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.
Chris ButlerMaven
This course dives into the new paradigms and frameworks product leaders and designers are using to incorporate AI into their products. Through case studies, live workshops, and projects, you will learn to apply ethical, bias, fairness, and other guardrails to AI/ML products. The course features real examples from GitHub, Google, Cognizant, and Facebook Reality Labs’ Portal device.
Isa FulfordDeepLearning.AI
This course teaches you how to efficiently build multi-step systems using large language models. You will learn to split complex tasks into a pipeline of subtasks using multistage prompts and evaluate your LLM inputs and outputs for safety, accuracy, and relevance. The course includes hands-on examples and built-in Jupyter notebooks to experiment with the code and prompts presented.
Krish NaikUdemy
This course provides a detailed exploration of generative AI, focusing on the integration of Langchain and Huggingface models. Participants will learn to create advanced AI applications, understand architecture and design patterns, and gain hands-on experience in deploying models across various environments. The course covers deployment strategies, RAG pipelines, and model optimization, ensuring learners can build scalable and reliable AI systems.
Mark SchaeferMaven
In this masterclass, you will learn how to create and sustain a powerful personal brand. The course covers essential topics such as staying relevant in a rapidly changing world, creating a personal brand, managing workload, and building momentum. You will receive an exclusive workbook and 1:1 coaching to help you achieve your personal branding goals.
Rav AhujaCoursera
In this course, you will explore the key concepts and applications of AI, including deep learning, machine learning, and neural networks. You'll examine generative AI models, such as large language models, and their capabilities. The course also covers AI's impact on industries like natural language processing, computer vision, and robotics, highlighting how these advancements drive innovation. Additionally, you'll delve into the ethical considerations and governance of AI, preparing you to navigate the evolving AI landscape.
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.
Mark LaurenceMaven
Participants will learn the five strategic steps to build an AI-forward business, master AI prompting, and deploy a framework-led diagnosis of their company's AI maturity. The course aims to transform senior leadership teams from AI novices to AI-literate leaders capable of driving AI adoption at scale.
Learn how AI applies to real scenarios and workflows.
Amir FeizpourMaven
This course will teach you the core principles of multi-agent LLM systems, how to design and build them, and how to integrate them into existing products. You will learn about optimizing teamwork, managing complex information flow, and ensuring security. By the end of the course, you will be able to design and build robust multi-agent LLM systems that enhance user experience, productivity, and business metrics.
Nikita NamjoshiDeepLearning.AI
In this course, you will gain a conceptual understanding of the RLHF training process, and then practice applying RLHF to tune an LLM. You will explore the two datasets that are used in RLHF training: the 'preference' and 'prompt' datasets. Use the open source Google Cloud Pipeline Components Library to fine-tune the Llama 2 model with RLHF. Assess the tuned LLM against the original base model by comparing loss curves and using the 'Side-by-Side (SxS)' method.
Amit SanganiDeepLearning.AI
In this course, you will learn best practices for prompting and selecting among the Llama 2 & 3 models by using them as a personal assistant to help you complete day-to-day tasks. You will experiment with advanced prompt engineering techniques, like few-shot prompting to get Llama 2 to classify the sentiment of text messages, and chain-of-thought prompting to solve logic problems. You will also treat Code Llama as a pair programming partner to both learn to write and improve code. Additionally, you will promote safe and responsible use of LLMs by having Llama Guard check user prompts and model responses for harmful content.
Pranav RajpurkarDeepLearning.AI
In this Specialization, you will learn to diagnose diseases from x-rays and 3D MRI brain images, predict patient survival rates using tree-based models, estimate treatment effects using data from randomized trials, and automate the labeling of medical datasets using natural language processing. The course covers model interpretation, image segmentation, natural language extraction, and more.
Travis AddairDeepLearning.AI
In this course, you will learn how auto-regressive large language models generate text one token at a time. You will implement the foundational elements of a modern LLM inference stack in code, including KV caching, continuous batching, and model quantization, and benchmark their impacts on inference throughput and latency. You will explore the details of how LoRA adapters work and learn how batching techniques allow different LoRA adapters to be served to multiple customers simultaneously. Get hands-on with Predibase’s LoRAX framework inference server to see these optimization techniques implemented in a real-world LLM inference server. Knowing more about how LLM servers operate under the hood will greatly enhance your understanding of the options you have to increase the performance and efficiency of your LLM-powered 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.
Andrew NgDeepLearning.AI
In this course, you will learn the fundamentals of generative AI, including its capabilities and limitations. You will explore various AI tools and techniques, and gain hands-on experience with generative AI applications. The course also covers the impact of AI on business and society, providing you with the knowledge to develop effective AI strategies.
Dr. Marily NikaMaven
In this course, you will learn how to run teams that integrate AI into your product strategy, work with engineering and ML Ops teams, and navigate the ethical and regulatory issues surrounding AI. The course provides hands-on experience through case studies and practical exercises, simulating real-world scenarios. You will also gain insights from guest speakers who are industry leaders in AI.
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.
Cecilia ZinitiMaven
This course will give you practical, immediately useful learnings on actual AI prompting with GC AI or general-purpose tools like ChatGPT or Claude. You'll get a great intro to how AI works, then get your hands dirty with an experienced GC and AI expert to help and push you with tips and tricks. You'll be shocked at the quality of AI legal outputs.
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.
Patrick NeemanMaven
In this course, you'll learn how to integrate AI into your design workflow, transforming from AI-curious to AI-empowered. You'll master AI assistant tools, empathy-driven design, and rapid prototyping, while gaining hands-on experience with generative AI platforms. This course will equip you with the skills to accelerate innovation, gain deeper user insights, and foster creative collaborations.
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.
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.
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 (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.
