Free NVIDIA Courses to Boost Your Career in AI, Data Science & Computing
Nvidia, an American multinational corporation and technology company, has become a global outreach in its sector. Founded by Jensen Huang, Curtis Priem, and Chris Malachowsky in 1993, the company is widely renowned tech giant reached across the world with its products like graphics processing units (GPUs), application programming interfaces (APIs) for data science and high-performance computing, and system on a chip units (SoCs) for mobile computing and many more. They company has built its subsidiaries networks with the companies including Bright Computing, Cumulus Networks, DeepMap, Mellanox Technologies and Nvidia Advanced Rendering Center.
Nvidia has come up with some technical courses that are fully free to take online at your time and that might skill you up in a way that might change your career into the next level.
1. Accelerate Data Science Workflows
If you are already skilled with basic familiarity with Python that might help you better understand the course: Accelerate Data Science Workflows. However, it is not a requirement for this free course developed by Nvidia. The 8 hours long course is designed for the beginners and taught in English language. It will teach you to use Jupyter iPython notebooks on your own Jetson to build a deep learning classification project with computer vision models.
2. Getting Started with AI
This course help you build and train a classification data set and model with the NVIDIA Jetson Nano whereby the power of AI is now in the hands of makers, self-taught developers, and embedded technology enthusiasts everywhere with the NVIDIA Jetson developer kits. This powerful computer lets you run multiple neural networks in parallel for applications like image classification, object detection, segmentation, and speech processing. In this course, you'll use Jupyter iPython notebooks on your own Jetson to build a deep learning classification project with computer vision models.
Free Nvidia Courses That Might Advance Your Career into the Next Level
3. Generative AI Explained
According to Nvidia, it is the no-coding course whereby it teaches you the Generative AI concepts and applications. The course further strengthens you with the skills filled of challenges and opportunities in the field. The Generative AI/LLM course is for all the beginners who want to build their career on this exciting field with no any course prerequisites. Upon completion of this course, you will build more effectively in yourself to use the various tools built on this technology.
4. Building a Brain in 10 Minutes
This is the introductory course in deep learning subject as defined by Nvidia whereby it offers exploring how neural networks use data to learn and understanding the math behind a neuron under the topics like AI Data, Neurons and TensorFlow 2. This course is designed to those whose Course Prerequisites is anyone who can run the code to see how it works, but to get the most out of this content, we recommend: An understanding of fundamental programming concepts in Python 3 such as functions, loops, dictionaries, and arrays.
5. Augment your LLM using RAG
RAG stands for Retrieval Augmented Generation launched by Facebook AI five years back. This course is aimed at optimizing the output of an LLM with dynamic, domain specific data without need of retraining the model. Throughout this course, you will be provided a starting point using components what Nvidia have used in its system. This is the technical course for beginners and which will up skill the learners with the basics of RAG, RAG retrieval process, and Nvidia AI Foundations and the components that constitute a RAG model.
6. Building RAG agents with LLMs
This course will show you how to deploy an agent system in practice. The evolution and adoption of large language models (LLMs) have been nothing short of revolutionary, with retrieval-based systems at the forefront of this technological leap. These models are not just tools for automation; they are partners in enhancing productivity, capable of holding informed conversations by interacting with a vast array of tools and documents. This course is designed for those eager to explore the potential of these systems, focusing on practical deployment and the efficient implementation required to manage the considerable demands of both users and deep learning models. As we delve into the intricacies of LLMs, participants will gain insights into advanced orchestration techniques that include internal reasoning, dialog management, and effective tooling strategies.
7. Mastering Recommender Systems
This exciting course developed by Nvidia developer explores strategies employed by Kaggle Grandmasters of NVIDIA to secure top positions in a data science competition focused on building a high-functioning recommendation system for e-commerce. Learn about the two-stage model approach, including candidate generation using co-visitation matrices and reranker model development with feature selection and engineering. Discover insights from second and third-place solutions, model ensembling techniques, and participate in a Q&A session. Gain valuable knowledge about recommender systems, data science competitions, and advanced techniques used by industry experts in this 47-minute video from the Grandmaster Series.
The covered syllabuses under this course are introduction, overview & summary of the challenge, recommender systems - 2 stage model, stage 1: candidate generation & co-visitation matrices, co-visitation matrices explained, stage 2: reranker model - feature selection & engineering, second-place solution, third-place solution, model ensembling and Q&A Session.
8. Perform Large-Scale Image Classification
This course is designed to discover advanced techniques for large-scale image classification from the aspects of introduction, welcome, competition, classical approach, winning solution, validation strategy, code efficiency, modeling, third place solution, architecture, fine-tuning, post processing, ensemble, competitions, cutout augmentation, label submitting &vaccine degradation.
The course teachs on how Kaggle Grandmasters of Nvidia (KGMON) built winning models for the Google Landmark Recognition 2020 competition, tackling the challenge of recognizing landmarks across 81,000+ classes. Also it explores classical approaches, winning solutions, validation strategies, code efficiency, and modeling techniques, along with gaining insights into third-place solutions, including architecture, fine-tuning, post processing, and ensemble methods.
9. Building Video AI Applications
The AI-based video understanding can be a great platform for an introduction to intelligent video analytics (IVA) applications using the Nvidia DeepStream SDK. The techniques you learn from this course can then be applied to your own projects in the future on the Nano or other Jetson platforms at the Edge.
Inside this course, you will learn how to build DeepStream applications to annotate video streams using the hardware like Nvidia Jetson Nano Developer Kit or Nvidia Jetson Nano 2GB Developer Kit. A person having an understanding of fundamental programming concepts in Python 3 such as functions, loops, dictionaries, and arrays can learn with passion.
10. Supercharge Your Data Science Workflows
The digital industry has gone so much of deep inside the ocean which cannot understand within a certain demarcation. This course offers you to learn how RAPIDS can speed up CPU-based data science processes for fast insights and efficiency whereby it also techs you a seamless experience to enable GPU-acceleration for many existing data science tasks with zero code changes.
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