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STEM (SCIENCE, TECHNOLOGY, ENGINEERING, AND MATH) DLI WORKSHOP

Fundamentals of Deep Learning

Businesses worldwide are using artificial intelligence to solve their greatest challenges. Healthcare professionals use AI to enable more accurate, faster diagnoses in patients. Retail businesses use it to offer personalized customer shopping experiences. Automakers use it to make personal vehicles, shared mobility, and delivery services safer and more efficient. Deep learning is a powerful AI approach that uses multi-layered artificial neural networks to deliver state-of-the-art accuracy in tasks such as object detection, speech recognition, and language translation. Using deep learning, computers can learn and recognize patterns from data that are considered too complex or subtle for expert-written software.

In this workshop, you’ll learn how deep learning works through hands-on exercises in computer vision and natural language processing. You’ll train deep learning models from scratch, learning tools and tricks to achieve highly accurate results. You’ll also learn to leverage freely available, state-of-the-art pre-trained models to save time and get your deep learning application up and running quickly.

This course is only available to students and faculties, please register with .edu email or provide your student/relevent ID.

Fundamentals of Deep Learning

By participating in this workshop, you’ll:

Learn the fundamental techniques and tools required to train a deep learning model
Gain experience with common deep learning data types and model architectures
Enhance datasets through data augmentation to improve model accuracy
Leverage transfer learning between models to achieve efficient results with less data and computation
Build confidence to take on your own project with a modern deep learning framework

Introduction (15 mins)	Meet the instructor. Create an account at courses.nvidia.com/join
The Mechanics of Deep Learning (120 mins)	Explore the fundamental mechanics and tools involved in successfully training deep neural networks: Train your first computer vision model to learn the process of training. Introduce convolutional neural networks to improve accuracy of predictions in vision applications. Apply data augmentation to enhance a dataset and improve model generalization.
Break (60 mins)
Pre-trained Models and Recurrent Networks (120 mins)	Leverage pre-trained models to solve deep learning challenges quickly. Train recurrent neural networks on sequential data: Integrate a pre-trained image classification model to create an automatic doggy door. Leverage transfer learning to create a personalized doggy door that only lets in your dog. Train a model to autocomplete text based on New York Times headlines.
Break (15 mins)
Final Project: Object Classification (120 mins)	Apply computer vision to create a model that distinguishes between fresh and rotten fruit: Create and train a model that interprets color images. Build a data generator to make the most out of small datasets. Improve training speed by combining transfer learning and feature extraction. Discuss advanced neural network architectures and recent areas of research where students can further improve their skills.
Final Review (15 mins)	Review key learnings and answer questions. Complete the assessment and earn a certificate. Complete the workshop survey. Learn how to set up your own AI application development environment.

Workshop Details

Language: English and Indonesia Bahasa

Duration: 8 hours

Prerequisites: An understanding of fundamental programming concepts in Python 3, such as functions, loops, dictionaries, and arrays; familiarity with Pandas data structures; and an understanding of how to compute a regression line. Suggested materials to satisfy prerequisites: Python Beginner’s Guide.

Technologies: Tensorflow 2 with Keras, Pandas

Assessment Type: Skills-based coding assessments evaluate students’ ability to train a deep learning model to high accuracy.

Certificate: Upon successful completion of the assessment, participants will receive an NVIDIA DLI certificate to recognize their subject matter competency and support professional career growth.

Hardware Requirements: Desktop or laptop computer capable of running the latest version of Chrome or Firefox. Each participant will be provided with dedicated access to a fully configured, GPU-accelerated server in the cloud.

DLI Ambassador

Tjeng Wawan
Cenggoro

BINUS University

Gregorius
Natanael
Elwirehardja

BINUS University

Ir. Andry
Chowanda

BINUS University

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Tjeng Wawan Cenggoro

DLI Ambassador, Bina Nusantara University

Wawan is an AI researcher whose focus is on the development of Deep Learning algorithms. He has led several research projects that utilize Deep Learning for Computer Vision, which is applied to various cases such as indoor video analytics and plant phenotyping. He has published over 50 peer-reviewed publications and reviewed for prestigious journals such as Scientific Reports and IEEE Access. He also holds 2 copyrights for AI-based video analytics software.

Bina Nusantara University

Bina Nusantara University, also known as BINUS University, is one of the best private higher education institutions in Indonesia. BINUS was awarded the title of “The Top 1 Private University in Indonesia” in the QS World University Rankings 2021 and included among “The Top 250 Universities” in the QS Asia University Rankings. With numerous awards under their belt, they have strived to develop the nation and build a global community through education and technology for many decades, mainly centralizing on the fields of Information Technology (IT). The journey of BINUS started back in 1974 as a computer course, until they are formally recognized as a private university in 1996. They then expanded and included other majors into their education programs. Throughout the years, more IT-related higher education majors were opened, including Cyber Security, Mobile Application & Technology, Game Application & Technology, and even Data Science. In 2017, BINUS finally established their own Artificial Intelligence Research & Development Center (AIRDC) in collaboration with NVIDIA and TechData. Through the AIRDC, many AI-related research have been conducted in various fields as an attempt to realize one of the many missions of BINUS, which is “Resolving the nation’s issues through high-impact research”. These fields of research include applications of AI and data science in agriculture, medical, genomics, proteomics, meteorology, video analytics, and many more.

Ir. Andry Chowanda

DLI Ambassador, Bina Nusantara University

Andry Chowanda is a Computer Science senior lecturer and Deputy Dean of the School of Computer Science at Bina Nusantara University, Indonesia. He received his Ph.D. degree in Computer Science from The University of Nottingham UK, a master’s degree in Business Management from BINUS Business School ID, and a bachelor’s degree in Computer Science from BINUS University ID. His research is in agent architecture and Machine (and Deep) Learning. His works mainly focus on how to model an agent that has the capability to sense and perceive the environment and react based on the perceived data in addition to the ability to build a social relationship with the user over time. In addition, Andry is also interested in serious games and gamification design.

Bina Nusantara University

Gregorius Natanael Elwirehardja

DLI Ambassador, Bina Nusantara University

As an AI researcher, Gregorius Natanael Elwirehardja have explored the usages of both conventional machine learning and deep learning in various fields. Currently, he is a researcher of NVIDIA-BINUS Artificial Intelligence Research & Development Center and a certified instructor of NVIDIA Deep Learning Institute. His research interests include applied machine learning in various fields including, but are not limited to, computer vision, mental health, and Natural Language Processing.

Bina Nusantara University

Fundamentals of Deep Learning

Fundamentals of Deep Learning

Workshop Details

DLI Ambassador

Tjeng Wawan
Cenggoro

Gregorius
Natanael
Elwirehardja

Ir. Andry
Chowanda

感謝大家踴躍報名，已提前額滿，會再另外用電子郵件通知報名成功訊息！

PERSONAL INFORMATION

NVIDIA GEFORCE RTX LAPTOPS FOR STEM MAJORS

Tjeng Wawan Cenggoro

Ir. Andry Chowanda

Gregorius Natanael Elwirehardja

Fundamentals of Deep Learning

Fundamentals of Deep Learning

Workshop Details

DLI Ambassador

Tjeng WawanCenggoro

GregoriusNatanaelElwirehardja

Ir. AndryChowanda

感謝大家踴躍報名，已提前額滿，會再另外用電子郵件通知報名成功訊息！

PERSONAL INFORMATION

NVIDIA GEFORCE RTX LAPTOPS FOR STEM MAJORS

Tjeng Wawan Cenggoro

Ir. Andry Chowanda

Gregorius Natanael Elwirehardja

Tjeng Wawan
Cenggoro

Gregorius
Natanael
Elwirehardja

Ir. Andry
Chowanda