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30-days-of-python

30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw

adb-ds-bootcamp-221020

Azure Databricks Data Science Bootcamp 20 October 2022

advanced-data-engineering-with-databricks

algorithm-data-structures-python

Various useful data structures in Python

amazon-deequ-glue

Automated data quality suggestions and analysis with Deequ on AWS Glue

amazon-kinesis-client-python

Amazon Kinesis Client Library for Python

amazon-redshift-utils

Amazon Redshift Utils contains utilities, scripts and view which are useful in a Redshift environment

analysing-realtime-streaming-data-using-msk-emr

apache-kafka-in-python

apache-spark-assignment-1

The Assignment 1 contains three questions and will ask one to get familiar with aspects of Apache Spark. While first two questions requires one to get familiar with Spark programming, the last question will ask one to understand an existing code and explain it in simple terms.

apache-spark-hands-on

Educational notes,Hands on problems w/ solutions for hadoop ecosystem

apache_spark_pptx

approachingalmost

Approaching (Almost) Any Machine Learning Problem

around-dataengineering

A Data Engineering & Machine Learning Knowledge Hub

athena-glue-service-logs

Glue scripts for converting AWS Service Logs for use in Athena

awesome-distributed-systems

A curated list to learn about distributed systems

awesome-neo4j

A curated list of Neo4j resources.

awesome-software-architecture

A curated list of awesome articles and resources to learn and practice about software architecture, patterns, and principles.

aws-analytics-reference-architecture

aws-batch-processing-job-repo

Orchestrating an Application Process with AWS Batch using AWS CloudFormation

aws-batch-runtime-monitoring

aws-data-wrangler

Pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).

aws-etl-orchestrator

A serverless architecture for orchestrating ETL jobs in arbitrarily-complex workflows using AWS Step Functions and AWS Lambda.

aws-glue-libs

AWS Glue Libraries are additions and enhancements to Spark for ETL operations.

aws-glue-quota-audit-framework

This aws sample code base implements Lambda logic to schedule only limited Glue jobs based on resource constraints

aws-glue-samples

AWS Glue code samples

aws-lambda-sap-odp-extractor

Extract data from SAP applications using Operational Data Provisioning

aws-modern-application-workshop

A tutorial for developers that want to learn about how to build modern applications on top of AWS. You will build a sample website that leverages infrastructure as code, containers, serverless code functions, CI/CD, and more.

aws-serverless-data-lake-framework

Enterprise-grade, production-hardened, serverless data lake on AWS

aws-stepfunctions-examples

AWS Step Functions is an orchestration service for reliably executing multi-step processes using visual workflows. This repository includes detailed examples that will help you unlock the power of serverless workflow.