Module #16 Cloud Cost Optimization Strategies Techniques for optimizing cloud costs for data science workloads
Module #17 Cloud Architecture for Data Science Designing scalable and efficient cloud architectures for data science workloads
Module #18 Cloud-based Collaboration and Version Control Collaboration and version control tools for data science teams in the cloud (GitHub, GitLab, Bitbucket)
Module #19 Cloud-based Monitoring and Logging Monitoring and logging tools for cloud-based data science workloads
Module #20 Cloud-based Backup and Recovery Backup and recovery strategies for cloud-based data science workloads
Module #21 Cloud Security for Data Science Security best practices for data science workloads in the cloud
Module #22 Cloud Compliance and Governance Compliance and governance considerations for cloud-based data science workloads
Module #23 Migrating Data Science Workloads to the Cloud Strategies for migrating on-premises data science workloads to the cloud
Module #24 Building a Cloud-based Data Science Team Organizational considerations for building a cloud-based data science team
Module #25 Course Wrap-Up & Conclusion Planning next steps in Cloud Infrastructure for Data Science career
