All courses
Aurimas GriciūnasMaven
This bootcamp offers a comprehensive journey into AI engineering, focusing on building production-grade AI systems. Participants will learn to design, build, and deploy AI applications using cutting-edge technologies like LLM APIs, vector databases, and AI agent libraries. The course emphasizes practical skills, enabling learners to create a capstone project that demonstrates their ability to solve real-world business challenges.
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.
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.
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.
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.
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.
Doug TurnbullMaven
In this course, you'll learn how to enhance your search engine's relevance using Large Language Models (LLMs). The course covers query and document understanding, deploying LLMs to production, and making unstructured search structured. You'll gain insights into modern search techniques, helping your team achieve better outcomes faster.
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.
Manish GuptaMaven
In this course, you will learn to curate an AI toolkit designed for your goals, craft effective prompts for AI models, create customized models for unique needs, analyze financial statements and big data, manage your finance team effectively, and create strategic plans through market research and analysis. The course includes interactive live sessions, lifetime access to course materials, 15 in-depth lessons, direct access to the instructor, 7 projects to apply learnings, guided feedback, and a private community of peers.
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.
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.
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.
Andreas KolleggerDeepLearning.AI
In this course, you will learn the basics of how knowledge graphs store data using nodes and edges, use Neo4j’s query language Cypher to retrieve information, add a vector index to a knowledge graph, and build a knowledge graph of text documents from scratch. You will also explore advanced techniques for connecting multiple knowledge graphs and using complex queries for comprehensive data retrieval. By the end of the course, you will be well-equipped to use knowledge graphs to uncover deeper insights in your data and enhance the performance of LLMs with structured, relevant context.
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.
Miguel AmigotedX
In this course, you will gain a deep understanding of ChatGPT's capabilities and limitations, including its use cases in data, coding, and tech. You will develop proficiency in using ChatGPT for generating code programmatically, from ideation to testing and debugging. Explore the applications of ChatGPT in architecture and design, code rewriting, and other areas of programming. Learn how to integrate ChatGPT into your programming workflow and leverage its human-like conversation capabilities to enhance productivity.
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.
