AWS Certified Data Analytics – Specialty (DAS-C01) Cert Prep: 3 Processing

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Noah Gift

1:10:57

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1. Determine Appropriate Data Processing Solution Requirements

001. Introduction to domain.mp4

00:56

002. Key concepts for Kubernetes.mp4

01:49

003. Kubernetes clusters.mp4

01:08

004. Kubernetes pods.mp4

01:06

005. Kubernetes service deployments.mp4

01:25

006. Running minikube.mp4

06:37

007. Running minikube with FastAPI.mp4

07:23

008. Building tiny containers.mp4

08:47

009. AWS App Runner API.mp4

05:31

010. PyTorch, FastAPI, and App Runner.mp4

07:48

011. AWS App Runner with C#.mp4

05:31

012. Options for container orchestration.mp4

02:16

013. AWS ECS Fargate for .NET.mp4

09:07

014. Load testing with Locust.mp4

03:25

015. SRE mindset for MLOps.mp4

05:32

016. Compute choices.mp4

01:10

017. Provisioning EC2.mp4

01:26

Description

The AWS Certified Data Analytics credential helps organizations identify and develop talent with critical skills for implementing cloud initiatives. Earning AWS Certified Data Analytics – Specialty certification validates expertise in using AWS data lakes and analytics services to get insights from data. In this course, Noah Gift focuses on the third domain of the exam: Processing. Join Noah as he examines the aspects of data processing you need to know to pass this section of the exam, including how to: determine appropriate data processing solution; design a solution for transforming and preparing data for analysis; and automate and operationalize data processing solutions.

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Amazon AWS

Noah Gift

Instructor's Courses

Author of Practical MLOps, Enterprise MLOps, Developing on AWS with C#, Pragmatic AI, and Python for DevOps. Certified on Multiple MLOps certifications including Google-Professional Machine Learning Engineer and AWS Certified Machine Learning - Specialty. Adjunct Professor at Duke MIDS & Northwestern Graduate Data Science & AI. Held business roles including CTO, general manager, consulting CTO, and cloud architect. Consults with start-ups and other companies on machine learning and cloud architecture. AWS ML Hero, Python Software Foundation Fellow, AWS Subject Matter on Machine Learning, AWS Certified Solutions Architect, AWS Certified Machine Learning Specialist, AWS Certified Big Data Specialist, Google Certified Professional Architect, and AWS Academy Accredited Instructor. Published books, videos, and courses on cloud machine learning, DevOps, Python, Data Science, Big Data and AI. ★ Specialties ★ ° Cloud-native Machine Learning and AI ° Directly teaching cutting edge skills to students that lead to jobs ° Creating world-class content in all forms ° Building Companies ° Shipping new Products ° Leading and growing engineering teams ° Production Machine Learning, Deep Learning, Big Data, and AI ° Serverless Data Engineering ° Advising Early Stage Startups/Consulting CTO services ° Distributed Systems and Scalability

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