This course is given in collaboration with NVIDIA Deep Learning Institute and AI Lab
Artificial Intelligence (AI), and Deep learning (DL) in particular, is transforming every industry.
With major breakthroughs in computer vision, natural language processing, speech recognition
and autonomous driving, deep learning has become the hottest topic in Artificial Intelligence.
We have reached a crucial moment where deep learning and high performance computing are
converging to deliver on promises made by big data. In this course, we will explore the
fundamentals of deep learning and discuss the current trend of this fast moving field, including
the latest on various DL software frameworks and HPC hardware/cloud platforms. Following the
success stories of applying deep learning to computer vision, natural language processing,
intelligent, and multiple data types, course participants will gain hands-on experience training
deep neural networks and using results to improve performance and capabilities. Upon
completion, attendees will be able to solve their own problems with deep learning. Participants
will also have the chance to receive an NVIDIA DLI certificate to recognize their subject matter
competency and support professional career growth.
This course is designed to empower you to jumpstart AI and gain the needed hands-on skills
and expertise to leverage this technology in order to solve the world’s most challenging
problems. Learn to build deep learning applications for industries such as autonomous
vehicles, finance, game development, healthcare, robotics, and more.
Course Target Group
- Fresh Graduates entering the job market.
- Developers who aim to learn today’s most sought after skill
- Software Engineers who seek to advance their careers with the state-of the art AI
- Data Scientists and researchers who want to solve challenging problems with AI
- Technology leaders who want to stay ahead of the competition by empowering their
companies with AI
- IT consultants
- Digital Transformation Specialists
|Module 1 Fundamentals of Deep Learning||This module will teach you the fundamentals of deep learning through theory and direct, hands-on experience. It will prepare you to take on your own deep learning project using a modern Python framework and help you identify what type of model architecture and deep learning approach you should use. You will learn the fundamental mechanisms of deep learning training and the key types of data and model architectures. You will also learn how to use data augmentation methods to improve your datasets and how to apply transfer learning to achieve efficient results. Finally, you will learn how to combine different types of models to achieve a complex goal and how to build real applications by combining deep learning with traditional programming.|
|Module 2 Natural Language Processing with Transformer-Based Models||In this module, you will first learn how text embedding has rapidly evolved in NLP tasks such as Word2Vec, recurrent neural network (RNN)-based embedding, and Transformers. Then you’ll learn how to use natural language processing (NLP) Transformer-based models for text- classification tasks, such as identifying specific types of articles within a large library of articles or abstracts. You’ll also learn how to leverage Transformer-based models for named-entity recognition (NER) tasks and how to analyze various model features, constraints, and characteristics to determine which is best suited for a particular use case based on metrics, domain specificity, and available resources. Finally, you will get practical experience in how to manage inference challenges to deploy refined models for live applications.|
Course Instructional Methodology
This course is designed to provide participants with a hands-on online AI training. Students will
have access to the fully-configured NVIDIA platform equipped with GPUs in the cloud
throughout the course. A combination of presentations, discussions, and hands-on labs will be
used in each session to engage the students in an exciting learning experience.
Every module of the course will be terminated by an online assessment where students will
demonstrate their competencies in the subject matter learned. Guidance and feedback from
the instructor will be provided on each exercise, discussion, and assessment in a way to
enable participants to identify their weaknesses and capitalize on their weak points.
Course Instructor: Dr. Manal Jalloul
Dr. Manal Jalloul is an Artificial Intelligence expert, keynote speaker, and entrepreneur. She is NVIDIA Deep Learning Institute's certified instructor and University ambassador striving to democratize AI education in the MENA region. She is also the co-founder and Chief Executive Officer of AI-Lab. AI Lab is an Artificial Intelligence consultancy and training company that provides specialized hands-on trainings and consulting services in the fields of Artificial Intelligence, Accelerated Computing, and Data Analytics to the industry. AI Lab is the certified delivery partner of NVIDIA DLI in EMEA. Through AI Lab, Dr. Jalloul strives to drive the adoption of AI among the startup ecosystem. Dr. Jalloul is a member of the advisory board of the International Group of Artificial Intelligence (IGOAI) serving as Lebanon's country advisor. She is also an executive member of the Global AI Ethics Institute expert team which aims to build a strong and fair global governance system for AI. Dr. Jalloul was named among NVIDIA's Top Distinguished Instructors for 2021. She is the recipient of ERSA/NVIDIA award for Best Young Enterpreneur in 2013 and Jammal Abdul Nasser Award for Academic Excellence in 2007. Dr. Jalloul is a public keynote speaker. She delivered keynote speeches, talks, and panel discussions about AI at international meetups and conferences.