AI on Amazon Web Services (AWS)のトレーニングコース

This instructor-led, live training in 日本 (online or onsite) is aimed at cloud engineers and developers who wish to use CloudFormation to manage infrastructure resources within the AWS ecosystem.

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

• Implement CloudFormation templates to automate infrastructure management.
• Integrate existing AWS resources into CloudFormation.
• Use StackSets to manage stacks across multiple accounts and regions.

This instructor-led, live training in 日本 (online or onsite) is aimed at developers who wish to integrate a DynamoDB NoSQL database into a web application hosted on AWS.

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

• Set up the necessary development environment to start integrating data into DynamoDB.
• Integrate DynamoDB into web applications and mobile applications.
• Move data in AWS with AWS services.
• Implement operations with AWS DAX.

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

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.

This instructor-led, live training in 日本 (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 日本 (online or onsite) is aimed at engineers who wish to use AWS CloudFormation to automate the process of managing AWS cloud infrastructure.

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

• Enable AWS services to get started managing infrastructure.
• Understand and apply the principle of "infrastructure as code".
• Improve quality and lower the costs of deploying infrastructure.
• Write AWS CloudFormation Templates using YAML.

This instructor-led, live training in 日本 (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 日本 (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 日本 (online or onsite) is aimed at beginner-level to intermediate-level researchers and laboratory professionals who wish to process and analyze images related to histological tissues, blood cells, algae, and other biological samples.

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

• Navigate the Fiji interface and utilize ImageJ’s core functions.
• Preprocess and enhance scientific images for better analysis.
• Analyze images quantitatively, including cell counting and area measurement.
• Automate repetitive tasks using macros and plugins.
• Customize workflows for specific image analysis needs in biological research.

This instructor-led, live training in 日本 (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to integrate AI functionalities into their applications using Google Gemini AI.

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

• Understand the fundamentals of large language models.
• Set up and use Google Gemini AI for various AI tasks.
• Implement text-to-text and image-to-text transformations.
• Build basic AI-driven applications.
• Explore advanced features and customization options in Google Gemini AI.

This instructor-led, live training in 日本 (online or onsite) is aimed at intermediate-level content creators who wish to utilize Google Gemini AI to enhance their content quality and efficiency.

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

• Understand the role of AI in content creation.
• Set up and use Google Gemini AI to generate and optimize content.
• Apply text-to-text transformations to produce creative and original content.
• Implement SEO strategies using AI-driven insights.
• Analyze content performance and adapt strategies using Gemini AI.

This instructor-led, live training in 日本 (online or onsite) is aimed at intermediate-level customer service professionals who wish to implement Google Gemini AI in their customer service operations.

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

• Understand the impact of AI on customer service.
• Set up Google Gemini AI to automate and personalize customer interactions.
• Utilize text-to-text and image-to-text transformations to improve service efficiency.
• Develop AI-driven strategies for real-time customer feedback analysis.
• Explore advanced features to create a seamless customer service experience.

This instructor-led, live training in 日本 (online or onsite) is aimed at beginner-level to intermediate-level data analysts and business professionals who wish to perform complex data analysis tasks more intuitively across various industries using Google Gemini AI.

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

• Understand the fundamentals of Google Gemini AI.
• Connect various data sources to Gemini AI.
• Explore data using natural language queries.
• Analyze data patterns and derive insights.
• Create compelling data visualizations.
• Communicate data-driven insights effectively.

Summery:

• Basics of IoT architecture and functions
• “Things”, “Sensors”, Internet and the mapping between business functions of IoT
• Essential of all IoT software components- hardware, firmware, middleware, cloud and mobile app
• IoT functions- Fleet manager, Data visualization, SaaS based FM and DV, alert/alarm, sensor onboarding, “thing” onboarding, geo-fencing
• Basics of IoT device communication with cloud with MQTT.
• Connecting IoT devices to AWS with MQTT (AWS IoT Core).
• Connecting AWS IoT core with AWS Lambda function for computation and data storage.
• Connecting Raspberry PI with AWS IoT core and simple data communication.
• Alerts and events
• Sensor calibration

Summary:

• Basics of IoT architecture and functions
• “Things”, “Sensors”, Internet and the mapping between business functions of IoT
• Essential of all IoT software components- hardware, firmware, middleware, cloud and mobile app
• IoT functions- Fleet manager, Data visualization, SaaS based FM and DV, alert/alarm, sensor onboarding, “thing” onboarding, geo-fencing
• Basics of IoT device communication with cloud with MQTT.
• Connecting IoT devices to AWS with MQTT (AWS IoT Core).
• Connecting AWS IoT core with AWS Lambda function for computation and data storage using DynamoDB.
• Connecting Raspberry PI with AWS IoT core and simple data communication.
• Hands on with Raspberry PI and AWS IoT Core to build a smart device.
• Sensor data visualization and communication with web interface.