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Overview
Assessment type:
Skills-based coding assessments evaluate students’ ability to debug and correct production-quality recommendation pipelines.
Certificate:
Upon successful completion of the assessments, participants will receive an NVIDIA Deep Learning Institute certificate to recognize their subject matter competency and support professional career growth
- Access workshops from anywhere with just your desktop/laptop computer and an internet connection. Each participant will have access to a fully configured, GPU-accelerated workstation in the cloud.
- Obtain hands-on experience with the most widely used, industry-standard software, tools, and frameworks.
- Learn to build deep learning and accelerated computing applications for industries, such as healthcare, robotics, manufacturing, accelerated computing, and more.
- Gain real-world expertise through content designed in collaboration with industry leaders, such as the Children’s Hospital of Los Angeles, Mayo Clinic, and PwC.
- Earn an NVIDIA Deep Learning Institute certificate to demonstrate your subject matter competency and support your career growth.
Prerequisites
- Intermediate knowledge of Python, including understanding of list comprehension
- Data science experience using Python
- Familiarity with NumPy and matrix mathematics
Delegates will learn how to
- Build a content-based recommender system using the open-source cuDF library and Apache Arrow
- Construct a collaborative filtering recommender system using alternating least squares (ALS) and CuPy
- Design a wide and deep neural network using TensorFlow 2 to create a hybrid recommender system
- Optimize performance for both training and inference using large, sparse datasets
- Deploy a recommender model as a high-performance web service
- Why Choose NVIDIA Deep Learning Institute for Hands-On Training?
Outline
- Meet the instructor.
- Create an account at courses.nvidia.com/join
Implement collaborative filtering with singular value decomposition (SVD):
- Read sparse data into a GPU using CuPy
- Perform ALS efficiently with NumPy broadcasting rules.
- Build a content-based filter with cuDF
Build a wide and deep network using TensorFlow 2:
- Build a deep network using Keras.
- Build a wide and deep network using TensorFlow feature columns.
- Efficiently ingest training data with tf.data.
- Case study 1: See real-world examples of recommender system model architectures.
Deploy a recommender system in a production environment:
- Acquire a trained model configuration for deployment.
- Build a container for deployment.
- Deploy the trained model using NVIDIA Triton Inference Server.
- Review key learnings and answer questions.
- Learn to build your own training environment from the DLI base environment container.
- Complete the assessment and earn a certificate.
- Take the workshop survey.
- Case study 2: Review real-world challenges of at-scale recommender systems
Frequently asked questions
See all of our FAQsHow can I create an account on myQA.com?
There are a number of ways to create an account. If you are a self-funder, simply select the "Create account" option on the login page.
If you have been booked onto a course by your company, you will receive a confirmation email. From this email, select "Sign into myQA" and you will be taken to the "Create account" page. Complete all of the details and select "Create account".
If you have the booking number you can also go here and select the "I have a booking number" option. Enter the booking reference and your surname. If the details match, you will be taken to the "Create account" page from where you can enter your details and confirm your account.
Find more answers to frequently asked questions in our FAQs: Bookings & Cancellations page.
How do QA’s virtual classroom courses work?
Our virtual classroom courses allow you to access award-winning classroom training, without leaving your home or office. Our learning professionals are specially trained on how to interact with remote attendees and our remote labs ensure all participants can take part in hands-on exercises wherever they are.
We use the WebEx video conferencing platform by Cisco. Before you book, check that you meet the WebEx system requirements and run a test meeting (more details in the link below) to ensure the software is compatible with your firewall settings. If it doesn’t work, try adjusting your settings or contact your IT department about permitting the website.
Learn more about our Virtual Classrooms.
How do QA’s online courses work?
QA online courses, also commonly known as distance learning courses or elearning courses, take the form of interactive software designed for individual learning, but you will also have access to full support from our subject-matter experts for the duration of your course. When you book a QA online learning course you will receive immediate access to it through our e-learning platform and you can start to learn straight away, from any compatible device. Access to the online learning platform is valid for one year from the booking date.
All courses are built around case studies and presented in an engaging format, which includes storytelling elements, video, audio and humour. Every case study is supported by sample documents and a collection of Knowledge Nuggets that provide more in-depth detail on the wider processes.
Learn more about QA’s online courses.
When will I receive my joining instructions?
Joining instructions for QA courses are sent two weeks prior to the course start date, or immediately if the booking is confirmed within this timeframe. For course bookings made via QA but delivered by a third-party supplier, joining instructions are sent to attendees prior to the training course, but timescales vary depending on each supplier’s terms. Read more FAQs.
When will I receive my certificate?
Certificates of Achievement are issued at the end the course, either as a hard copy or via email. Read more here.