All courses
Amir FeizpourMaven
This course will teach you the core principles of multi-agent LLM systems, how to design and build them, and how to integrate them into existing products. You will learn about optimizing teamwork, managing complex information flow, and ensuring security. By the end of the course, you will be able to design and build robust multi-agent LLM systems that enhance user experience, productivity, and business metrics.
Adrian Gonzalez SanchezDeepLearning.AI
In Building Your Own Database Agent, you will learn to interact with tabular data and SQL databases using natural language, enabling more efficient and accessible data analysis. You will gain hands-on experience with the Azure OpenAI Service, implementing techniques like Retrieval Augmented Generation (RAG) and function calling. By the end of the course, you’ll be equipped with the technical knowledge and practical experience to implement similar systems in your own projects or organizations, enabling more efficient and accessible data interaction and analysis.
Allie K. MillerMaven
This course offers a well-rounded approach to AI learning, tailored specifically for business leaders and executives. You'll learn how to contextualize AI into your business, find and prioritize AI use cases, and deploy AI responsibly. The course includes real-world tactics for AI execution, change management strategies, and insights into building an AI-focused culture. Benefit from the wisdom of world-class guest speakers and gain practical advice to enhance your organization's skills.
Will KurtDeepLearning.AI
In this course, you will gain a comprehensive understanding of structured outputs and their significance in software development. You will learn to generate structured outputs using APIs, re-prompting libraries, and constrained decoding. The course includes practical applications like building a social media agent and using Pydantic for defining structured outputs. By the end, you will be equipped with the knowledge to implement structured outputs in your LLM applications, enhancing your ability to develop scalable and efficient software solutions.
Isa FulfordDeepLearning.AI
This course teaches you how to efficiently build systems using the ChatGPT API by automating complex workflows. You'll learn to split tasks into a pipeline of subtasks using multistage prompts and evaluate LLM inputs and outputs for safety, accuracy, and relevance. The course includes hands-on examples and Jupyter notebooks for seamless experimentation.
Andrew NgDeepLearning.AI
In this specialization, you will learn the foundational concepts of deep learning, build and train neural networks, and apply them to various AI tasks. The program covers neural networks, hyperparameter tuning, convolutional networks, sequence models, and more. By the end, you will have the skills to build and apply deep learning models to real-world problems.
Harrison ChaseDeepLearning.AI
In LangChain for LLM Application Development, you will gain essential skills in expanding the use cases and capabilities of language models in application development using the LangChain framework. You will learn about models, prompts, parsers, memories for LLMs, chains, question answering over documents, and agents. By the end of the course, you will have a model that can serve as a starting point for your own exploration of diffusion models for your applications.
Carey PhelpsDeepLearning.AI
In this course, you will learn to instrument a Jupyter notebook, manage hyperparameter configurations, log run metrics, collect artifacts for dataset and model versioning, and log experiment results. Additionally, you will learn to trace prompts and responses to LLMs over time in complex interactions. By the end of the course, you will have a systematic workflow to boost your productivity and accelerate your journey toward breakthrough results.
Andrew NgDeepLearning.AI
In this course, you will gain a comprehensive understanding of AI technologies and their applications. You will learn about the workflow of machine learning and data science projects, AI terminology, and strategies for building AI projects. Additionally, you will explore the societal impact of AI, including issues like bias and job displacement. This course is ideal for non-technical business professionals, machine learning engineers, and data scientists looking to build a sustainable AI strategy.
Harrison ChaseDeepLearning.AI
In this course, you will learn how to build an agent with long-term memory by creating a personal email agent that can respond, ignore, and notify the user using writing, scheduling, and memory tools. You’ll develop your agent’s memory by adding facts to its memory store, providing examples to learn the user’s preferences, and optimizing system prompts to evolve instructions based on previous responses. This course will equip you with the skills to integrate semantic, episodic, and procedural memory into AI agents, enhancing their functionality and user interaction.
Charles PackerDeepLearning.AI
In this course, you will learn to build agentic memory into your applications using the Letta framework. Discover how an LLM agent can act as an operating system to manage memory, autonomously optimizing context use. You'll explore the key ideas behind the MemGPT paper, including the two tiers of memory and how agent states are turned into prompts. By the end, you'll be equipped to create adaptive, collaborative AI agents for tasks like research and HR.
Rav AhujaCoursera
In this course, you will explore the key concepts and applications of AI, including deep learning, machine learning, and neural networks. You'll examine generative AI models, such as large language models, and their capabilities. The course also covers AI's impact on industries like natural language processing, computer vision, and robotics, highlighting how these advancements drive innovation. Additionally, you'll delve into the ethical considerations and governance of AI, preparing you to navigate the evolving AI landscape.
Jay AlammarDeepLearning.AI
In this course, you'll learn how a transformer network architecture that powers LLMs works. You'll build the intuition of how LLMs process text and work with code examples that illustrate the key components of the transformer architecture. By the end of this course, you’ll have a deep understanding of how LLMs process language and you’ll be able to read through papers describing models and understand the details that are used to describe these architectures.
Robert MonarchDeepLearning.AI
In this specialization, you will master a step-by-step framework for developing AI projects. You will analyze data and build AI models for projects focused on air quality, wind energy, biodiversity monitoring, and disaster management. Through real-world case studies, you will explore public health, climate change, and disaster management, and develop practical skills to make a positive impact using AI.
João MouraDeepLearning.AI
In this course, you will learn key principles of designing effective AI agents and organizing a team of AI agents to perform complex, multi-step tasks. You will apply these concepts to automate six common business processes. By the end of the course, you will have designed several multi-agent systems to assist you in common business processes and studied the key principles of AI agent systems.
Younes BelkadaDeepLearning.AI
In this course, you will learn how to compress models using linear quantization and downcasting techniques. You will gain a foundation in quantization methods, enabling you to optimize generative AI models for better performance on various devices. By the end of the course, you will be able to apply these techniques to your own models, making them more efficient and accessible.
