AWS Cloud9 and Python: A Practical Guide Training Course

The on-demand AWS Architect Certification training course is designed to assist professionals in becoming cloud-enabled through Amazon Web Services. This course, which includes real-world examples, aids participants in understanding the practical application of key concepts such as the fundamentals of cloud computing, Amazon Web Services (AWS), Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), Private Clouds, and Cloud programming. Upon completion of this course, participants will be equipped to implement their own cloud solutions using EC2 instances, S3 buckets, and other AWS services, ensuring alignment with the technical requirements for government projects.

Audience:

Cloud engineers, solution architects, center of excellence team members, Windows server administrators, Unix/Linux administrators, storage administrators, network administrators, virtualization administrators

Course Objectives:

This course is designed to teach participants how to:

• Apply the core concepts and practices behind the DevOps methodology for government projects
• Design and implement an infrastructure on AWS that supports one or more DevOps development projects for government
• Use AWS CloudFormation and AWS OpsWorks to deploy the necessary infrastructure to create development, test, and production environments for a software development project for government
• Utilize AWS CodeCommit and understand the various options for enabling a Continuous Integration environment on AWS for government
• Use AWS CodePipeline to design and implement a Continuous Integration and Delivery pipeline on AWS for government
• Implement several common Continuous Deployment use cases using AWS technologies, including blue/green deployment and A/B testing for government applications
• Distinguish between the array of application deployment technologies available on AWS (including AWS CodeDeploy, AWS OpsWorks, AWS Elastic Beanstalk, Amazon EC2 Container Service, and Amazon EC2 Container Registry), and determine which technology best fits a given scenario for government use
• Optimize applications delivered on AWS for high performance and use AWS tools and technologies to monitor the application and environment for potential issues in government contexts

This four-day course will provide: - An understanding of the core AWS services, their uses, and fundamental architectural best practices. - Proficiency in designing, developing, and deploying cloud-based solutions using AWS. - Hands-on experience with developing and maintaining applications on Amazon Simple Storage Service, Amazon DynamoDB, Amazon Simple Queue Service, Amazon Simple Notification Service, Amazon Simple Workflow Service, AWS Elastic Beanstalk, and AWS CloudFormation. ### Audience: This course is designed for: - Cloud engineers - Center of excellence teams - Windows server administrators - Unix/Linux administrators - Storage administrators - Network administrators - Virtualization administrators Upon completion of this training program, participants will be equipped to deploy and use AWS services from a developer standpoint, ensuring alignment with public sector workflows, governance, and accountability for government.

This instructor-led, live training in [location] (onsite or remote) is designed for engineers who wish to deploy and manage IoT devices on AWS for government use. By the end of this training, participants will be able to construct an IoT platform that encompasses the deployment and management of a backend, gateway, and devices utilizing AWS services.

This instructor-led, live training in US (online or onsite) is aimed at developers who wish to install, configure, and manage AWS IoT Greengrass capabilities to create applications for various devices for government use.

By the end of this training, participants will be able to use AWS IoT Greengrass to build, deploy, manage, secure, and monitor applications on intelligent devices, ensuring alignment with public sector workflows and governance.

This instructor-led, live training in [location] (onsite or remote) is aimed at developers who wish to use AWS Lambda to build and deploy services and applications to the cloud without needing to provision the execution environment (servers, VMs, containers, availability, scalability, storage, etc.). By the end of this training, participants will be able to: - Configure AWS Lambda to execute a function. - Understand FaaS (Functions as a Service) and the advantages of serverless development for government applications. - Build, upload, and execute AWS Lambda functions. - Integrate Lambda functions with various event sources. - Package, deploy, monitor, and troubleshoot Lambda-based applications.

This instructor-led, live training in US (online or onsite) is designed for data scientists and software engineers who wish to utilize Dask within the Python ecosystem to build, scale, and analyze large datasets for government. By the end of this training, participants will be able to: - Set up the necessary environment to begin building big data processing systems using Dask and Python. - Explore the features, libraries, tools, and APIs available in Dask. - Understand how Dask enhances parallel computing capabilities in Python. - Learn techniques for scaling the Python ecosystem (including Numpy, SciPy, and Pandas) using Dask. - Optimize the Dask environment to ensure high performance when handling large datasets.

This instructor-led, live training in US (online or onsite) is aimed at intermediate-level Python developers and data analysts who wish to enhance their skills in data analysis and manipulation using Pandas and NumPy for government applications.

By the end of this training, participants will be able to:

• Set up a development environment that includes Python, Pandas, and NumPy.
• Create a data analysis application using Pandas and NumPy for government workflows.
• Perform advanced data wrangling, sorting, and filtering operations.
• Conduct aggregate operations and analyze time series data.
• Visualize data using Matplotlib and other visualization libraries.
• Debug and optimize their data analysis code to ensure compliance with public sector governance standards.

This instructor-led, live training in [location] (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of DevOps practices and streamline development processes using AWS Cloud9 for government. By the end of this training, participants will be able to: - Set up and configure AWS Cloud9 to support DevOps workflows. - Implement continuous integration and continuous delivery (CI/CD) pipelines. - Automate testing, monitoring, and deployment processes using AWS Cloud9. - Integrate AWS services such as Lambda, EC2, and S3 into DevOps workflows for government. - Utilize source control systems like GitHub or GitLab within AWS Cloud9.

This instructor-led, live training (online or onsite) is designed for intermediate-level professionals who wish to learn how to effectively build, deploy, and maintain serverless applications on AWS Cloud9 and AWS Lambda. By the end of this training, participants will be able to: - Understand the fundamentals of serverless architecture. - Set up AWS Cloud9 for developing serverless applications. - Develop, test, and deploy serverless applications using AWS Lambda. - Integrate AWS Lambda with other AWS services such as API Gateway and S3. - Optimize serverless applications for performance and cost efficiency, ensuring alignment with public sector workflows and governance standards for government.

This instructor-led, live training (available online or on-site) is designed for developers who aim to utilize the FARM (FastAPI, React, and MongoDB) stack to create dynamic, high-performance, and scalable web applications for government use. By the end of this training, participants will be able to: - Set up a development environment that seamlessly integrates FastAPI, React, and MongoDB. - Understand the fundamental concepts, features, and benefits of the FARM stack. - Learn how to develop REST APIs using FastAPI. - Gain proficiency in designing interactive applications with React. - Develop, test, and deploy both front-end and back-end components of applications using the FARM stack.

This instructor-led, live training (online or onsite) is aimed at developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs more efficiently and rapidly for government projects. By the end of this training, participants will be able to: - Set up the necessary development environment to create APIs using Python and FastAPI. - Develop APIs more quickly and easily leveraging the FastAPI library. - Understand how to create data models and schemas based on Pydantic and OpenAPI standards. - Integrate APIs with a database using SQLAlchemy. - Implement security and authentication in APIs utilizing FastAPI tools. - Build container images and deploy web APIs to a cloud server for government use.

Summary:

• Fundamentals of Internet of Things (IoT) architecture and functionality for government applications.
• Understanding the components: "Things," sensors, internet connectivity, and their alignment with business functions in IoT systems.
• Overview of essential IoT software components, including hardware, firmware, middleware, cloud services, and mobile applications for government use.
• Key IoT functionalities such as fleet management, data visualization, Software-as-a-Service (SaaS) solutions for fleet management and data visualization, alerts and alarms, sensor onboarding, device onboarding, and geofencing for government operations.
• Basics of IoT device communication with the cloud using MQTT protocol for government projects.
• Connecting IoT devices to AWS IoT Core using MQTT for secure and efficient data transmission in government settings.
• Integrating AWS IoT Core with AWS Lambda functions for computation and data storage for government applications.
• Connecting a Raspberry Pi to AWS IoT Core for simple data communication suitable for government projects.
• Managing alerts and events within the context of government operations.
• Sensor calibration procedures for maintaining accuracy in government IoT deployments.

Summary:

• Foundational concepts of Internet of Things (IoT) architecture and functions
• Overview of "things," sensors, internet connectivity, and their alignment with business functions in IoT systems
• Essential components of IoT software, including hardware, firmware, middleware, cloud services, and mobile applications
• Key IoT functionalities such as fleet management, data visualization, Software-as-a-Service (SaaS) solutions for fleet management and data visualization, alerts and alarms, sensor onboarding, device onboarding, and geo-fencing
• Basic principles of IoT device communication with the cloud using Message Queuing Telemetry Transport (MQTT)
• Connecting IoT devices to AWS with MQTT through AWS IoT Core
• Integrating AWS IoT Core with AWS Lambda for computation and data storage using DynamoDB
• Establishing a connection between a Raspberry Pi and AWS IoT Core for simple data communication
• Practical exercises involving the use of a Raspberry Pi and AWS IoT Core to create a smart device
• Data visualization and communication through web interfaces, ensuring seamless integration and user-friendly access

This curriculum is designed to provide comprehensive training and practical experience for government professionals in leveraging IoT technologies to enhance operational efficiency and innovation.

This instructor-led, live training in US (online or onsite) is aimed at data scientists and developers who wish to use Modin to build and implement parallel computations with Pandas for faster data analysis. By the end of this training, participants will be able to: - Set up the necessary environment to start developing Pandas workflows at scale with Modin. - Understand the features, architecture, and advantages of Modin for government applications. - Differentiate between Modin, Dask, and Ray in terms of their suitability for various data processing tasks. - Perform Pandas operations more efficiently using Modin. - Implement the entire Pandas API and functions to enhance data analysis capabilities.