NVIDIA has launched completely free training courses that will take you from the basics to the latest AI and Generative AI applications, with accredited certificates.
Whether you’re a beginner or have prior experience, you’ll find something suitable among these courses. Take a look and enroll in the one that’s right for you.
What’s special about NVIDIA courses?
- They’re completely free and accessible to everyone, whether you’re a beginner looking for the fundamentals of artificial intelligence or a professional wanting to delve deeper.
- They’re offered by NVIDIA, one of the world’s leading companies in developing AI technologies and graphics processing units (GPUs) used in major research and technology centers.
- The courses are practical and professionally designed by certified experts, ensuring you receive applied content that you can directly use in your projects.
- You can earn free NVIDIA-certified certificates, which add significant value to your resume and increase your chances of employment in the technology and AI fields.
- They cover a variety of learning areas, including machine learning, computer vision, natural language processing, and robotics.
- It gives you the opportunity to join a global community of learners and programmers, helping you to exchange experiences and expand your professional network.
NVIDIA AI Courses
Generative AI Explained Course
If you’re wondering what generative artificial intelligence is, this course is the perfect starting point. You will learn:
- What is generative AI and how exactly does it work?
- Practical applications of generative AI, such as creating images, text, and more.
- You will also learn about the most prominent challenges and opportunities in this rapidly evolving field.
Artificial Intelligence for Everyone
This course aims to simplify AI concepts for everyone, starting from the basics and progressing to the practical application of generative intelligence.
You will learn:
- How AI impacts sectors such as healthcare and autonomous vehicles.
- The difference between machine learning and generative AI.
- How to use GenAI to create audio and visual content.
Specialized courses in artificial intelligence
Getting Started with AI on a Jetson Nano
If you own a Jetson Nano and want to explore its capabilities, this course will teach you:
- Setting up your device and camera.
- Gathering image data to train models.
- Illustrating data and training neural networks to develop your models.
Building an Artificial Brain in 10 Minutes
Want to understand how the human brain works from a technical perspective? In this course, you will learn:
- How neural networks learn from data.
- The mathematical fundamentals that underpin the structure of an artificial “neuron.”
Building AI Video Applications with Jetson Nano
This course is one of NVIDIA’s AI courses, and in this hands-on course you will learn:
- How to create video processing lines using DeepStream.
- How to manage multiple video sources simultaneously.
- You will also learn how to use alternative inference engines such as YOLO.
Other NVIDIA Courses
Building RAG Agents Using Large Language Models (LLMs)
If you are interested in developing applications based on LLMs such as GPT, Cloud, and Mistral, this course is for you. You will learn:
- Scalable deployment strategies.
- Developing applications across microservices.
- Using Lang Chain to manage dialogues.
- Experiencing the latest advanced models.
Accelerate your data science workflow without writing a single line of code.
Why write code from scratch when you can accelerate tasks using the power of the GPU? You will learn:
- The benefits of combining CPU and GPU processing in your workflow
- Accelerate data processing and machine learning using GPU technologies
- Get faster results without major code changes
Introduction to Artificial Intelligence in Data Centers
If you want to understand how to build an AI operating environment in data centers, start with this course where you will learn:
- Fundamentals of artificial intelligence, machine learning, and GPU architecture.
- An overview of deep learning frameworks and AI applications.
- How to plan and operate multi-unit systems.
Tips for Getting the Most Out of NVIDIA Courses
- Before you begin, define your path. Choose the area closest to your interests (machine learning, computer vision, generative AI, etc.) to get a clear start.
- If you’re a beginner, stick to introductory courses first, then gradually increase the difficulty before delving into advanced courses.
- Practice it practically. Try the code and projects presented in the lessons directly on your computer or in a testing environment (like Google Colab).
- Set aside consistent time. Ideally, dedicate a few hours per week to reviewing the lessons, even if it’s just two hours, to ensure consistent progress.
- Take notes. Record important ideas and key steps so you can easily review them when needed.
- Participate in the NVIDIA Community Forum. It’s an interactive community where you can ask questions, discuss topics, and follow other people’s experiences.
- Test yourself: After each unit or course, complete a small project or solve practice problems to assess your understanding.
- Take advantage of the certificates: After completing each course, download the certificate and add it to your resume or LinkedIn profile.
