Harrison ChaseDeepLearning.AI

In LangChain for LLM Application Development, you will gain essential skills in expanding the use cases and capabilities of language models in application development using the LangChain framework. You will learn about models, prompts, parsers, memories for LLMs, chains, question answering over documents, and agents. By the end of the course, you will have a model that can serve as a starting point for your own exploration of diffusion models for your applications.

Sharon ZhouDeepLearning.AI

In this course, you will learn to improve the accuracy of LLM applications by understanding development steps from evaluation to fine-tuning. You will explore memory tuning to enhance model performance and use the Llama 3-8b model to build an LLM application that converts text to SQL. The course covers prompt engineering, self-reflection, and fine-tuning techniques like LoRA and memory tuning to reduce hallucinations.

Bernease HermanDeepLearning.AI

In this course, you will explore new metrics and best practices to monitor your LLM systems and ensure safety and quality. You will learn to identify hallucinations, detect jailbreaks, and identify data leakage. Additionally, you will build your own monitoring system to evaluate app safety and security over time. By the end of the course, you will be able to identify common security concerns in LLM-based applications and customize your safety and security evaluation tools.

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.

Ritesh VajariyaMaven

This course empowers you to lead the AI revolution in your organization. It bridges the gap between technical knowledge and strategic leadership, positioning you at the forefront of the AI evolution. You'll explore AI's essence, its real-world applications, and its business-revolutionizing potential. Equip yourself to spearhead AI initiatives, make informed decisions, and champion ethical AI use.

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.

Aman KhanMaven

In this course, you'll learn to build and deploy functional AI agents, define AI roadmaps, and evaluate AI product performance with robust metrics. You'll gain hands-on experience in prototyping, collaborating with AI engineers, and developing AI product strategies. This course is designed for PMs looking to transition from understanding AI concepts to shipping successful AI products.

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.

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.

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.

Anshul RamachandranDeepLearning.AI

In this course, you'll explore the evolution of AI coding assistants and learn how to use Windsurf to code and build several applications. You'll gain insights into the challenges of AI coding agents, such as code search and discovery, and learn to manage unexpected AI behavior. By the end, you'll understand agentic coding in-depth and be able to use it to make your development process more efficient.

Maaike GroenewegeMaven

This course provides a comprehensive introduction to designing Generative AI applications with a focus on user-centered design. You'll learn about the three core components of a well-designed GenAI application: prompts, workflows, and retrieval augmented generation. The course includes theory, hands-on projects, and the use of various GenAI tools. You'll also have the opportunity to connect with other professionals in the field and learn together in small, interactive groups.

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.

Michele CatastaDeepLearning.AI

In this course, you'll explore the growing practice of 'vibe coding' where AI coding agents assist in the development process. You'll learn to structure your work, refine prompts, and use frameworks for cleaner, more efficient code. By building two web applications, you'll gain hands-on experience with Replit's tools and improve your development skills.

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.

Harrison ChaseDeepLearning.AI

In this course, you will learn how to build an agent with long-term memory by creating a personal email agent that can respond, ignore, and notify the user using writing, scheduling, and memory tools. You’ll develop your agent’s memory by adding facts to its memory store, providing examples to learn the user’s preferences, and optimizing system prompts to evolve instructions based on previous responses. This course will equip you with the skills to integrate semantic, episodic, and procedural memory into AI agents, enhancing their functionality and user interaction.

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.

Heidi CulbertsonMaven

In this course, you will learn how to design world-class bots by understanding conversation across the lifespan. You will explore how human communication evolves as we grow up and how to apply this knowledge to create usable conversational products. The course covers developing use cases, applying linguistics and cognition knowledge, training bots, crafting responses, prototyping, and usability testing. By the end of the course, you will have actionable knowledge, frameworks, and techniques to design better bots.

Jiantao JiaoDeepLearning.AI

In this course, you will learn two critical skills for building applications with LLMs: function-calling and structured data extraction. You will work with NexusRavenV2-13B, an open-source model fine-tuned for these tasks. The course covers forming prompts with function definitions, using LLM responses to call functions, handling multiple function calls, and building applications that process customer service transcripts. These skills will enable you to create advanced AI agents and assistants for various real-world applications.

Younes Bensouda MourriDeepLearning.AI

In the Natural Language Processing Specialization, you will learn to use logistic regression, naïve Bayes, and word vectors for sentiment analysis, analogies, and translations. You will also explore dynamic programming, hidden Markov models, and word embeddings for autocorrect, autocomplete, and part-of-speech tagging. Advanced topics include dense and recurrent neural networks, LSTMs, GRUs, and Siamese networks for sentiment analysis, text generation, named entity recognition, and question identification. Finally, you will delve into encoder-decoder, causal, and self-attention models for machine translation, text summarization, question-answering, and chatbot creation.

Colt SteeleDeepLearning.AI

In this course, you will learn about Anthropic's approach to AI research, principles of AI safety, and the key differences between its models. You will gain hands-on experience with API requests, multimodal prompting, and tool use, culminating in a demo that combines these features to build an AI assistant capable of using a computer. This course is perfect for those looking to explore the cutting-edge capabilities of AI models in practical applications.

Ishan AnandMaven

This course demystifies AI and teaches you exactly how Large Language Models (LLMs) like GPT-2 work, with no prerequisites beyond a STEM background. Using a unique spreadsheet implementation of GPT-2, we’ll break down each model component with crystal-clear explanations. Gain AI literacy, build a foundation for further AI projects, and confidently lead AI-driven teams.

Karina NguyenDeepLearning.AI

In this course, you'll learn to use OpenAI Canvas to enhance your writing and coding. Discover how to collaborate with ChatGPT for brainstorming, drafting, and refining text or code. Learn to build practical use cases like creating a game app, generating Python code from plot screenshots, and creating SQL databases from architecture images. Understand the model training and design processes that power Canvas.

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.