AWS Cloud9 and Python: A Practical Guide Training Course

This instructor-led, live training in Botswana (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 Botswana (online or onsite) is targeted at cloud engineers aiming to grasp and apply the more intricate components of AWS architecture. While the course addresses many topics similar to those found in the AWS Certified Solutions Architect (Professional) exams, it is explicitly NOT designed to prepare participants for the examination. Instead, this is a practical, hands-on course that demonstrates how to implement in a live lab environment various configurations, implementations, and deployments that an AWS Solutions Architect would typically perform.

Upon completion of this training, participants will be capable of:

• Designing complex cloud solutions on AWS.
• Deploying scalable, highly available, and fault-tolerant software applications on AWS.
• Integrating the most suitable AWS services with an application.
• Migrating complex software applications to AWS.
• Applying best practices for the design, implementation, optimization, and deployment of infrastructure and applications on AWS.

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

Upon completion of this training, participants will be equipped to:

• Comprehend the AI/ML services available within the AWS ecosystem.
• Set up and manage AI/ML environments on AWS.
• Acquire practical experience in constructing, training, and deploying AI models using Amazon SageMaker.
• Learn to apply various AWS AI services to address specific use cases.

This on-demand AWS Architect Certification training course is crafted to equip professionals with the skills needed to become cloud-enabled through Amazon Web Services. Delivered with real-world examples, the course enables participants to grasp the practical application of key concepts including cloud computing fundamentals, 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, participants will be capable of deploying their own cloud implementations using resources such as EC2 instances and S3 buckets.

AWS (Amazon Web Services) is a comprehensive cloud platform that provides compute, storage, database, networking, analytics, and managed services, empowering organisations to build scalable and cost-effective solutions.

This instructor-led live training (available online or onsite) is designed for beginner to intermediate business and technical stakeholders who wish to understand core AWS services, the value proposition of cloud computing, cost models, security fundamentals, and how to align AWS capabilities with organisational objectives.

Upon completion 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).
• Recognise 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 customized training for this course, please contact us to arrange.

This instructor-led, live training in Botswana (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 Botswana (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 Botswana (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 Botswana (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 Botswana (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 Botswana (online or onsite) is designed for advanced-level professionals seeking to deepen their understanding of DevOps practices and streamline development processes using AWS Cloud9.

By the conclusion of this training, participants will be capable of:

• Setting up and configuring AWS Cloud9 for DevOps workflows.
• Implementing continuous integration and continuous delivery (CI/CD) pipelines.
• Automating testing, monitoring, and deployment processes using AWS Cloud9.
• Integrating AWS services such as Lambda, EC2, and S3 into DevOps workflows.
• Utilising source control systems like GitHub or GitLab within AWS Cloud9.

This instructor-led, live training in Botswana (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.

Upon completion of this training, participants will be able to:

• Grasp the core principles of serverless architecture.
• Configure AWS Cloud9 for serverless application development.
• Develop, test, and deploy serverless applications leveraging AWS Lambda.
• Integrate AWS Lambda with other AWS services, such as API Gateway and S3.
• Optimize serverless applications for both performance and cost-efficiency.

This instructor-led live training, offered online or on-site, is designed for developers who wish to leverage the FARM (FastAPI, React, and MongoDB) stack to create 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 Botswana (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:

• Grasping the architecture and fundamental operations of IoT systems.
• Examining the notions of "Things" and "Sensors," the essence of the Internet of Things, and aligning business processes with IoT solutions.
• A thorough examination of IoT software layers: hardware, firmware, middleware, cloud infrastructure, and mobile applications.
• Core IoT capabilities: fleet management, data visualisation, SaaS-based facility management and data visualisation, alert and alarm systems, sensor and device onboarding, and geo-fencing.
• The basics of device-to-cloud communication via MQTT.
• Linking IoT devices to AWS through MQTT using AWS IoT Core.
• Integrating AWS IoT Core with AWS Lambda for processing and Amazon DynamoDB for data storage.
• Establishing a connection between a Raspberry Pi and AWS IoT Core for seamless data exchange.
• Practical lab session: Creating a smart device using a Raspberry Pi and AWS IoT Core.
• Visualising sensor data and managing web interface communication.