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NVIDIA free AI courses help you quickly master generative AI! Whether you are an AI enthusiast, developer or technology explorer, NVIDIA's new free AI course will be your choice.
The course is completely free, with no fees and provides practical skills training in AI, machine learning and edge computing. The course covers a wide range of topics including image classification, regression analysis, and building AI systems on the Jetson Nano development kit. This article will focus on 9 compulsory courses in 2025 to help you start your AI learning journey.
2. Accelerate the data science workflow
Learn to use RAPIDS to accelerate CPU-based data science workflows.
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Course Objective: Master the basics of AI by building and training classified datasets and models using NVIDIA Jetson Nano. This course will guide you on how to set up the Jetson Nano development kit, collect data, and train machine learning models.
Reason for learning: Very suitable for beginners, this course introduces AI concepts and provides practical experience in edge computing.
Click here to view this NVIDIA free course.
Course Objective: Learn how to speed up data science workflows by leveraging GPUs to accelerate data preprocessing, machine learning, and data visualization.
Learning reasons: Transfer CPU-based tasks to the GPU, which significantly saves computing time and improves your productivity.
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Course Objective: Explore the world of generative AI, including its core concepts, applications, and challenges. Learn how this technology reshapes the impact of all industries around the world.
Reason for learning: Understand the impact and potential of generative AI.
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Course Objective: Understand the biological motivations of neural network development and how these logics translate into growth in AI systems.
Reason for learning: Learn from a unique perspective on the origin of AI and its connection to neuroscience.
Click here to view this NVIDIA free AI course.
Course Objective: Understand the capabilities of Retrieval Enhanced Generation (RAG) and large language models. Learn to build a system that retrieves relevant information to improve response.
Learning reason: Master the basic knowledge of RAG-based systems.
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Course objective: Learn to deploy AI agents in real scenarios. This course covers the end-to-end process of building a RAG-based proxy system.
Learning reason: Understand how to integrate LLM with practical applications.
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Course Objective: Understand advanced recommendation system strategies adopted by NVIDIA data science experts, including techniques to gain top positions in data science competitions.
Why you learn: Master one of the most popular skills in e-commerce and content platforms.
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Course Objective: Learn about advanced technologies to solve large-scale image classification problems by using NVIDIA's state-of-the-art tools.
Reason for learning: Use practical applications to enhance your computer vision skills.
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Course Objective: Master the creation of applications using the NVIDIA DeepStream SDK to effectively annotate and process video streams.
Why you learn: Understand video analytics, a key area in the smart city, security and media.
Click here to explore this course.
NVIDIA has long been a major player in the field of generative AI. From developing GPU chips that support all innovative GPU chips to launching LLM and Agent infrastructure that will support further development in the field, NVIDIA has developed technology at scale. Now, with free courses, it plans to democratize learning to help learners around the world join the wave of generative AI.
We also offer some of the most advanced free AI courses – for more information, check out the Analytics Vidhya free courses!
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