaneck\, N J campus. Checks should NOT be mailed to this address.\nCan physically bri ng (preferred) checks in person on the first day or use online payments at registration.\nEmail the organizer for any questions about course\, regis tration\, or other issues.\n\nRoom: Room TBD\, Bldg: Becton Building \, FD U Metropolitan Campus\, 960 River Road\, Teaneck\, New Jersey\, United Sta tes\, 07666 LOCATION:Room: Room TBD\, Bldg: Becton Building \, FDU Metropolitan Campus\ , 960 River Road\, Teaneck\, New Jersey\, United States\, 07666 ORGANIZER:a.j.patel@ieee.org SEQUENCE:27 SUMMARY:Practical Generative AI: A Hands-On Introduction for Technical Prof essionals URL;VALUE=URI:https://events.vtools.ieee.org/m/497080 X-ALT-DESC:Description:

September 20 through November 1\, 2025. Si x Saturdays 1:30-4:30pm (9/20\, 9/27\, 10/4\, 10/18\, 10/25\, 11/1).

\n

The IEEE North Jersey Section Communications Society Chapter is offerin g a course entitled
"Practical Generative AI: A Hands-On Introduction for Technical Professionals". \;

\n

This six-week introductory co urse in Generative AI is designed for a technical audience \;
with no prior specialization in AI or machine learning. It provides a practical \, \;
hands-on approach to understanding how generative models like large language models (LLMs) \;
work and how they can be applied a cross tasks involving text\, code\, images\, and video. \;

\n

The course begins with foundational concepts\, including the evolution of gen erative AI\, \;
and moves into core mechanics such as tokenization\ , transformers\, and prompt engineering. \;
Participants explore bo th the capabilities and limitations of tools like ChatGPT\, \;
Goog le Gemini\, GitHub Copilot\, and various APIs. The course will include som e suggested \;
projects using freely tools such as Gemini and AWS.< /p>\n

Each week combines a lecture with interactive demos and assignment s to reinforce learning \;
through real-world use cases. The latter weeks focus on building simple GenAI-powered \;
apps and understan ding limitations such as bias\, hallucinations\, and data privacy. \;< br>The course wraps up with future directions in AI and equips participant s with the skills \;
to responsibly use and to integrate generative models into their own technical workflows.

\n

The IEEE North Jersey Section's Communications Society Chapter can arrange for providing IEEE CE Us - Continuing Education Units (for a $5 charge) upon completion of the c ourse. \; Course prices: $75 for Undergrad/Grad/Life/ComSoc members\, $100 for IEEE members\, $150 for non-IEEE members



Agenda: < br />

Agenda: The primary objective of this course is to provide student s with an understanding of \;
Gen AI\, tools and techniques used\, the wide variety of applications\, and an Agentic future.
The material covered includes an introduction to the concepts and how to build applicat ions
using these concepts.  \;On the completion of the course\, stu dents will learn:

\n

Week 1: Introduction to Generative AI
Goal: G round the audience in what Generative AI is\, its evolution\, and why it m atters.
Topics:
History of generative models (GANs &rarr\; Transform ers)\, Multi-modal use cases\, \;
Overview of LLMs\, Economics\, an d Regulatory landscape.

\n

Week 2: How Generative AI Works \;
Goal: Demystify the architecture and inner workings of generative models.< br>Topics:
Review of deep neural networks and core ideas like: tokeniza tion\, embeddings\, \;
attention\, transformers\, how to train an L LM.  \;What is the differences between
Fine-tuning vs. pretraining vs. prompt engineering\, and how to deal with
hallucinations\, biases\, context windows

\n

Week 3: Building with Generative AI APIs
Goal: Equip learners to integrate LLMs into real-world apps.
Topics:
What are the key APIs available to use (OpenAI\, Google Gemini\, AWS\, Hugging Face)\,
Using and calling models with Python\, Building a simple GenAI- powered app (chatbot)
and what is prompt templating and chaining

\n< p>Week 4: Prompt Engineering for Developers
Goal: Learn effective promp ting strategies for real-world applications.
Topics:
Different types include Zero-shot\, few-shot\, chain-of-thought prompting\,
Common pro mpt engineering mistakes\, System messages and role prompts\, and
Code generation with LLMs (Copilot\, Gemini+Colab\, GPT-4)

\n

Week 5: Imag e &\; Video Generation
Goal: Broaden the view beyond text\; explore image and video synthesis.
Topics:
How to do image generation using diffusion models (DALL·\;E\, Midjourney\, Stable Diffusion)
How t o do video generation using Google Veo

\n

Week 6: Generative AI Agent s and Autonomous Workflows
Goal: Introduce AI agents\, their architectu re\, and how they orchestrate autonomous tasks using LLMs.
Topics:
W hat are AI agents and how to agents use tools\, memory\, and planning.
Real world use cases: research assistants\, workflow automation\, task cha ining
Risks and guardrails: failure cases\, cost\, ethical boundaries\, and \;
what is AGI and the alignment problem?

\n

Technical Re quirements :

\n

Access to a tool such as ChatGPT or Google Gemini wil l be necessary to complete most examples \;
using prompts. Coding d emos in this course will use the Python programming language and will  \;
be distributed in the form of Colab notebooks. During the latter por tion of the course\, \;
coding demos will make use of the Google Ge mini APIs. These examples can easily be adapted \;
to other framewo rks such OpenAI APIs\, etc. \;

\n

Basic programming skills and so me familiarity with the Python language are assummed.
Students are expe cted to be able to bring a laptop in order to use Google Colab Notebooks.< /p>\n

The course is intended to be subdivided into six sessions\, each t hree hours long for a total of 18 \;
course hours. Each lecture is further subdivided into lecture\, guided and independent project based&nbs p\;
exercises to build experience with hands-on techniques. \; CEUs will be made available.

\n

This course will be held at FDU - Teaneck \, NJ campus. \; Checks should NOT be mailed to this address. \; < br>Can physically bring (preferred) checks in person on the first day or u se online payments at registration. \;
Email the organizer \;f or any questions about course\, registration\, or other issues.

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