More to explore:

Results for "Data Engineering Basics"

  • Skills you'll gain: Extract, Transform, Load, Web Scraping, Database Design, SQL, IBM DB2, Database Management, Data Store, Data Architecture, Relational Databases, Database Systems, Apache Hadoop, Databases, Big Data, Unit Testing, Database Development, Data Storage, Operational Databases, Data Import/Export, Python Programming, NumPy

  • Skills you'll gain: Data Store, Data Architecture, Apache Hadoop, Extract, Transform, Load, Relational Databases, Big Data, Data Storage, Databases, Operational Databases, Apache Spark, Data Storage Technologies, Data Lakes, Data Warehousing, Data Governance, Data Pipelines, Data Integration, Data Processing, SQL, NoSQL, Data Science

  • Skills you'll gain: Data Engineering, Snowflake Schema, Data Pipelines, Retrieval-Augmented Generation, Generative AI, Model Deployment, Data Architecture, Responsible AI, Embeddings, Data Transformation, Data Processing, Data Governance, Data Management, Data Quality, Business Logic, SQL, Data Collection, Data Entry, Data Security, Python Programming

  • Skills you'll gain: Data Lakes, Apache Spark, Databricks, Data Pipelines, PySpark, Business Intelligence, Data Warehousing, Data Architecture, Performance Tuning, Data Governance, Transaction Processing, GitHub, Dashboard, Version Control, Data Integration, Data Transformation, Data Cleansing, Analytics, Git (Version Control System), Scalability

  • Skills you'll gain: Pandas (Python Package), Data Cleansing, Data Engineering, Data Quality, Descriptive Statistics, Data Manipulation, Data Wrangling, Statistical Analysis, Data Transformation, Package and Software Management, Data Import/Export, Statistics, Data Preprocessing, Data Processing, Data Analysis, Data Validation, Exploratory Data Analysis, Data Pipelines, NumPy, Python Programming

  • Skills you'll gain: NoSQL, Extract, Transform, Load, Database Administration, Apache Spark, Data Warehousing, Web Scraping, Bash (Scripting Language), Package and Software Management, Data Pipelines, Apache Hadoop, Database Design, SQL, IBM Cognos Analytics, Data Store, Generative AI, Professional Networking, Data Import/Export, Python Programming, Data Analysis, Data Science

What brings you to Coursera today?

  • Skills you'll gain: Infrastructure Architecture, Metadata Management

  • Skills you'll gain: Databricks, CI/CD, Apache Spark, Microsoft Azure, Data Governance, Data Lakes, Data Architecture, Integration Testing, Continuous Integration, Continuous Deployment, Data Infrastructure, Real Time Data, Data Integration, Data Pipelines, IT Automation, Data Management, Automation, Data Storage, Metadata Management, File Systems

  • Skills you'll gain: Pandas (Python Package), Bash (Scripting Language), Version Control, Jupyter, Linux Commands, Git (Version Control System), Shell Script, Linux, Web Scraping, Linux Administration, Data Manipulation, MySQL, Microservices, AWS SageMaker, SQL, JSON, Command-Line Interface, Python Programming, Big Data, Data Science

  • Skills you'll gain: Ansible, Infrastructure as Code (IaC), Configuration Management, Correlation Analysis, CI/CD, Docker (Software), GitHub, Data Strategy, Collaborative Software, Git (Version Control System), Containerization, Cloud Infrastructure, Data Security, Data Pipelines, Version Control, Continuous Deployment, Continuous Integration, Devops Tools, Kubernetes, Scalability

  • Skills you'll gain: Google Cloud Platform, Data Lakes, Data Migration, DevOps, Dataflow, Cloud Management, CI/CD, Data Pipelines, Cloud Storage, Cloud Security, Cloud Computing, Cloud Engineering, Redis, Big Data, Data Management, Database Management, Google Analytics, Analytics, SQL, Query Languages

  • Skills you'll gain: Extract, Transform, Load, Web Scraping, Database Management, Databases, Unit Testing, Data Transformation, Data Access, Package and Software Management, Application Programming Interface (API), Data Integration, Data Wrangling, Integrated Development Environments, Data Pipelines, Maintainability, Python Programming, Programming Principles, Hypertext Markup Language (HTML), Style Guides