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Engenharia de Dados\n\nRepositório dos exercícios e projetos do curso de Engenharia de Dados da Ada em parceria com o Santander (em andamento).\n\nConteúdo didático do curso:\n* Módulo I: Lógica de Programação em Python II\n  - Listas;\n  - Tuplas;\n  - Dicionários;\n  - Compreensão de listas;\n  - Expressões geradoras;\n  - Strings;\n  - Funções;\n  - Programação funcional;\n  - Tratamento de exceções;\n  - Arquivos.\n    \n* Módulo II: Programação Orientada a Objetos\n  - Paradigmas de programação;\n  - Classes e objetos;\n  - Módulos e pacotes;\n  - Atributos privados e métodos de acesso;\n  - Métodos mágicos;\n  - Atributos e métodos estáticos;\n  - Herança e polimorfismo.\n\n* Módulo III: Técnicas de Programação em Python I\n  - Git e GitHub;\n  - NumPy;\n  - Pandas.\n\n* Módulo IV: Extração de Dados I\n  - Databricks;\n  - ETL e ELT;\n  - APIs;\n  - Armazenamento de dados;\n  - Apache Spark;\n  - Arquitetura orientada a eventos;\n  - Apache Kafka.\n\n* Módulo V: Analytics Engineering\n  - Boas Práticas Para Tratamento de Dados (Analytics);\n  - Data Quality, Data Clean e Testes;\n  - Validando dados com Great Expectations;\n  - Especializando dados através do dbt - data build tool.\n \n* Módulo VI: Big Data\n  - Big Data;\n  - Apache Hadoop;\n  - Cloud computing;\n  - Databricks;\n  - Apache Hive;\n  - Spark;\n  - Delta Lake;\n  - Otimizações e Engenharia de Dados com Spark;\n  - Spark Streaming.\n  \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmpbeatriz%2Fsantander_coders_2024","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmpbeatriz%2Fsantander_coders_2024","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmpbeatriz%2Fsantander_coders_2024/lists"}