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September 21 through November 2, 2024. Six Saturdays 1:30-4:30pm (9/21, 9/28, 10/5, 10/19, 10/26, 11/2). The IEEE North Jersey Section Communications Society Chapter is offering a course entitled "DEEP LEARNING WITH APPLICATIONS". Deep learning is a transformative field within artificial intelligence and machine learning that has revolutionized our ability to solve complex problems in various domains, including computer vision, natural language processing, and reinforcement learning. This hands-on course on deep learning is designed to provide students with an understanding how these amazing successes are made possible by drawing inspiration from the way that brains, both human and otherwise, operate. Students will gain a comprehensive foundation in the principles, techniques, and applications of deep neural networks. Learning how to solve real data-set based applications will teach students how to really apply deep learning with Python programming software. Participants will be asked to design and train deep neural networks to perform tasks such as image classification using commonly available data sets. However, participants are encouraged to apply the techniques from this course to other data sets according to their interests. Discuss with the instructor in order to propose your own project. More importantly, this will set the foundations for understanding and developing Generative AI applications. The IEEE North Jersey Section's Communications Society Chapter can arrange for providing IEEE CEUs - Continuing 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 Co-sponsored by: Education Committee Speaker(s): Thomas Long, Agenda: 1. Introduction to Neural Networks: Explore the fundamental concepts of artificial neural networks, backpropagation, activation functions, and gradient descent, laying the groundwork for deep learning understanding. 2. Introduction to PyTorch: Learn how to implement and train neural networks using PyTorch one of the most popular deep learning frameworks. Understand tensors. 3. Computer Vision Applications: Apply deep learning to computer vision problems, including image classification and object detection using Convolutional Neural Networks (CNNs) 4. Training and Optimizing Deep Neural Networks: Study techniques for training deep neural networks effectively, including optimization algorithms, weight initialization, regularization, and dropout. 5. Sequential Data Analysis: Explore how deep learning is used to analyze sequential data using Recurrent Neural Networks (RNNs). In particular, explore how neural networks are used in Natural Language Processing (NLP) tasks such as sentiment analysis and machine translation. 6. Generative AI: Overview of generative ai techniques that leverage the patterns present in a dataset to generate new content. Applications of generative ai include large language models such as ChatGPT and image generation models such as Midjourney and Stable Diffusion. This course assumes a basic understanding of machine learning concepts and programming skills in Python. Familiarity with linear algebra and calculus will be beneficial, but not mandatory. Statistical software (Python, Scikit-learn) and Deep Learning Frameworks (Pytorch, TensorFlow) will be used throughout the course for the exploration of different learning algorithms and for the creation of appropriate graphics for analysis. Learning objectives: Subjects covered include these and other deep learning related materials: artificial neural networks, training deep neural networks, RNN, CNN, image recognition, natural language processing, GANs, data processing techniques, and NN architectures. The course is intended to be subdivided into 3-hour sessions. Each lecture is further subdivided into lecture, guided and independent project based exercises to build experience with hands-on techniques. This course will be held at FDU - Teaneck, NJ campus. Checks should NOT be mailed to this address. Can bring checks in person or use online payments at registration. Email the organizer for any questions about course, registration, or other issues. Technical Requirements: Students will need access to the Python programming language. In addition to a standard Python installation, most programming exercises will use the package Scikit-learn. Basic programming skills and some familiarity with the Python language are assummed. Students are expected to be able to bring a laptop onto which most of these libraries can be pre-installed using python's pip install. Most of the coding in this course will use the Python programming language. Coding examples and labs will be distributed in the form of Juypter notebooks. In addition to standard Python, most programming exercises will use either the PyTorch or TensorFlow libraries. Books and other resources will be referenced. Room: Room 306, Bldg: Becton Building , FDU Metropolitan Campus, 960 River Road, Teaneck, New Jersey, United States, 07666

[] Thank you to our Corporate Sponsors! https://www.cnf.cornell.edu/events/nys_nano/2024 On Friday, Sept 27th, RIT will host the New York State Nanotechnology Network (NNN) Symposium geared toward connecting NYS undergraduate and graduate students with our NYS industry partners for the purpose of learning about and discussing "Growing the Semiconductor Workforce." The day will include a morning session with student, government, and industry talks, and an afternoon Poster Session & Career Fair! The goal of this Career Fair-themed symposium is to showcase the NYS student workforce talent pipeline and to bring together universities and industries to exchange information and to present technology research activities in and around NYS. Come and network with us. Find the great employees you were looking to hire -- or find your dream job! This event also coincides with the IEEE EDS Activities in Western New York Conference, marking the 44th event! STUDENTS: Plan to submit a nano-research-related abstract by August 21st to be part of this showcase for New York State students. Abstract submission website: https://www.cnf.cornell.edu/events/nys_nano/2024/abstracts CLOSED Career Fair CV/Resume submission: (https://cornell.app.box.com/f/e16d751e68104980937403338787e968) NYS COMPANIES: Become a symposium sponsor to participate in the symposium, student showcase, and Career Fair. Sponsor website: https://www.cnf.cornell.edu/events/nys_nano/2024/sponsorships Find out what is new in the Semiconductor Industry, nanotechnology, and workforce needs in New York State! Co-sponsored by: New York State Nanotechnology Network (NNN) Speaker(s): Scott Bukofsky, Nicole Kerness, Lisa Fritz, Panel Session on Workforce Development Agenda: 2024 NNN Symposium "Growing the NYS Semiconductor Workforce" Student Hall for Exploration and Development (SHED), Room 3350 Rochester Institute of Technology Agenda: 8:30-9:00 a.m. Registration & Continental Breakfast 9:00 a.m. Welcome Remarks - Karl Hirschman, RIT - Ron Olson, CNF 9:15-10:30 a.m. Invited Keynote Speakers - Session chair: Ross Goodman, U Albany - 9:15 - 9:40 "CHIPS R&D and Workforce Programs for Sustained U.S. Leadership" - Scott Bukofsky, Director of Capabilities for the CHIPS National Semiconductor Technology Center, Department of Commerce - 9:40 - 10:05 "Inventing the Ideal Ohmic Switch" - Nicole Kerness, Senior Director, Process Engineering and Integration, Menlo Micro - 10:05 - 10:30 "Silicon Carbide – Transforming the Semiconductor and Automotive Industries with the Power to Make it Real" - Lisa Fritz, Senior Vice President of Global Quality, Wolfspeed 10:30-11:00a.m. Coffee break & poster set-up 11:00-12:30p.m. Student oral presentations - Session chair: Nava Ariel, Columbia University 12:30-1:15p.m. Lunch + Poster Preview 1:15-1:40p.m. Invited talk (Micron) - T.B.D. 1:45-3:15p.m. Workforce Development Panel Session - Michael Jackson, RIT (moderator) - Dan Dechene, IBM Research - Andrew Seward, TEL - Scott Bukofsky, Department of Commerce - Nicole Kerness, Menlo Micro - Ida Habtemichael, Micron - Lisa Fritz, Wolfspeed - Keith Tabakman, GlobalFoundries 3:15-5:00p.m. Poster Session & Sponsor Career Fair - Note: Poster judging ends at 4:30p.m. 5:00p.m. Closing remarks 5:15p.m. Student awards and group photograph 5:30p.m. Adjourn Room: 3350, Bldg: Student Hall for Exploration and Development (SHED) , Rochester Institute of Technology, One Lomb Memorial Drive, Rochester, New York, United States, 14623

Co-sponsored by: SIGHT Agenda: Agenda Roof Top Meet Up Social at Bar Bella at Bellworks in Holmdel, New Jersey 27 September 2024 5pm to 10pm Bring a guest. Join the group for a Roof Top Meet Up Social at Bar Bella. Bring a guest. Bell works , holmdel, New Jersey, United States, 07733

Kick-off meeting to celebrate the new IEEE Student Branch formed at SUNY Oswego. Refreshments will be provided. Room: 170, Bldg: Richard S. Shineman Center, Oswego, New York, United States, 13126