Learn
Learn the basics of AI (genetic algorithm)
Learn practical Excel function techniques
Learn practical VBA techniques
Learn shift optimization theory
Learn techniques to improve daily Excel work
Seminar Requirements
It works with Excel 2016 or later version for Windows.
Important notice: Please prepare a version that can use the Spill function.
The original is in Japanese, and the English version was created utilizing a machine translation.
There might be some mistranslations.
Since this is for advanced users, basic explanations are omitted.
Course Content
Features of this course
You will learn while enjoying the process of building little by little just like assembling a plastic model.
Usually get an expensive shift optimization app.
The source code, which is not available on the market, is also included, so it is worth several hundred thousand yen in real value.
Furthermore, you can freely customize it to your needs because it even comes with an explanation of the source code.
Will also learn the actual development process and VBA tips.
Will be able to apply it to various uses and develop useful applications.
For example, it can be used to calculate the shortest or cheapest itinerary, or to plan products that make effective use of materials.
Key Features
This is a very economical course that gives you the programming skills to make money and the apps to make money.
Curriculum Introduction
1. Seminar Introduction
2. Overview of Genetic Algorithms
3. Programming Guidelines
4. Design
5. Creation of shift table base
6. Generation of first shift
7. Generational evolution, evaluation, and performance analysis
Learn
Learn the basics of AI (genetic algorithm)
Learn practical Excel function techniques
Learn practical VBA techniques
Learn shift optimization theory
Learn techniques to improve daily Excel work
Seminar Requirements
It works with Excel 2016 or later version for Windows.
Important notice: Please prepare a version that can use the Spill function.
The original is in Japanese, and the English version was created utilizing a machine translation.
There might be some mistranslations.
Since this is for advanced users, basic explanations are omitted.
Course Content
Features of this course
You will learn while enjoying the process of building little by little just like assembling a plastic model.
Usually get an expensive shift optimization app.
The source code, which is not available on the market, is also included, so it is worth several hundred thousand yen in real value.
Furthermore, you can freely customize it to your needs because it even comes with an explanation of the source code.
Will also learn the actual development process and VBA tips.
Will be able to apply it to various uses and develop useful applications.
For example, it can be used to calculate the shortest or cheapest itinerary, or to plan products that make effective use of materials.
Key Features
This is a very economical course that gives you the programming skills to make money and the apps to make money.
Curriculum Introduction
1. Seminar Introduction
2. Overview of Genetic Algorithms
3. Programming Guidelines
4. Design
5. Creation of shift table base
6. Generation of first shift
7. Generational evolution, evaluation, and performance analysis
Lesson Title: Introduction to Socket IO
Objective: By the end of this lesson, students will understand the basics of Socket IO and its significance in real-time web applications.
Socket IO is an open-source, cross-platform library that provides full-duplex bidirectional communication between a client and a server based on events. It is built on the WebSocket protocol, providing additional capabilities such as automatic reconnection and fallback to HTTP long polling where WebSockets cannot be used.
Automatic reconnection
Under some particular conditions, the WebSocket connection between the server and the client can be interrupted with both sides being unaware of the broken state of the link.
That's why Socket IO includes a heartbeat mechanism, which periodically checks the status of the connection.
And when the client eventually gets disconnected, it automatically reconnects with an exponential back-off delay, in order not to overwhelm the server.
Packet buffering
The packets are automatically buffered when the client is disconnected, and will be sent upon reconnection.
More information
How it works
The bidirectional channel between the Socket IO server (Node js) and the Socket IO client (browser, Node js, or another programming language) is established with a WebSocket connection whenever possible, and will use HTTP long-polling as fallback.
Materials:
- A computer with Node.js installed
- Internet access
- Code editor (e.g., Visual Studio Code)
- Node js
- Javascript
Lesson Title: Introduction to Socket IO
Objective: By the end of this lesson, students will understand the basics of Socket IO and its significance in real-time web applications.
Socket IO is an open-source, cross-platform library that provides full-duplex bidirectional communication between a client and a server based on events. It is built on the WebSocket protocol, providing additional capabilities such as automatic reconnection and fallback to HTTP long polling where WebSockets cannot be used.
Automatic reconnection
Under some particular conditions, the WebSocket connection between the server and the client can be interrupted with both sides being unaware of the broken state of the link.
That's why Socket IO includes a heartbeat mechanism, which periodically checks the status of the connection.
And when the client eventually gets disconnected, it automatically reconnects with an exponential back-off delay, in order not to overwhelm the server.
Packet buffering
The packets are automatically buffered when the client is disconnected, and will be sent upon reconnection.
More information
How it works
The bidirectional channel between the Socket IO server (Node js) and the Socket IO client (browser, Node js, or another programming language) is established with a WebSocket connection whenever possible, and will use HTTP long-polling as fallback.
Materials:
- A computer with Node.js installed
- Internet access
- Code editor (e.g., Visual Studio Code)
- Node js
- Javascript
Welcome to the Fundamentals of Prompt Engineering for ChatGPT course!
Course Overview
Are you eager to harness the full potential of ChatGPT and optimize its responses? Look no further! In this comprehensive course, you'll dive deep into prompt engineering and gain the essential skills to leverage ChatGPT effectively. Through a combination of theoretical knowledge, practical examples, and hands-on exercises, you'll become a master at crafting prompts that elicit accurate and relevant answers.
Module 1: Understanding ChatGPT
In this module, you'll get acquainted with ChatGPT and its capabilities. We'll explore the GPT-3.5 architecture, uncovering the secrets behind its training process. Additionally, we'll discuss the limitations and challenges that arise when using ChatGPT, enabling you to navigate them effectively.
Module 2: Fundamentals of Prompt Engineering
Prompt engineering is the key to unlocking ChatGPT's potential. In this module, you'll learn the core concepts of prompt engineering and its role in optimizing responses. We'll delve into the components of a good prompt, including context, instruction, and question framing. Moreover, we'll explore strategies for formulating effective prompts that elicit accurate and informative answers.
Module 3: Defining the Context
Context is crucial in guiding ChatGPT's understanding and generating relevant responses. In this module, we'll explore techniques for setting up context effectively. You'll learn how to provide background information, reference previous statements, and structure prompts to harness the power of context-driven conversations.
Module 4: Crafting Clear Instructions
To ensure ChatGPT's responses align with your desired outcomes, precise and explicit instructions are vital. In this module, we'll discuss techniques for writing unambiguous instructions that guide ChatGPT's behavior effectively. Through examples and practical exercises, you'll learn how to specify desired outputs and achieve optimal results.
Module 5: Framing Effective Questions
Asking the right questions is an art that can significantly impact the quality of ChatGPT's answers. In this module, we'll explore strategies for framing questions that elicit specific and targeted responses. Through real-life examples and use cases, you'll sharpen your question-framing skills and enhance your ability to extract valuable information from ChatGPT.
Module 6: Experimenting with Formatting
Formatting plays a vital role in prompt engineering. In this module, we'll delve into techniques such as adding system messages, incorporating user messages, and controlling output length. You'll discover how formatting can improve user interactions and make the most of ChatGPT's capabilities.
Module 7: Iterative Improvement and Fine-tuning
Prompt engineering is an iterative process that requires continuous refinement. In this module, you'll learn how to incorporate user feedback and experiment with different prompts to achieve better results. Additionally, we'll discuss the concept of fine-tuning ChatGPT for specific tasks or domains, enabling you to tailor its responses to your specific needs.
Enroll now in the Fundamentals of Prompt Engineering for ChatGPT course and unlock the true potential of ChatGPT through effective prompt engineering. Start your journey today!
Welcome to the Fundamentals of Prompt Engineering for ChatGPT course!
Course Overview
Are you eager to harness the full potential of ChatGPT and optimize its responses? Look no further! In this comprehensive course, you'll dive deep into prompt engineering and gain the essential skills to leverage ChatGPT effectively. Through a combination of theoretical knowledge, practical examples, and hands-on exercises, you'll become a master at crafting prompts that elicit accurate and relevant answers.
Module 1: Understanding ChatGPT
In this module, you'll get acquainted with ChatGPT and its capabilities. We'll explore the GPT-3.5 architecture, uncovering the secrets behind its training process. Additionally, we'll discuss the limitations and challenges that arise when using ChatGPT, enabling you to navigate them effectively.
Module 2: Fundamentals of Prompt Engineering
Prompt engineering is the key to unlocking ChatGPT's potential. In this module, you'll learn the core concepts of prompt engineering and its role in optimizing responses. We'll delve into the components of a good prompt, including context, instruction, and question framing. Moreover, we'll explore strategies for formulating effective prompts that elicit accurate and informative answers.
Module 3: Defining the Context
Context is crucial in guiding ChatGPT's understanding and generating relevant responses. In this module, we'll explore techniques for setting up context effectively. You'll learn how to provide background information, reference previous statements, and structure prompts to harness the power of context-driven conversations.
Module 4: Crafting Clear Instructions
To ensure ChatGPT's responses align with your desired outcomes, precise and explicit instructions are vital. In this module, we'll discuss techniques for writing unambiguous instructions that guide ChatGPT's behavior effectively. Through examples and practical exercises, you'll learn how to specify desired outputs and achieve optimal results.
Module 5: Framing Effective Questions
Asking the right questions is an art that can significantly impact the quality of ChatGPT's answers. In this module, we'll explore strategies for framing questions that elicit specific and targeted responses. Through real-life examples and use cases, you'll sharpen your question-framing skills and enhance your ability to extract valuable information from ChatGPT.
Module 6: Experimenting with Formatting
Formatting plays a vital role in prompt engineering. In this module, we'll delve into techniques such as adding system messages, incorporating user messages, and controlling output length. You'll discover how formatting can improve user interactions and make the most of ChatGPT's capabilities.
Module 7: Iterative Improvement and Fine-tuning
Prompt engineering is an iterative process that requires continuous refinement. In this module, you'll learn how to incorporate user feedback and experiment with different prompts to achieve better results. Additionally, we'll discuss the concept of fine-tuning ChatGPT for specific tasks or domains, enabling you to tailor its responses to your specific needs.
Enroll now in the Fundamentals of Prompt Engineering for ChatGPT course and unlock the true potential of ChatGPT through effective prompt engineering. Start your journey today!
Embark on a transformative learning journey with the "Amazon Bedrock Masterclass: A Guide to Generative AI on AWS." This comprehensive course is meticulously designed to equip you with the knowledge, skills, and practical expertise necessary to excel in the rapidly evolving domain of Generative Artificial Intelligence (AI) using Amazon's robust Bedrock platform.
The course commences with a robust introduction to Amazon Bedrock, providing a solid foundation to understand the platform's capabilities and offerings. As a fully managed service on AWS, Amazon Bedrock simplifies the development of generative AI applications by providing access to high-performing foundation models from leading AI companies. This initial module sets the stage for the subsequent exploration and deep-dive into the myriad features that Amazon Bedrock offers, thus enabling a nuanced understanding and effective utilization of the platform. As you progress through the course, you'll delve into the technical intricacies of working with the Amazon Bedrock API, a critical skill for leveraging the platform's capabilities to the fullest. Your learning journey will then advance to exploring the advanced features of Amazon Bedrock, thus preparing you to handle complex generative AI projects.
The course then transitions to a practical approach, focusing on building generative AI applications with Bedrock. This module is designed to transition theoretical knowledge into practical expertise, enabling you to conceptualize, develop, and deploy generative AI applications effectively. Afterwards, the course underscores the importance of adhering to best practices while also providing a thorough understanding of the pricing model of Amazon Bedrock, thereby enabling informed and cost-effective decision-making.
The culmination of this masterclass is the Capstone Project, where you'll apply the amassed knowledge and skills in a real-world project, showcasing your competency in utilizing Amazon Bedrock for generative AI applications. This hands-on project is an opportunity to integrate and apply the learning from each module in a practical scenario, thus solidifying your understanding and readiness to tackle real-world generative AI challenges using Amazon Bedrock.
The "Amazon Bedrock Masterclass: A Guide to Generative AI on AWS" is more than just a course; it's a pathway to mastering generative AI on one of the most sophisticated platforms. The structured modules, practical insights, and the capstone project collectively ensure a rich, engaging, and rewarding learning experience, propelling you towards becoming a proficient practitioner of generative AI on AWS.
Embark on a transformative learning journey with the "Amazon Bedrock Masterclass: A Guide to Generative AI on AWS." This comprehensive course is meticulously designed to equip you with the knowledge, skills, and practical expertise necessary to excel in the rapidly evolving domain of Generative Artificial Intelligence (AI) using Amazon's robust Bedrock platform.
The course commences with a robust introduction to Amazon Bedrock, providing a solid foundation to understand the platform's capabilities and offerings. As a fully managed service on AWS, Amazon Bedrock simplifies the development of generative AI applications by providing access to high-performing foundation models from leading AI companies. This initial module sets the stage for the subsequent exploration and deep-dive into the myriad features that Amazon Bedrock offers, thus enabling a nuanced understanding and effective utilization of the platform. As you progress through the course, you'll delve into the technical intricacies of working with the Amazon Bedrock API, a critical skill for leveraging the platform's capabilities to the fullest. Your learning journey will then advance to exploring the advanced features of Amazon Bedrock, thus preparing you to handle complex generative AI projects.
The course then transitions to a practical approach, focusing on building generative AI applications with Bedrock. This module is designed to transition theoretical knowledge into practical expertise, enabling you to conceptualize, develop, and deploy generative AI applications effectively. Afterwards, the course underscores the importance of adhering to best practices while also providing a thorough understanding of the pricing model of Amazon Bedrock, thereby enabling informed and cost-effective decision-making.
The culmination of this masterclass is the Capstone Project, where you'll apply the amassed knowledge and skills in a real-world project, showcasing your competency in utilizing Amazon Bedrock for generative AI applications. This hands-on project is an opportunity to integrate and apply the learning from each module in a practical scenario, thus solidifying your understanding and readiness to tackle real-world generative AI challenges using Amazon Bedrock.
The "Amazon Bedrock Masterclass: A Guide to Generative AI on AWS" is more than just a course; it's a pathway to mastering generative AI on one of the most sophisticated platforms. The structured modules, practical insights, and the capstone project collectively ensure a rich, engaging, and rewarding learning experience, propelling you towards becoming a proficient practitioner of generative AI on AWS.
This comprehensive training course will equip participants with the knowledge and skills to leverage machine learning (ML) and artificial intelligence (AI) for security applications. The course begins with an introduction to the principles and fundamentals of ML and AI for security, providing a solid foundation for understanding the subsequent topics.
Participants will then delve into the intricacies of training models for AI security, exploring the techniques and methodologies involved in developing robust and secure AI systems. The course will also cover the usage of ChatGPT, a powerful AI language model, for security applications. Participants will learn to utilize ChatGPT to enhance security measures, detect anomalies, and respond to threats.
Furthermore, the course will introduce participants to GPT4all, the successor to ChatGPT, and its advanced features. Participants will learn how to leverage GPT4all plugins to enhance search capabilities and gather valuable insights from vast amounts of data.
Securing AI models and data will be a vital course focus, as participants will gain insights into best practices for protecting sensitive information and ensuring the integrity of AI systems. Additionally, participants will learn how to evaluate and monitor AI security systems to identify vulnerabilities and mitigate risks.
Real-world case studies will be examined to provide practical examples of AI security applications. The course will conclude with a discussion on future trends and challenges in AI security, enabling participants to stay ahead of the evolving landscape.
This comprehensive training course will equip participants with the knowledge and skills to leverage machine learning (ML) and artificial intelligence (AI) for security applications. The course begins with an introduction to the principles and fundamentals of ML and AI for security, providing a solid foundation for understanding the subsequent topics.
Participants will then delve into the intricacies of training models for AI security, exploring the techniques and methodologies involved in developing robust and secure AI systems. The course will also cover the usage of ChatGPT, a powerful AI language model, for security applications. Participants will learn to utilize ChatGPT to enhance security measures, detect anomalies, and respond to threats.
Furthermore, the course will introduce participants to GPT4all, the successor to ChatGPT, and its advanced features. Participants will learn how to leverage GPT4all plugins to enhance search capabilities and gather valuable insights from vast amounts of data.
Securing AI models and data will be a vital course focus, as participants will gain insights into best practices for protecting sensitive information and ensuring the integrity of AI systems. Additionally, participants will learn how to evaluate and monitor AI security systems to identify vulnerabilities and mitigate risks.
Real-world case studies will be examined to provide practical examples of AI security applications. The course will conclude with a discussion on future trends and challenges in AI security, enabling participants to stay ahead of the evolving landscape.