Modern Applications of AI (Video Collection)

Description

Master the latest techniques in multimodal AI, large language models, and automated AI agents.

This master class includes the following courses:

• Evaluating Large Language Models (LLMs)
• Practical Retrieval Augmented Generation (RAG)
• Modern Automated AI Agents: Building Agentic AI to Perform Complex Tasks
• Multimodal AI Essentials: Merging Text, Image, and Audio for Next-Generation AI Applications

Key topics covered in the course include:

• Distinguish between generative and understanding tasks
• Evaluate AI agents and retrieval-augmented generation systems
• Develop an understanding of different types of LLMs and how they fit into RAG
• Build a RAG application using a vector database and multiple embedders
• Test different generators like GPT-4o, Claude, Command-R, and more
• Build your own API for running RAG
• Apply multimodal AI concepts
• Construct, fine-tune, and evaluate diffusion models with DreamBooth
• Fine-tune a text-to-speech model with SpeechT5
• Evaluate the performance of multimodal models

Evaluating Large Language Models (LLMs) introduces you to the process of evaluating LLMs, Multimodal AI, and AI-powered applications like agents and RAG. To fully utilize these powerful and often unwieldy AI tools and make sure they meet your real-world needs, they need to be assessed and evaluated. This video prepares you to evaluate and optimize LLMs so you can produce cutting edge AI applications.

Practical Retrieval Augmented Generation shows you how to improve existing large language models by giving them the ability to access additional information that was not part of their original training data.

Modern Automated AI Agents introduces you to the concept of automated agents. It then helps you build a solid understanding of how to design, build, and optimize AI agents to tackle real-world challenges.

Multimodal AI Essentials: Merging Text, Image, and Audio for Next-Generation AI Applications shows you how combining modalities like text, audio, video, and images can enable AI systems to achieve remarkable capabilities. You will gain hands-on experience building visual questions and answering models, generating personalized images with diffusion, designing end to end multimodal applications, and even fine-tuning multimodal models for specific tasks. This video gives you the tools, knowledge, and confidence to design and deploy your own state-of-the-art multimodal AI systems.

Related Learning:

• Sign up for live trainings by Sinan Ozdemir: https://learning.oreilly.com/search/?q=sinan%20ozdemir&type=live-course&rows=100&language=en&publishers=Pearson

Skill Level:

• Beginner to Intermediate

Course Requirements:

• Python 3 proficiency with some experience working in interactive Python environments including Notebooks (Jupyter/Google Colab/Kaggle Kernels)
• Comfortable using the Pandas library and either TensorFlow or PyTorch
• Understanding of ML/deep learning fundamentals including train/test splits, loss/cost functions, and gradient descent

About Pearson Video Training:

Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Prentice Hall, Sams, and Que Topics include: IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more. Learn more about Pearson Video training at http://www.informit.com/video.

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