As we step into 2024, the opportunity to enrol in NVIDIA free courses presents itself as a gateway for students to enhance their skills, broaden their knowledge, and prepare for the future of technology. This blog post serves as a guide for college students looking to seize this chance to enrol in NVIDIA free courses, explore cutting-edge topics, and embark on a journey of learning and growth.
Also, Read: Nasscom Govt Free Course For Everyone; Duration 1 Hour: Enroll now in 2024
Also, Read: Skill India Free Course with Free Certificates For Everyone; Enroll Now in 2024
Table of Contents
About the NVIDIA
Nvidia Corporation is an American multinational corporation and technology company headquartered in Santa Clara, California, and incorporated in Delaware. It is a software and fabless company that designs and supplies graphics processing units (GPUs), application programming interfaces (APIs) for data science and high-performance computing as well as system on-a-chip units (SoCs) for the mobile computing and automotive market. Nvidia is also a dominant supplier of artificial intelligence (AI) hardware and software.
Nvidia’s professional line of GPUs is used for edge-to-cloud computing and in supercomputers and workstations for applications in such fields as architecture, engineering and construction, media and entertainment, automotive, scientific research, and manufacturing design. Its GeForce line of GPUs are aimed at the consumer market and are used in applications such as video editing, 3D rendering and PC gaming. In the second quarter of 2023, Nvidia had a market share of 80.2% in the discrete desktop GPU market. The company expanded its presence in the gaming industry with the introduction of the Shield Portable (a handheld game console), Shield Tablet (a gaming tablet) and Shield TV (a digital media player), as well as its cloud gaming service GeForce Now.
Why do we learn to enrol in NVIDIA Free Courses?
There’s a key difference between the reasons to learn and the reasons to enrol in NVIDIA free courses. Here’s a breakdown:
Reasons to Learn AI with NVIDIA Free Courses:
Gain In-Demand Skills: AI is rapidly transforming industries, and these courses equip you with valuable skills sought after by employers.
Free Education: Sharpen your knowledge without breaking the bank. It’s a cost-effective way to explore AI.
Flexible Learning: The self-paced format allows you to learn at your own convenience, fitting it around your existing commitments.
Industry Expertise: Learn from the best! NVIDIA is a leading innovator in AI, so you’re getting top-notch knowledge.
Practical Learning: These courses go beyond theory, offering hands-on experience through projects, making the learning process engaging and applicable.
Eligibility Criteria
NVIDIA Free Courses for Any College student with any stream.
Also, Read: CISCO Free Data Analytics Course For College Students Enroll now in 2024
Also, Read : TCS Free Aptitude Course; for Placement & Govt Exam Preparation in 2024
Here Are NVIDIA Free Courses
1. Generative AI Explained
About this Course
Generative AI describes technologies that are used to generate new content based on a variety of inputs. In recent times, Generative AI involves the use of neural networks to identify patterns and structures within existing data to generate new content. In this course, you will learn Generative AI concepts, and applications, as well as the challenges and opportunities in this exciting field.
What You Will Learn
Upon completion, you will have a basic understanding of Generative AI and be able to effectively use the various tools built on this technology.
Course Outline
In this course you’ll learn how to:
Define Generative AI and explain how Generative AI works
Describe various Generative AI applications
Explain the challenges and opportunities in Generative AI
Course Link Click Here
2. Getting Started with AI on Jetson Nano
About this Course
The power of AI is now in the hands of makers, self-taught developers, and embedded technology enthusiasts everywhere with the NVIDIA Jetson Nano Developer Kit. This easy-to-use, 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 Nano to build a deep learning classification project with computer vision models.
Course Link Click Here
3. Building A Brain in 10 Minutes
About this Course
Course Abstract
This notebook explores the biological and psychological inspirations to the world’s first neural networks.
Learning Objectives
The goals of this exercise include: Exploring how neural networks use data to learn
Understanding the math behind a neuron
Prerequisites Anyone 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.
An understanding of how to compute a regression line.
Course Link Click Here
4. Building Video AI Applications at the Edge on Jetson Nano
About this Course
AI-based video understanding can unlock insights, whether it’s recognizing a cat in your backyard or optimizing customers’ shopping experiences. The NVIDIA Jetson Nano Developer Kit is an easy-to-use, powerful computer that lets you run multiple neural networks in parallel. This makes it a great platform for an introduction to intelligent video analytics (IVA) applications using the NVIDIA DeepStream SDK. In this course, you’ll use JupyterLab notebooks and Python application samples on your Jetson Nano to build new projects that extract meaningful insights from video streams through deep learning video analytics. 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.
Course Link Click Here
5. Augment your LLM Using Retrieval Augmented Generation
About this Course
This course introduces a workflow that we believe is representative of where you should start. It will save you time in having to try and go through all the permutations and decisions you would otherwise make about vector databases, embedding models, and LLMs. In this introduction, we provide a starting point using components we at NVIDIA have used internally including popular Open Source Software frameworks.
Course Link Click Here
6. Building RAG Agents with LLMs
About this Course
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.
What You Will Learn?
Participants will embark on a learning journey that encompasses the composition of LLM systems, fostering predictable interactions through a blend of internal and external reasoning components. The course emphasizes the creation of robust dialog management and document reasoning systems that not only maintain state but also structure information in easily digestible formats. A key component of our exploration will be the use of embedding models, which are essential for executing efficient similarity queries, enhancing content retrieval, and establishing dialog guardrails. Furthermore, we will tackle the implementation and modularization of retrieval-augmented generation (RAG) agents, which are adept at navigating research papers to provide answers without the need for fine-tuning.
Course Link Click Here
Also, Read : DU Internship 2024; Free Certificate Stipend Rs. 10,500/ month: Apply by 4 May
Also, Read : Top 4 MIT Free Courses You Can Take Online in 2024
7. Accelerate Data Science Workflows with Zero Code Changes
About this Course
Across industries, modern data science requires large amounts of data to be processed quickly and efficiently. These workloads need to be accelerated to ensure prompt results and increase overall productivity. NVIDIA RAPIDS offers a seamless experience to enable GPU acceleration for many existing data science tasks with zero code changes.
What You Will Learn
In this course, you’ll learn to use RAPIDS to speed up your CPU-based data science workflows.
Course Outline
By participating in this workshop, you’ll: Understand the benefits of a unified workflow across CPUs and GPUs for data science tasks. Learn how to GPU-accelerate various data processing and machine learning workflows with zero code changes. Experience a significant reduction in processing time when workflows are GPU-accelerated
Course Link Click Here
FAQ
What are NVIDIA Free Courses?
NVIDIA’s Deep Learning Institute (DLI) offers a comprehensive selection of online courses designed to teach you the fundamentals and advanced concepts of Artificial Intelligence (AI). The best part? These courses are completely free, making them a fantastic resource for college students looking to upskill in this in-demand field.
Why should I enroll in NVIDIA Free Courses?
There are many reasons why these courses are a perfect fit for college students:
Cost-Effective: No financial barrier to entry! Gain valuable AI skills without spending a dime.
Flexible Learning: Self-paced courses allow you to learn at your own speed and fit them around your busy schedule.
Industry Expertise: Learn from the experts at NVIDIA, a leader in AI technology.
Project-Based Learning: Gain practical experience by working on real-world AI projects throughout the courses.
Career Advancement: Boost your resume and stand out to potential employers with sought-after AI skills.
What are some of the NVIDIA Free Courses?
Here’s a glimpse of some exciting courses you can explore:
Fundamentals of Deep Learning: A foundational course providing a comprehensive introduction to core deep learning concepts.
Generative AI Explained: Delve into the world of generative AI, where the focus is on creating new data and exploring its applications.
Building Video AI Applications at the Edge on Jetson Nano: Learn to develop and deploy AI-powered video applications on NVIDIA’s Jetson Nano platform, a compact device for edge computing.
Introduction to AI in the Data Center: Discover the critical role of AI in data centres and how it’s revolutionizing data processing and analysis.
Disaster Risk Monitoring Using Satellite Imagery: Learn how to leverage AI with satellite imagery for disaster risk monitoring, a powerful application with real-world impact.
