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.
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.
Marc SunDeepLearning.AI
In this course, you will implement and customize linear quantization from scratch, studying the tradeoff between space and performance. You will build a general-purpose quantizer in PyTorch to quantize any open source model, compressing model weights from 32 bits to 8 bits and even 2 bits. This course provides the foundation to explore more advanced quantization methods.
Thomas WolfDeepLearning.AI
In this course, you'll explore the evolution of agentic systems and learn why code agents are the next big step. You'll gain insights into the core idea of code agents, their benefits, and how to run them safely using a constrained Python interpreter. By the end, you'll be equipped to build and deploy code agents, ready to optimize their performance in real-world applications.
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.
Fab GiovanettiMaven
This course offers an in-depth exploration of sustainable and ethical marketing practices. Participants will learn to craft purpose-driven strategies, communicate the importance of ethical marketing to stakeholders, and execute accessible advertising campaigns. The course combines live workshops and on-demand sessions, providing a comprehensive learning experience that encourages collaboration and personal growth.
Jorden WoodsMaven
Unlock the power of GenAI tailored to your business. This course covers AI basics, the latest techniques, and responsible AI frameworks. Gain hands-on experience in a guided workshop with both tech and non-tech tracks. Learn to design and build custom GenAI models for greater efficiency, accuracy, safety, privacy, security, and compliance. Enhance your competitive edge with domain-specific datasets and proprietary algorithms.
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.
Learn how AI applies to real scenarios and workflows.
Jerry LiuDeepLearning.AI
Join our new short course and learn from Jerry Liu, co-founder and CEO at LlamaIndex, to start using agentic RAG, a framework designed to build research agents skilled in tool use, reasoning, and decision-making with your data. You will build various types of agents, including a router agent for Q&A and summarization tasks, and a research assistant agent capable of handling multiple documents. This course will enhance your ability to engage with and analyze your data comprehensively.
Isa FulfordDeepLearning.AI
In Building Systems with the ChatGPT API, you will learn how to automate complex workflows using chain calls to a large language model. You will build chains of prompts that interact with the completions of prior prompts, systems where Python code interacts with both completions and new prompts, and a customer service chatbot using all the techniques from this course. This course is beginner-friendly and includes hands-on examples with built-in Jupyter notebooks for seamless experimentation.
Tim TullyDeepLearning.AI
In this course, you will explore the implementation of six applications using vector databases. You will learn how to create a semantic search tool, enhance LLM applications with RAG, develop a recommender system, build a hybrid search app, create a facial similarity app, and implement an anomaly detection app. By the end of the course, you will have new ideas for building applications with any vector database.
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.
Thomas WolfDeepLearning.AI
In this course, you'll explore the evolution of agentic systems and learn why code agents are the next big step. You'll gain insights into the core idea of code agents, their benefits, and how to run them safely using a constrained Python interpreter. By the end, you'll be equipped to build and deploy code agents, ready to optimize their performance in real-world applications.
Laurence MoroneyDeepLearning.AI
In this four-course Specialization, you’ll learn how to get your machine learning models into the hands of real people on all kinds of devices. Start by understanding how to train and run machine learning models in browsers and in mobile applications. Learn how to leverage built-in datasets with just a few lines of code, learn about data pipelines with TensorFlow data services, use APIs to control data splitting, process all types of unstructured data and retrain deployed models with user data while maintaining data privacy. Apply your knowledge in various deployment scenarios and get introduced to TensorFlow Serving, TensorFlow, Hub, TensorBoard, and more.
Laurence MoroneyDeepLearning.AI
In this hands-on, four-course Professional Certificate program, you’ll learn the necessary tools to build scalable AI-powered applications with TensorFlow. After finishing this program, you’ll be able to apply your new TensorFlow skills to a wide range of problems and projects. This program can help you prepare for the Google TensorFlow Certificate exam and bring you one step closer to achieving the Google TensorFlow Certificate.
James GrayMaven
In this comprehensive course, you'll master AI assistants, build AI workflows, and create multi-agent systems to automate tasks and achieve outcomes. Gain hands-on experience with cutting-edge AI tools and learn to integrate AI into your work and business, enhancing your productivity and impact.
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.
Frank KaneUdemy
In an era where Machine Learning (ML) and Artificial Intelligence (AI) are revolutionizing industries across the globe, understanding how giants like Google, Amazon, and Udemy leverage these technologies to extract meaningful insights from vast data sets is more critical than ever. Whether you're aiming to join the ranks of top-tier AI specialists or you're driven by the fascinating challenges this field offers, our course is your gateway to an exciting new career trajectory. Designed for individuals with programming or scripting backgrounds, this course goes beyond the basics, preparing you to stand out in the competitive tech industry. Our curriculum, enriched with over 145 lectures and 20+ hours of video content, is crafted to provide hands-on experience with Python, guiding you from the fundamentals of statistics to the cutting-edge advancements in generative AI.
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.
Dr. Marily NikaMaven
In this comprehensive workshop, you will learn how to approach AI Product Management interviews with confidence. Dr. Marily Nika will guide you through three main interview themes: Product Sense, Execution/Analytical, and Strategy Insight. You will get the opportunity to practice live in a safe space, gain access to valuable resources, and receive direct feedback from the instructor. This workshop is designed to help you succeed in AI PM interviews, whether you are an aspiring AI PM, a recent graduate, an experienced PM or ML Engineer, or a team lead.
Vasudev LalDeepLearning.AI
In this course, you will delve into the fascinating realm of Multimodal RAG, learning how to effectively chat with videos. The course offers a comprehensive understanding of generative AI, supported by practical code examples and video lessons. Designed for intermediate learners, it provides a unique opportunity to expand your AI knowledge and skills.
Sung KimDeepLearning.AI
This course provides a comprehensive understanding of pretraining large language models. You'll learn to prepare data, configure models, and assess performance, with a focus on cost-effective strategies. The course covers creating high-quality datasets, using the Hugging Face library, and evaluating model performance with benchmark tasks.
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.
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.
