Top AI Courses from NVIDIA

Top AI Courses from NVIDIA NVIDIA offers a range of practical and hands-on AI courses that cover various applications and technologies. These courses are designed to equip participants with the skills and knowledge to apply AI in real-world scenarios. Getting Started with Deep Learning - Learn the fundamentals of deep learning through practical exercises in computer vision and natural language processing. - Train models from scratch, use pre-trained models, and apply techniques like data augmentation and transfer learning for accurate results. Generative AI Explained - Gain an understanding of Generative AI, its concepts, applications, challenges, and opportunities. - Learn how to use various tools built on Generative AI technology. Disaster Risk Monitoring Using Satellite Imagery - Build and deploy deep learning models to detect flood events using satellite imagery. - Implement machine learning workflows, process large data with accelerated tools, and deploy models for real-time analysis using NVIDIA’s tools and frameworks. Accelerating End-to-End Data Science Workflows - Learn to build and execute end-to-end GPU-accelerated data science workflows using RAPIDS libraries. - Perform fast data preparation, machine learning, graph analysis, and visualization to improve productivity and efficiency in handling large datasets. Building Real-Time Video AI Applications - Build and deploy AI-based video analytics solutions using NVIDIA’s tools. - Construct streaming analytics pipelines, deploy pre-trained models, apply transfer learning for custom models, and optimize video AI application performance. Generative AI with Diffusion Models - Delve into the fundamentals of diffusion models for text-to-image pipelines in applications such as creative content generation and drug discovery. - Learn to build and improve U-Nets for image generation, control output with context embeddings, and generate images from text prompts using the CLIP neural network. Getting Started with Image Segmentation - Learn image segmentation using MRI images to measure heart parts, covering TensorFlow tools and performance metrics. - Set up deep learning workflows for various computer vision tasks. Introduction to Graph Neural Networks - Understand the fundamentals of graph neural networks (GNNs), their applications, and how to build and train GNN models. - Explore practical uses across various industries. Building RAG Agents with LLMs - Explore the deployment and efficient implementation of large language models (LLMs) for enhanced productivity. - Design dialog management systems, utilize embeddings for content retrieval, and implement advanced LLM pipelines using tools like LangChain and Gradio. Introduction to Transformer-Based Natural Language Processing - Learn how Transformer-based large language models (LLMs) are used in modern NLP applications, including tasks such as text classification, named-entity recognition (NER), author attribution, and question answering. Prompt Engineering with LLaMA-2 - Cover prompt engineering techniques that enhance the capabilities of large language models (LLMs) like LLaMA-2. - Learn to write precise prompts, edit system messages, and incorporate prompt-response history to create AI assistant and chatbot behavior. Practical AI Solutions If you want to evolve your company with AI, stay competitive, and use AI to your advantage, consider the top AI courses from NVIDIA. Discover how AI can redefine your way of work, identify automation opportunities, define KPIs, select an AI solution, and implement gradually for business impact. For AI KPI management advice, connect with us at hello@itinai.com. For continuous insights into leveraging AI, stay tuned on our Telegram t.me/itinainews or Twitter @itinaicom. Spotlight on a Practical AI Solution Consider the AI Sales Bot from itinai.com/aisalesbot designed to automate customer engagement 24/7 and manage interactions across all customer journey stages. Discover how AI can redefine your sales processes and customer engagement. Explore solutions at itinai.com.