Emmanuel AcheampongMaven
In this bootcamp, you will go beyond fundamental AI knowledge and apply hands-on technical skills to real-world data problems. You will develop three distinct applications that showcase your diverse skillset in Data Analytics, Computer Vision, and Natural Language Processing. The course includes interactive live sessions, lifetime access to course materials, guided feedback, and a private community of peers.
Blake EmalMaven
In AI Marketing 101, you'll learn how to leverage AI tools to streamline your marketing tasks. From writing great prompts to generating A+ content for SEO, ads, and content marketing, this course covers it all. You'll also learn how to build repeatable processes and automate key parts of your workflow using tools like ChatGPT, Notion AI, and DALL-E 3.
Andrew NgDeepLearning.AI
In this Machine Learning in Production course, you will build intuition about designing a production ML system end-to-end: project scoping, data needs, modeling strategies, and deployment patterns and technologies. You will learn strategies for addressing common challenges in production like establishing a model baseline, addressing concept drift, and performing error analysis. You’ll follow a framework for developing, deploying, and continuously improving a productionized ML application.
Luis SerranoDeepLearning.AI
In this specialization, you will gain a deep understanding of the mathematical principles that underpin machine learning algorithms. You will learn how to apply statistical techniques to enhance your data analysis, and acquire skills that are highly sought after by employers. By the end of the course, you will be able to implement and optimize machine learning algorithms, making you a valuable asset in the field of AI and data science.
Sara DavisonMaven
In this course, you will learn essential AI fundamentals for business growth, key AI concepts, platforms, and tools, and how to create and use a Business Second Brain. You'll also learn the fundamentals of prompt engineering, advanced techniques for multi-step workflows, and strategies to align AI-generated content with your brand voice. By the end of the course, you'll be able to identify AI opportunities within your business, craft effective prompts, build and prepare an AI assistant for deployment, and integrate AI assistants with your knowledge base.
Rav AhujaCoursera
This specialization provides a thorough introduction to AI, covering its applications, use cases, and impact across industries. Learners will explore key concepts such as Machine Learning, Deep Learning, and Neural Networks, and gain practical experience by building and deploying an AI-enabled chatbot without coding. The course also covers IBM Watson AI services and the creation of intelligent virtual assistants, equipping learners with the skills needed to leverage AI in various scenarios.
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.
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.
Learn how AI applies to real scenarios and workflows.
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.
Nikita NamjoshiDeepLearning.AI
In this course, you will explore the properties of word and sentence embeddings and learn how to use them to measure semantic similarity between texts. You will apply text embeddings for tasks such as classification, clustering, and outlier detection. Additionally, you will learn to modify the text generation behavior of an LLM by adjusting parameters like temperature, top-k, and top-p. The course also covers the application of the open-source ScaNN library for efficient semantic search and building a Q&A system by combining semantic search with an LLM.
Maheen SohailMaven
This course covers AI design fundamentals, the end-to-end design process for AI products, and career preparation in AI design. You will learn about AI models, key terminologies, design principles, and ethical considerations. The course includes live Q&As, discussions, mini-projects, and case studies to provide hands-on learning and practical experience.
Michael HirschMaven
This intensive 3-week program is designed for product leaders at all stages of their AI journey. Learn to navigate AI-driven landscapes, make strategic AI decisions, and lead teams through AI transformations. Gain hands-on experience with essential AI tools and frameworks, and develop AI-driven leadership skills to advance your career.
Younes Bensouda MourriDeepLearning.AI
In the Natural Language Processing Specialization, you will learn to use logistic regression, naïve Bayes, and word vectors for sentiment analysis, analogies, and translations. You will also explore dynamic programming, hidden Markov models, and word embeddings for autocorrect, autocomplete, and part-of-speech tagging. Advanced topics include dense and recurrent neural networks, LSTMs, GRUs, and Siamese networks for sentiment analysis, text generation, named entity recognition, and question identification. Finally, you will delve into encoder-decoder, causal, and self-attention models for machine translation, text summarization, question-answering, and chatbot creation.
Mahesh YadavMaven
Drawing from Mahesh Yadav's extensive experience in AI/ML product management at leading companies like Facebook, AWS, and Google, this course addresses the critical gap in understanding AI/PM product basics and technical concepts. It includes hands-on labs to build your AI product portfolio, practical lab sessions, and effective product requirement documents (PRDs). The course prepares you for real-life interview settings and your AI PM career.
Maaike GroenewegeMaven
This course provides a comprehensive introduction to designing Generative AI applications with a focus on user-centered design. You'll learn about the three core components of a well-designed GenAI application: prompts, workflows, and retrieval augmented generation. The course includes theory, hands-on projects, and the use of various GenAI tools. You'll also have the opportunity to connect with other professionals in the field and learn together in small, interactive groups.
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.
Miguel AmigotedX
In this course, you will explore the capabilities of OpenAI's advanced language model, ChatGPT, and learn how to utilize it for a wide range of applications. You will gain a comprehensive understanding of ChatGPT, its features, and limitations. By the end of the course, you will be able to use ChatGPT for various tasks, such as summarizing and expanding on a topic, building chatbots, and generating creative content.
Luis SerranoDeepLearning.AI
In this specialization, you will gain a deep understanding of the mathematical principles that underpin machine learning algorithms. You will learn how to apply statistical techniques to enhance your data analysis, and acquire skills that are highly sought after by employers. By the end of the course, you will be able to implement and optimize machine learning algorithms, making you a valuable asset in the field of AI and data science.
Rav AhujaCoursera
This specialization provides a thorough introduction to AI, covering its applications, use cases, and impact across industries. Learners will explore key concepts such as Machine Learning, Deep Learning, and Neural Networks, and gain practical experience by building and deploying an AI-enabled chatbot without coding. The course also covers IBM Watson AI services and the creation of intelligent virtual assistants, equipping learners with the skills needed to leverage AI in various scenarios.
Sharon ZhouDeepLearning.AI
Join our new short course, Finetuning Large Language Models! Learn from Sharon Zhou, Co-Founder and CEO of Lamini, and instructor for the GANs Specialization and How Diffusion Models Work. When you complete this course, you will be able to understand when to apply finetuning on LLMs, prepare your data for finetuning, and train and evaluate an LLM on your data. Finetuning allows the model to learn style, form, and can update the model with new knowledge to improve results.
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.
Mustafa KapadiaMaven
This course is designed to help Product Managers automate 30+ key PM tasks using AI within the first hour. You will learn to craft precise prompts, build the right mindset, and take automation to the next level by building agents (GPTs) without coding. The course includes interactive live sessions, lifetime access to materials, and a project to apply your learnings.
Sebastian WitalecDeepLearning.AI
In this course, you will gain the knowledge to make informed decisions about when to apply vector databases to your applications. You will explore how to use vector databases and LLMs to gain deeper insights into your data, build labs that show how to form embeddings, and use several search techniques to find similar embeddings. Additionally, you will explore algorithms for fast searches through vast datasets and build applications ranging from RAG to multilingual search.
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.
