AI Foundations

Josh StarmerDeepLearning.AI

In this course, you will delve into the attention mechanism, a key component of transformers, and learn how to implement it using PyTorch. You'll explore the relationships between word embeddings, positional embeddings, and attention, and understand the roles of Query, Key, and Value matrices. The course covers self-attention, masked self-attention, and cross-attention, providing a comprehensive understanding of how these concepts are incorporated into transformers. By the end, you'll be equipped with the knowledge to build reliable and scalable AI applications.

Dr. Nancy LiMaven

In this bootcamp, you will lead a team of AI engineers, data scientists, and designers to build and launch a real AI product. You'll learn AI product strategy, validate user pain points, design and prototype with experts, and launch your product publicly. The course provides resume help, job referrals, and the opportunity to apply for seed funding and incubators.

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.

Jack CohenMaven

In this course, you'll learn to transform your management style by integrating AI tools and human systems. You'll develop a personal operating system that enhances focus, emotional balance, and team alignment. The course covers building Custom GPTs, mastering delegation, and using AI for feedback and coaching. By the end, you'll be equipped to lead with confidence and inspire growth in your team.

Sharon ZhouDeepLearning.AI

In this specialization, you will learn to understand GAN components, build basic and advanced GANs using PyTorch, and control your GAN to build conditional GANs. You will compare generative models, use the FID method to assess GAN fidelity and diversity, and learn to detect bias in GANs. Additionally, you will explore GAN applications in data augmentation and privacy preservation, and implement Pix2Pix and CycleGAN for image translation.

Harrison ChaseDeepLearning.AI

In this course, you will delve into the fundamentals of data loading, document splitting, vector stores, and embeddings. You will learn advanced techniques for data retrieval and build a one-pass question-answering solution. By the end of the course, you will be able to create a chatbot that interacts with data using LangChain and LLMs.

Sophia YangDeepLearning.AI

In this course, you’ll access Mistral AI’s collection of open source and commercial models, including the Mixtral 8x7B model, and the latest Mixtral 8x22B. You’ll learn about selecting the right model for your use case, and get hands-on with features like effective prompting techniques, function calling, JSON mode, and Retrieval Augmented Generation (RAG). By the end of this course, you’ll be equipped to leverage Mistral AI’s leading open source and commercial models.

Miguel AmigotedX

In this course, you'll learn how to use ChatGPT for content creation, grading, and more. You'll discover how to create personalized learning experiences for students and automate grading and feedback. We'll also cover ethical and legal considerations for using ChatGPT in education, and explore advanced techniques for customization and integration with other educational tools. By the end of the course, you'll be able to unlock the limitless potential of ChatGPT in education, and significantly improve your efficiency and access to information. Join us in this exciting journey and explore how AI and language models can transform the way we teach and learn.

Krish NaikUdemy

This course provides a detailed exploration of generative AI, focusing on the integration of Langchain and Huggingface models. Participants will learn to create advanced AI applications, understand architecture and design patterns, and gain hands-on experience in deploying models across various environments. The course covers deployment strategies, RAG pipelines, and model optimization, ensuring learners can build scalable and reliable AI systems.

Elie SchoppikDeepLearning.AI

In this course, you will explore the Model Context Protocol (MCP) and its role in standardizing AI application development. Learn to build and deploy MCP servers, create MCP-compatible applications, and connect AI applications to external systems. By the end, you'll be equipped to develop AI applications with rich context and minimal integration work.

Ross DawsonMaven

In this transformative course, you will dive deep into the landscape of cognition-enhancing AI, learning how to leverage advanced AI techniques to augment your thinking. You will identify the most impactful use cases for your work and master sophisticated strategies that will take your value creation to new heights. By applying cutting-edge AI-augmented thinking strategies, you will pinpoint the most effective pathways to make smarter decisions, solve problems more creatively, and achieve your goals with greater precision and clarity.

Andrew NgCoursera

In this course, you will learn the fundamental concepts of AI, including machine learning, deep learning, and data science. You will explore what AI can realistically achieve and how to identify opportunities to apply AI in your organization. The course also covers the ethical and social implications of AI, providing a well-rounded understanding of the field.

Fábio DuarteGetSmarter

In this course, you will gain a broad perspective on the future of real estate, including disruptions to commercial and residential properties, parking lots, curbsides, warehousing, and last mile delivery. You will understand how AI and self-driving vehicles are transforming the real estate industry and learn to leverage trends in micro-mobility, on-demand mobility, and self-driving vehicles for real estate investment opportunities. The course includes exposure to real city case studies and industry-relevant tools, equipping you with practical skills to navigate the evolving mobility landscape.

Heidi CulbertsonMaven

In this course, you will learn how to design world-class bots by understanding conversation across the lifespan. You will explore how human communication evolves as we grow up and how to apply this knowledge to create usable conversational products. The course covers developing use cases, applying linguistics and cognition knowledge, training bots, crafting responses, prototyping, and usability testing. By the end of the course, you will have actionable knowledge, frameworks, and techniques to design better bots.

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.

Isa FulfordDeepLearning.AI

In ChatGPT Prompt Engineering for Developers, you will learn how to use a large language model (LLM) to quickly build new and powerful applications. Using the OpenAI API, you’ll be able to quickly build capabilities that learn to innovate and create value in ways that were cost-prohibitive, highly technical, or simply impossible before now. This short course taught by Isa Fulford (OpenAI) and Andrew Ng (DeepLearning.AI) will describe how LLMs work, provide best practices for prompt engineering, and show how LLM APIs can be used in applications for a variety of tasks, including summarizing, inferring, transforming text, and expanding text. You’ll also learn two key principles for writing effective prompts, how to systematically engineer good prompts, and build a custom chatbot. All concepts are illustrated with numerous examples, which you can play with directly in our Jupyter notebook environment to get hands-on experience with prompt engineering.