All courses
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.
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.
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.
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.
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.
Abby MorganDeepLearning.AI
In this course, you will learn to prompt various vision models such as Meta’s Segment Anything Model (SAM), OWL-ViT, and Stable Diffusion 2.0. You will explore techniques like image generation, image segmentation, object detection, and in-painting. Additionally, you will learn to fine-tune diffusion models using DreamBooth and track your experiments with Comet. This hands-on course is designed to help you get started with prompting vision models and enhance your image generation capabilities.
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.
Amit RawalMaven
By the end of this course, you'll be adept at using AI to transform complex data into compelling stories that drive action and impact. You'll learn how AI can augment your analytical capabilities, automate tedious tasks, and provide deeper insights. The course offers step-by-step guidance and over 50 prompts to help you craft impactful narratives using data.
Sean BarnesDeepLearning.AI
This comprehensive program equips you with the skills to manage the entire data lifecycle, from defining problems to delivering insights. You'll learn foundational analysis and visualization, statistical techniques, Python for automation, and data extraction from various sources. The course also covers AI integration in analytics, preparing you for the growing demand in data-centric roles.
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.
Sebastian WitalecDeepLearning.AI
This course provides a comprehensive understanding of building multimodal search and RAG systems, focusing on the integration of various data types like text, images, and video into AI models. You will learn about contrastive learning for training multimodal models, visual instruction tuning, and the implementation of multi-vector recommender systems that enhance the capabilities of AI applications in industry settings.
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.
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.
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.
Manisha AroraMaven
This course offers a dynamic blend of technical expertise and real-world business challenges. Through a series of interactive sessions, discussions, and hands-on projects, you will learn how to scope machine learning projects effectively, lead discussions with stakeholders, navigate the entire data science workflow from data exploration to model deployment, and communicate project insights and business impact to stakeholders.
