Git, Docker & CI/CD: DevOps Foundations for Data Engineers

Transform your data deployment process from manual to automated with enterprise-grade CI/CD pipelines. In today's fast-paced data environment, manual deployments are error-prone, time-consuming, and simply unsustainable at scale. This Short Course was created to help data management and engineering professionals accomplish seamless, reliable data pipeline deployments through automation. By completing this course, you'll be able to configure GitHub Actions workflows that automatically run unit tests, build Docker images, push to registries, and trigger production deployments - skills you can implement immediately in your next project. You'll master the essential automation techniques that separate junior practitioners from seasoned professionals who build production-grade data systems. By the end of this course, you will be able to: Apply CI/CD pipelines to promote data pipeline artifacts between environments safely and reliably This course is unique because it focuses specifically on data pipeline deployment automation, bridging the gap between traditional software CI/CD practices and the unique requirements of data engineering workflows. To be successful in this project, you should have a background in basic data pipeline concepts, familiarity with Git version control, and understanding of Docker fundamentals.

Did you know that over 80% of merge conflicts and hidden bugs in collaborative projects can be traced back to mismanaged version control workflows? Mastering Git conflict resolution and debugging techniques ensures cleaner, more stable codebases. This Short Course was created to help professionals in this field maintain code stability and diagnose complex issues in collaborative data engineering environments with confidence and systematic precision. By completing this course, you will be able to resolve complex merge conflicts, trace bugs through commit histories, and apply version control strategies that safeguard team productivity and code reliability—skills essential for high-quality software delivery. By the end of this 3-hour long course, you will be able to: Apply techniques to resolve complex merge conflicts in text and binary files. Analyze commit history to trace the introduction of a bug. This course is unique because it combines hands-on Git problem-solving with advanced debugging workflows, teaching you how to pinpoint issues quickly, prevent code regressions, and collaborate efficiently across distributed teams. To be successful in this project, you should have: Basic Git commands (add, commit, push, pull) Understanding of version control concepts Command-line familiarity Experience using a text editor Did you know that over 80% of merge conflicts and hidden bugs in collaborative projects can be traced back to mismanaged version control workflows? Mastering Git conflict resolution and debugging techniques ensures cleaner, more stable codebases. This Short Course was created to help professionals in this field maintain code stability and diagnose complex issues in collaborative data engineering environments with confidence and systematic precision. By completing this course, you will be able to resolve complex merge conflicts, trace bugs through commit histories, and apply version control strategies that safeguard team productivity and code reliability—skills essential for high-quality software delivery. By the end of this 3-hour long course, you will be able to: Apply techniques to resolve complex merge conflicts in text and binary files. Analyze commit history to trace the introduction of a bug. This course is unique because it combines hands-on Git problem-solving with advanced debugging workflows, teaching you how to pinpoint issues quickly, prevent code regressions, and collaborate efficiently across distributed teams. To be successful in this project, you should have: Basic Git commands (add, commit, push, pull) Understanding of version control concepts Command-line familiarity Experience using a text editor

Course Description: Automate Software Installation with Ansible Did you know that automating server setup can reduce configuration time by over 70% while virtually eliminating human error? Consistent, repeatable environments are the foundation of reliable data pipelines. This Short Course was created to help data engineering professionals automate infrastructure provisioning and ensure consistent, scalable server environments for data pipeline deployments. By completing this course, you will be able to use Ansible to automate software installation on servers, streamline configuration steps, and enforce reliability across your infrastructure—skills that improve deployment speed and operational consistency. By the end of this 2-hour long course, you will be able to: Apply an automation tool to install software on a server. This course is unique because it blends hands-on automation with practical server management, giving you real-world experience in building reproducible, scalable environments using industry-standard tools. To be successful in this project, you should have: Basic Linux command line knowledge Understanding of server administration concepts Familiarity with text editors Did you know that automating server setup can reduce configuration time by over 70% while virtually eliminating human error? Consistent, repeatable environments are the foundation of reliable data pipelines. This Short Course was created to help data engineering professionals automate infrastructure provisioning and ensure consistent, scalable server environments for data pipeline deployments. By completing this course, you will be able to use Ansible to automate software installation on servers, streamline configuration steps, and enforce reliability across your infrastructure—skills that improve deployment speed and operational consistency. By the end of this 2-hour long course, you will be able to: Apply an automation tool to install software on a server. This course is unique because it blends hands-on automation with practical server management, giving you real-world experience in building reproducible, scalable environments using industry-standard tools. To be successful in this project, you should have: Basic Linux command line knowledge Understanding of server administration concepts Familiarity with text editors

Transform your data engineering workflows with enterprise-grade containerization skills that eliminate "works on my machine" problems forever. This Short Course empowers data engineers to master the critical containerization pipeline from development to production deployment. By completing this course, you'll confidently create robust Dockerfiles that package complex data processing environments, systematically version and tag container images for release management, and seamlessly integrate with cloud-native deployment pipelines. You'll discover how to eliminate environment inconsistencies, accelerate team collaboration, and establish the foundation for scalable, reproducible data infrastructure. By the end of this course, you will be able to: - Apply containerization to build and publish versioned images with runtime dependencies This course is unique because it bridges the gap between development containerization and production-ready deployment, focusing specifically on data engineering use cases with hands-on experience using industry-standard tools like Amazon ECR and Kubernetes. To be successful in this course, you should have basic familiarity with command-line interfaces, understanding of software dependencies, and exposure to data processing concepts.

Provision Secure Cloud Data Infrastructure Did you know that nearly 45% of cloud data breaches stem from misconfigured infrastructure? Building a secure cloud foundation is the first step toward protecting sensitive data and maintaining compliance at scale. This Short Course was created to help professionals in this field build secure, compliant data platforms using Infrastructure as Code while ensuring proper encryption, access controls, and network isolation for enterprise-grade deployments. By completing this course, you will be able to provision cloud-based data infrastructure with built-in security controls, automate environment setup, and apply best practices for protecting data integrity and privacy—skills that enhance both performance and compliance. By the end of this 3-hour long course, you will be able to: Apply cloud services to provision a secure data infrastructure. This course is unique because it combines cloud engineering with data security principles, giving you hands-on experience in deploying scalable, compliant environments that safeguard enterprise information from the ground up. To be successful in this project, you should have: Basic cloud concepts Command-line experience Understanding of data storage fundamentals

Master the essential skills for designing robust version control workflows that enable seamless parallel development. This course empowers you to architect structured branching strategies that govern how code evolves from initial concept to production-ready release. This Short Course was created to help data management and engineering professionals accomplish effective team collaboration through strategic branch management. By completing this course, you'll be able to design formal workflows for managing code changes, establish conventions for concurrent development, and implement GitHub protection rules that ensure stable, scalable collaborative environments. You'll transform from reactive code management to proactive workflow design that scales with your team's growth. By the end of this course, you will be able to: Create a version control branching strategy to enable concurrent development and release cycles Design structured workflows with clear branch hierarchies and merge protocols Implement GitHub protected branch policies for enterprise-grade code management This course is unique because it combines theoretical branching models with hands-on GitHub implementation, giving you both the strategic understanding and practical tools needed for immediate workplace application. To be successful in this project, you should have a background in basic Git version control concepts, familiarity with collaborative development environments, and understanding of software development lifecycle principles.

Transform your data engineering impact by mastering advanced SQL analytics that drive critical business decisions. Data teams lose millions annually due to poor pipeline monitoring, inefficient scaling decisions, and missed data relationships that could unlock strategic insights. This Short Course was created to help data engineering professionals accomplish measurable business impact through sophisticated SQL analytics. By completing this course, you'll be able to build comprehensive monitoring dashboards that prevent costly pipeline failures, create ROI-backed infrastructure recommendations that optimize budget allocation, and identify hidden data correlations that reveal new business opportunities you can apply immediately in your role. By the end of this course, you will be able to: - Apply SQL to build dashboards for monitoring pipeline performance - Evaluate warehouse scaling strategies to deliver ROI-backed recommendations - Apply correlation techniques to measure the association between numeric variables This course is unique because it bridges the gap between technical SQL skills and strategic business value, teaching you to translate complex data operations into executive-ready insights and financial justifications. To be successful in this project, you should have a solid foundation in intermediate SQL, experience with data warehousing concepts, and familiarity with basic performance metrics and business analytics principles.