Results for "feature engineering for ai systems"
Scrimba
Skills you'll gain: Model Context Protocol, Prompt Engineering, Retrieval-Augmented Generation, LangChain, OpenAI API, Prompt Patterns, Embeddings, Image Analysis, Responsible AI, AI Workflows, OpenAI, LLM Application, AI Integrations, Cloud Deployment, Cloud Applications, Multimodal Prompts, Memory Management, Hugging Face, Vector Databases, Software Engineering
Skills you'll gain: Prompt Engineering, Apache Spark, PyTorch (Machine Learning Library), Large Language Modeling, Retrieval-Augmented Generation, Transfer Learning, Model Evaluation, Computer Vision, Unsupervised Learning, Generative Model Architectures, Generative AI, PySpark, Prompt Engineering Tools, Vision Transformer (ViT), Keras (Neural Network Library), Vector Databases, Fine-tuning, Machine Learning, Python Programming, Data Science
Pragmatic AI Labs
Skills you'll gain: Prompt Engineering, MLOps (Machine Learning Operations), Data Pipelines, Databricks, Generative AI, Data Lakes, Generative AI Agents, Data Governance, Data Architecture, AI Enablement, Data Modeling, Data Management, Data Processing, Data Strategy, Data Quality, Scala Programming, SQL, Python Programming, Data Visualization, Data Literacy
Skills you'll gain: Responsible AI, Agentic Workflows, AI Workflows, AI Orchestration, Generative AI Agents, AI Enablement, Business Process Automation, Artificial Intelligence and Machine Learning (AI/ML), Workflow Management, LLM Application, Model Deployment, Artificial Intelligence, LangChain, Vector Databases, Agentic systems, Tool Calling, AI Security, AI Personalization, AI Product Strategy, Generative AI
Skills you'll gain: Feature Engineering, Model Evaluation, Model Deployment, Fine-tuning, Data Preprocessing, Model Training, Deep Learning, Machine Learning Methods, Model Optimization, Scikit Learn (Machine Learning Library), PyTorch (Machine Learning Library), Scalability, Hugging Face, Docker (Software), Supervised Learning, Machine Learning Algorithms, Applied Machine Learning, Application Deployment, Software Development, Machine Learning
Pragmatic AI Labs
What brings you to Coursera today?
Pragmatic AI Labs
Skills you'll gain: Amazon Bedrock, AI Security, Retrieval-Augmented Generation, Docker (Software), Prompt Engineering, GitHub Copilot, Token Optimization, Agentic Workflows, AI Orchestration, LLM Application, Debugging, Serverless Computing, Software As A Service, Model Context Protocol, Amazon Web Services, Large Language Modeling, Rust (Programming Language), Code Review, Natural Language Processing, GitHub
Microsoft
Skills you'll gain: Generative AI, Responsible AI, Generative Model Architectures, Multimodal Prompts, Prompt Engineering, MLOps (Machine Learning Operations), Generative Adversarial Networks (GANs), Azure DevOps Pipelines, AI Security, Fine-tuning, Data Ethics, AI Orchestration, AI Workflows, Model Deployment, Azure DevOps, Microsoft Azure, ChatGPT, AI Integrations, Artificial Intelligence and Machine Learning (AI/ML), Python Programming
Microsoft
Skills you'll gain: Unsupervised Learning, Fine-tuning, Model Deployment, Generative AI, Large Language Modeling, Data Management, Generative Model Architectures, Natural Language Processing, MLOps (Machine Learning Operations), Supervised Learning, Microsoft Azure, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Generative Adversarial Networks (GANs), Infrastructure Architecture, LLM Application, Responsible AI, Generative AI Agents, Data Preprocessing, Model Optimization
LearnKartS
Skills you'll gain: Agentic systems, Model Context Protocol, Vector Databases, Gemini, Generative AI Agents, Google Gemini, Retrieval-Augmented Generation, Artificial Intelligence, Generative AI, Embeddings, MongoDB, Node.JS, API Design, TypeScript, PostgreSQL, Web Applications, Systems Architecture, Database Management, Debugging, Machine Learning
Skills you'll gain: AI Orchestration, AI Workflows, LangChain, Agentic Workflows, Tool Calling, LangGraph, LLM Application, Agentic systems, Generative AI Agents, Responsible AI, Retrieval-Augmented Generation, Artificial Intelligence and Machine Learning (AI/ML), Generative AI, AI Integrations, Prompt Engineering, Large Language Modeling, Software Design Patterns, Software Development, Python Programming, Application Development
Google Cloud
Skills you'll gain: Feature Engineering, Data Preprocessing, Model Optimization, Dataflow, Tensorflow, Data Pipelines, Keras (Neural Network Library), Data Processing, Data Transformation, Applied Machine Learning, Data Modeling, Data Store, Real Time Data, Machine Learning
In summary, here are 10 of our most popular feature engineering for ai systems courses
- AI Engineering: Scrimba
- IBM AI Engineering: IBM
- Enterprise AI and Data Engineering with Databricks: Pragmatic AI Labs
- Learn AI Agents: Design, Build & Deploy: AI CERTs
- Machine Learning and Deep Learning for Software Engineers: Board Infinity
- Agile With AI: Pragmatic AI Labs
- AI Tooling: Pragmatic AI Labs
- Microsoft Generative AI Engineering: Microsoft
- Microsoft AI & ML Engineering: Microsoft
- Agentic AI Engineering: RAG, MCP & MERN: LearnKartS
