AWS Cloud9 and Python: A Practical Guide Training Course

This instructor-led, live training in Macao (online or onsite) is aimed at beginner-level to intermediate-level system administrators and IT professionals who wish to gain hands-on experience in managing AWS cloud services and prepare for the AWS Certified SysOps Administrator - Associate exam.

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

• Set up and configure AWS services and resources securely.
• Manage user identities, permissions, and access to AWS resources.
• Design and deploy scalable, highly available, and fault-tolerant systems on AWS.
• Implement and manage data flow to and from AWS.
• Optimize AWS service usage to ensure efficient operation and cost management.

This instructor-led, live training in Macao (online or onsite) is aimed at cloud engineers wishing to understand and implement the more complex aspects of AWS architecture. The course covers many of the same topics as the AWS Certified Solutions Architect (Professional) level courses. However, this course is NOT intended to prepare participants to take an exam. This is a hands-on, practical course that demonstrates how to implement in a live lab environment many of the configurations, implementations, and deployments that an AWS Solutions Architect would need to carry out.

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

• Design complex cloud solutions on AWS.
• Deploy software applications on AWS that are scalable, highly available, and fault-tolerant.
• Integrate the most appropriate AWS services with an application.
• Migrate a complex software application to AWS.
• Apply best practices to the design, implementation, optimization and deployment of infrastructure and applications on AWS.

This instructor-led, live training in Macao (online or onsite) is aimed at intermediate-level IT professionals who wish to learn how to leverage AWS tools and services to build, train, and deploy AI models efficiently.

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

• Understand the AI/ML services provided by AWS.
• Be able to set up and manage AI/ML environments on AWS.
• Gain hands-on experience in building, training, and deploying AI models using Amazon SageMaker.
• Learn to utilize various AWS AI services for specific use cases.

On demand AWS Architect Certification training course is designed to help professionals to become cloud-enabled using Amazon Web Services. This course is taught with real life examples, helps participants understand the practical application of concepts such as 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. After this course participants will be able to have their own implementations on cloud using EC2 instances, S3 buckets etc.

AWS is Amazon Web Services, a comprehensive cloud platform offering compute, storage, database, networking, analytics, and managed services that enable organizations to build scalable and cost-effective solutions.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level business and technical stakeholders who wish to understand core AWS services, cloud value propositions, cost models, security basics, and how to align AWS capabilities with organizational objectives.

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

• Explain core AWS services and common cloud architectures.
• Assess the business benefits and cost models of migrating workloads to AWS.
• Identify appropriate AWS services for common business problems (compute, storage, databases, networking, analytics).
• Recognize basic security, compliance, and governance considerations in the AWS cloud.
• Outline a simple migration or cloud adoption plan with high-level cost and risk considerations.

Format of the Course

• Interactive lecture and discussion.
• Instructor-led demonstrations in the AWS console.
• Group exercises and scenario-based workshops.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Macao (online or onsite) is aimed at beginner-level developers who wish to set up and use AWS Cloud9 for cloud-based projects.

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

• Understand the AWS Cloud9 environment and its components.
• Set up their own AWS Cloud9 development workspace.
• Develop and run simple applications within AWS Cloud9.
• Familiarize themselves with the collaboration features of AWS Cloud9.

This instructor-led, live training in Macao (online or onsite) is aimed at intermediate-level data scientists and analysts who wish to use AWS Cloud9 for streamlined data science workflows.

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

• Set up a data science environment in AWS Cloud9.
• Perform data analysis using Python, R, and Jupyter Notebook in Cloud9.
• Integrate AWS Cloud9 with AWS data services like S3, RDS, and Redshift.
• Utilize AWS Cloud9 for machine learning model development and deployment.
• Optimize cloud-based workflows for data analysis and processing.

This instructor-led, live training in Macao (onsite or remote) is aimed at engineers who wish to deploy and manage IoT devices on AWS.

By the end of this training, participants will be able to build an IoT platform that includes the deployment and management of a backend, gateway, and devices on top of AWS.

This instructor-led, live training in Macao (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 worry about provisioning the execution environment (servers, VMs and 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.
• Build, upload and execute AWS Lambda functions.
• Integrate Lambda functions with different event sources.
• Package, deploy, monitor and troubleshoot Lambda based applications.

This instructor-led, live training in Macao (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.

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.
• 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.

This instructor-led, live training in Macao (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.

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

• Set up and configure AWS Cloud9 for 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.
• Utilize source control systems like GitHub or GitLab within AWS Cloud9.

This instructor-led, live training in Macao (online or onsite) is aimed at 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 serverless application development.
• 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.

This instructor-led, live training in (online or onsite) is aimed at developers who wish to use the FARM (FastAPI, React, and MongoDB) stack to build dynamic, high-performance, and scalable web applications.

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

• Set up the necessary development environment that integrates FastAPI, React, and MongoDB.
• Understand the key concepts, features, and benefits of the FARM stack.
• Learn how to build REST APIs with FastAPI.
• Learn how to design interactive applications with React.
• Develop, test, and deploy applications (front end and back end) using the FARM stack.

This instructor-led, live training in Macao (online or onsite) is aimed at developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs easier and faster.

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

• Set up the necessary development environment to develop APIs with Python and FastAPI.
• Create APIs quicker and easier using the FastAPI library.
• Learn how to create data models and schemas based on Pydantic and OpenAPI.
• Connect APIs to a database using SQLAlchemy.
• Implement security and authentication in APIs using the FastAPI tools.
• Build container images and deploy web APIs to a cloud server.

Summary:

• Understanding IoT architecture and core functions.
• Exploring the concept of "Things" and "Sensors," the Internet of Things, and mapping business functions to IoT solutions.
• Comprehensive overview of IoT software components: hardware, firmware, middleware, cloud infrastructure, and mobile applications.
• Key IoT functions: Fleet management, data visualization, SaaS-based FM and DV, alerting/alarm systems, sensor and "thing" onboarding, and geo-fencing.
• Fundamentals of IoT device-to-cloud communication using MQTT.
• Connecting IoT devices to AWS via MQTT using AWS IoT Core.
• Integrating AWS IoT Core with AWS Lambda for computation and Amazon DynamoDB for data storage.
• Connecting a Raspberry Pi to AWS IoT Core for seamless data communication.
• Hands-on lab: Building a smart device using a Raspberry Pi and AWS IoT Core.
• Sensor data visualization and web interface communication.