Postgraduate Certificate in Setting Up Python Cloud Infrastructure

This course is designed for IT professionals, data scientists, and software developers who aim to establish a robust Python cloud infrastructure. Participants will gain hands-on experience in setting up cloud environments, deploying Python applications, and managing cloud resources efficiently. Key topics include cloud provider services, Python deployment tools, and automation scripts for cloud operations.

Upon completion, learners will be proficient in creating scalable and secure Python applications in the cloud, leveraging automation to streamline development and deployment processes. The course equips learners with the skills to optimize cloud resources, reduce costs, and enhance application performance.

1. 1. Introduction to Python Cloud Infrastructure: Learners will understand the basics of cloud computing, Python ecosystems, and cloud infrastructure services. They will gain foundational knowledge on setting up a Python development environment in the cloud.
2. 2. Virtual Environments and Dependency Management: This module introduces learners to virtual environments and tools like pip and conda for managing dependencies in Python projects. Practical skills include creating and managing virtual environments for cloud-based Python applications.
3. 3. Cloud Providers Overview: Learners will explore major cloud providers such as AWS, Google Cloud, and Azure, focusing on their services, pricing models, and security features. Practical skills include setting up accounts and understanding basic services.
4. 4. Python in the Cloud - AWS: This module delves into AWS services relevant to Python developers, including S3, EC2, and Lambda. Learners will gain hands-on experience deploying Python applications on AWS.
5. 5. Cloud Storage Solutions: Learners will study various cloud storage options and best practices for using S3, GCS, and Azure Blob Storage. Practical skills involve setting up storage solutions and managing data in the cloud.
6. 6. Containers and Docker: This module covers Docker basics, container orchestration with Kubernetes, and deploying Python applications in containers. Learners will gain skills in building, deploying, and managing containerized Python applications.
7. 7. Serverless Computing with Python: Learners will learn to write serverless functions using AWS Lambda, Google Cloud Functions, and Azure Functions. Practical skills include designing and deploying serverless Python applications.
8. 8. Security in Python Cloud Infrastructure: This module focuses on security best practices for Python cloud applications, including authentication, authorization, and secure coding practices. Learners will gain skills to ensure the security of their Python cloud infrastructure.
9. 9. Monitoring and Logging: Learners will learn to use monitoring and logging tools like CloudWatch, Stackdriver, and Azure Monitor to track application performance and troubleshoot issues. Practical skills include setting up monitoring and logging for Python applications.
10. 10. DevOps Practices for Python Cloud Infrastructure: This module introduces DevOps principles and tools like Git, Jenkins, and Ansible for continuous integration and deployment. Learners will gain skills in automating the deployment and management of Python applications in the cloud.