Certificate in Serverless for Data Scientists
-- ViewingNowThe Certificate in Serverless for Data Scientists is a comprehensive course designed to equip learners with the essential skills required to build and deploy serverless data science solutions in the cloud. This course is of paramount importance due to the increasing demand for serverless architectures that offer improved scalability and reduced costs in the data science industry.
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⢠Introduction to Serverless Architectures – Understanding the basics of serverless architectures, their benefits, and how they differ from traditional architectures.
⢠Serverless Data Processing &ndsh; Exploring data processing tools and services in a serverless environment, such as AWS Glue, AWS Lambda, and Google Cloud Functions.
⢠Data Storage Options in Serverless Architectures – Examining various data storage options like Amazon S3, DynamoDB, and Google Cloud Storage.
⢠Serverless Machine Learning – Delving into machine learning libraries and frameworks for serverless architectures, such as TensorFlow, PyTorch, and scikit-learn.
⢠Deploying Serverless Data Science Workflows – Learning to deploy data science workflows using tools like Apache Airflow, Kubeflow, and TFX.
⢠Monitoring and Optimizing Serverless Data Science Applications – Understanding how to monitor and optimize serverless data science applications using tools like CloudWatch, Datadog, and New Relic.
⢠Security Best Practices for Serverless Data Science – Exploring security best practices, including identity and access management, data encryption, and network security.
⢠Serverless Data Science Use Cases – Examining real-world use cases and case studies of serverless data science in action.
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