MLOps (Machine Learning Operations)

Skills you'll gain: MLOps (Machine Learning Operations), CI/CD, Continuous Deployment, Docker (Software), Kubernetes, Containerization, Scalability, Continuous Integration, DevOps, Data Infrastructure, IT Infrastructure, Infrastructure Architecture, Cloud Infrastructure, Artificial Intelligence and Machine Learning (AI/ML), Continuous Monitoring, Real Time Data, Version Control

Skills you'll gain: MLOps (Machine Learning Operations), Google Cloud Platform, Data Management, Data Governance, Workflow Management, Tensorflow, Applied Machine Learning, Data Pipelines, Machine Learning, Cloud Computing, Data Transformation, Continuous Monitoring

Skills you'll gain: Microsoft Azure, MLOps (Machine Learning Operations), Databricks, Cloud Computing, Data Ethics, Data Pipelines, Responsible AI, Machine Learning, Information Privacy, Continuous Monitoring, Data Security, Performance Tuning, Scalability

Skills you'll gain: Generative AI, Generative AI Agents, Google Cloud Platform, MLOps (Machine Learning Operations), Artificial Intelligence and Machine Learning (AI/ML), Prompt Engineering, Tensorflow, OpenAI, AI Product Strategy, Cloud Infrastructure, Applied Machine Learning, Big Data, Machine Learning

Skills you'll gain: Feature Engineering, MLOps (Machine Learning Operations), Responsible AI, Generative AI, Tensorflow, Generative AI Agents, Google Cloud Platform, Dataflow, Keras (Neural Network Library), Data Quality, Exploratory Data Analysis, Machine Learning Methods, Machine Learning, Applied Machine Learning, Data Pipelines, Apache Airflow, Artificial Intelligence and Machine Learning (AI/ML), Scikit Learn (Machine Learning Library), Data Cleansing, Cloud Computing

Skills you'll gain: Unsupervised Learning, Scikit Learn (Machine Learning Library), PyTorch (Machine Learning Library), Exploratory Data Analysis, Deep Learning, Microsoft Azure, Data Visualization, Regression Analysis, Predictive Modeling, Data Analysis, Image Analysis, Pandas (Python Package), Jupyter, Artificial Intelligence and Machine Learning (AI/ML), Classification And Regression Tree (CART), Data Science, MLOps (Machine Learning Operations), Machine Learning, Tensorflow, Artificial Neural Networks

Skills you'll gain: Feature Engineering, Responsible AI, Tensorflow, Exploratory Data Analysis, Data Quality, Machine Learning, Applied Machine Learning, Keras (Neural Network Library), Scikit Learn (Machine Learning Library), Google Cloud Platform, MLOps (Machine Learning Operations), Supervised Learning, Machine Learning Algorithms, Data Strategy, Predictive Modeling, Artificial Neural Networks, Dataflow, Data Pipelines, Performance Tuning, Deep Learning

Skills you'll gain: MLOps (Machine Learning Operations), Generative AI, Responsible AI, Security Testing, Predictive Modeling, Verification And Validation, Data Validation, Machine Learning

Skills you'll gain: Generative AI, Large Language Modeling, MLOps (Machine Learning Operations), Artificial Intelligence, Cloud Computing, Cloud Infrastructure, Infrastructure Architecture, Data Infrastructure, Artificial Neural Networks, IT Infrastructure, Information Technology Operations, Deep Learning, Network Infrastructure, Tensorflow, Hardware Architecture, Machine Learning, PyTorch (Machine Learning Library), Data Centers, Computer Architecture

Skills you'll gain: Google Cloud Platform, MLOps (Machine Learning Operations), Tensorflow, Unstructured Data, Applied Machine Learning, Data Pipelines, Big Data, Machine Learning, Jupyter, Artificial Intelligence

Skills you'll gain: Generative AI, Artificial Intelligence and Machine Learning (AI/ML), Responsible AI, Applied Machine Learning, Data Ethics, Machine Learning Methods, Scalability, Machine Learning, Distributed Computing, MLOps (Machine Learning Operations), Ethical Standards And Conduct, Microsoft Azure, Information Privacy

Skills you'll gain: MLOps (Machine Learning Operations), Systems Design, Tensorflow, Hybrid Cloud Computing, Google Cloud Platform, Systems Architecture, Performance Tuning, Applied Machine Learning, Machine Learning, Distributed Computing, Scalability, Data Pipelines