Dr. Ronny KohaviMaven

This course covers the design and analysis of trustworthy A/B tests, integrating AI/ML, and growing your business through data-driven decision-making. You will learn from real examples and stories from Microsoft, Amazon, and Airbnb, understanding the challenges and pitfalls of experimentation. The course also covers cultural challenges, institutional memory, observational causal studies, and more technical topics like Bayesian vs. Frequentist methods.

Bryan D. Eldridge, M.Ed.Maven

This course will enable life science practitioners with no prior experience in building AI-driven applications to leverage their subject matter expertise and existing capabilities around data and statistical models - in tandem with easily accessible support and resources - to design and execute their first AI project. You will understand how AI has impacted the traditional data lifecycle, master the basics of the AI lifecycle, develop a comprehensive understanding of the contemporary AI landscape, and explain how each major type of AI model is applicable to life sciences.

Maria KhalusovaDeepLearning.AI

In this course, you will learn to select open source models from Hugging Face Hub to perform various tasks using the transformers library. You will package your code into a user-friendly app that can run on the cloud using Gradio and Hugging Face Spaces. The course covers tasks such as turning a small language model into a chatbot, translating languages, summarizing documents, converting audio to text, and more. By the end of the course, you will have the building blocks to create your AI-enabled applications.

Ammaar ReshiMaven

In this practical course, you'll master AI tools to tell your own stories and share them with the world. You'll learn to work with GPT for storytelling, use AI image generation tools to create illustrations, and prepare your content for publishing. By the end of the course, you'll be a published author with your own paperback book to share with family, friends, and the internet.

Antje BarthDeepLearning.AI

This course provides a comprehensive understanding of generative AI, covering key steps in a typical LLM-based generative AI lifecycle, from data gathering and model selection to performance evaluation and deployment. You will learn about the transformer architecture, empirical scaling laws, and state-of-the-art training, tuning, inference, tools, and deployment methods. The course also discusses the challenges and opportunities that generative AI creates for businesses, with insights from industry researchers and practitioners.

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.

Jess GoldbergMaven

In this course, you'll gain a comprehensive understanding of how to transform your job search into a strategic plan. You'll learn to craft a step-by-step strategy that leads to interviews and offers, optimize your first impression, and master the art of negotiation. The course also covers networking techniques and the use of AI tools to enhance your career prospects.

Andrew NgDeepLearning.AI

In this course, you will learn the fundamentals of generative AI, including its capabilities and limitations. You will explore various AI tools and techniques, and gain hands-on experience with generative AI applications. The course also covers the impact of AI on business and society, providing you with the knowledge to develop effective AI strategies.

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.

Josh StarmerDeepLearning.AI

Dive deep into the attention mechanism that revolutionized AI with transformers. This course, taught by Josh Starmer, covers the evolution of attention, the role of Query, Key, and Value matrices, and the differences between self-attention and masked self-attention. Gain hands-on experience coding these concepts in PyTorch, and understand how they contribute to building scalable AI applications.

Doug TurnbullMaven

In this course, you'll learn how to enhance your search engine's relevance using Large Language Models. You'll gain skills in query and content understanding, and learn to deploy LLMs in production efficiently. The course is designed to help you sidestep traditionally complex processes and achieve structured, well-formed queries, ultimately improving your team's search outcomes.

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.

Matt RobinsonDeepLearning.AI

This course will teach you how to preprocess data for LLM application development, focusing on working with different document types. You will learn to extract and normalize various documents into a common JSON format, enrich it with metadata, and apply techniques for document image analysis to preprocess PDFs, images, and tables. By the end of the course, you will be able to build a RAG bot capable of ingesting different documents and apply these skills to real-world scenarios.

Ofer MendelevitchDeepLearning.AI

This course offers a comprehensive exploration of embedding models, focusing on their architecture and implementation. Participants will learn about word and sentence embeddings, dual encoder models, and the use of contrastive loss to enhance question-answer retrieval applications. The course provides a hands-on approach to understanding the technical concepts behind embedding models, making it ideal for data scientists, machine learning engineers, and NLP enthusiasts.

Jay AlammarDeepLearning.AI

In this course, you will 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.

Amit SanganiDeepLearning.AI

In this course, you will explore the Llama 4 models, learning how to utilize their Mixture-of-Experts architecture for efficient application development. You'll gain practical experience with image reasoning, image grounding, and long-context text processing. The course also covers prompt optimization and synthetic data creation, equipping you with the skills to build production-ready features that span text, images, and massive context. By the end, you'll be able to confidently choose and implement the right Llama 4 model for your projects.

Jay AlammarDeepLearning.AI

In this course, you will 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.

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.

Ofer MendelevitchDeepLearning.AI

This course offers a comprehensive exploration of embedding models, focusing on their architecture and implementation. Participants will learn about word and sentence embeddings, dual encoder models, and the use of contrastive loss to enhance question-answer retrieval applications. The course provides a hands-on approach to understanding the technical concepts behind embedding models, making it ideal for data scientists, machine learning engineers, and NLP enthusiasts.

Miguel AmigotedX

Are you fascinated by the potential of AI and language models in healthcare? Join our How to Use ChatGPT in Healthcare course and delve into the transformative impact of ChatGPT in the industry. Explore a wide range of use cases that highlight its limitless potential in patient care, data accessibility, and healthcare administration. Gain a comprehensive understanding of the ethical and legal considerations surrounding the implementation of this technology. With this knowledge, you'll be empowered to apply ChatGPT in your day-to-day activities, revolutionizing the way you provide care, access medical data, and streamline administrative tasks. Don't miss out on this opportunity to be at the forefront of healthcare innovation. Enroll now and unlock the extraordinary power of ChatGPT in healthcare.

Div GargDeepLearning.AI

In this course, you'll delve into the world of AI browser agents, learning how they automate online tasks and the decision-making strategies they employ. You'll build agents that can scrape websites, fill out forms, and more, using the AgentQ framework to enhance their capabilities. By the end, you'll have a solid understanding of AI agents' current state and future directions.

Jay AlammarDeepLearning.AI

In this course, you will 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.

Jacob LeeDeepLearning.AI

This course will show web developers how to expand their toolkits with LangChain.js, a popular JavaScript framework for building with LLMs. It covers useful concepts for creating powerful, context-aware applications. By taking this course, you will learn to use LangChain’s underlying abstractions to build your own JavaScript apps, understand the basics of retrieval augmented generation (RAG), and have the structure of a basic conversational retrieval system that you can use for building your own chatbots.

Michele CatastaDeepLearning.AI

In this course, you'll explore the growing practice of 'vibe coding' where AI coding agents assist in the development process. You'll learn to structure your work, refine prompts, and use frameworks for cleaner, more efficient code. By building two web applications, you'll gain hands-on experience with Replit's tools and improve your development skills.