AI for Data

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.

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.

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 solutions using cutting-edge technologies like LLM APIs, vector databases, and AI agent libraries. The course emphasizes practical application, with each concept directly applied to a capstone project, ensuring learners gain real-world engineering skills.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

João AscensãoOne Month PM

This course covers everything from the basics of AI and data science to advanced product management techniques. You will learn how to frame AI problems, develop AI products, and strategize using data. The course also includes live Q&A sessions with industry leaders, providing practical insights into managing AI-driven products.