
Students will understand the course structure, objectives, and how NisusAI can benefit their business operations.
Students will grasp the fundamentals of Generative AI, its applications, and its importance in modern business environments.
Students will learn what an AI assistant is and the basic steps involved in creating one using NisusAI.
Students will understand key AI and machine learning terminologies critical for effective use of the NisusAI platform.
Students will learn about Vector DB and its role in managing and retrieving data efficiently within AI systems.
Students will grasp the concept of Semantic Search and how it enhances data search accuracy in AI-driven systems.
Students will understand RAG (Retrieval-Augmented Generation) and its operational mechanisms in AI applications.
Students will be introduced to the Document Splitting Module and understand its purpose in managing large documents.
Actions are tasks that NisusAI performs to complete specific jobs step by step. They help automate processes, saving you time and reducing manual effort. Actions ensure that every task is done in the correct order, improving efficiency and accuracy.
Actions are managed by the LLM, which organizes tasks in sequence. The system processes one action at a time or in parallel, ensuring smooth and efficient workflow execution.
Students will understand what prompts are and learn techniques to create effective prompts for AI assistants.
Students will become familiar with the Prompt Management Interface, enabling them to navigate and use it effectively.
Students will learn about the different model parameters and how to adjust them to optimize AI responses.
Students will learn best practices for interacting with LLMs through prompts to maximize their effectiveness.
Students will learn the process of saving prompts within the platform, ensuring they can reuse effective prompts later.
Students will understand how to test and refine prompts, enhancing their effectiveness in AI assistant interactions.
Students will understand the functioning of Large Language Models (LLMs) and their role in AI-driven tasks.
Students will gain the skills needed to build a functional AI assistant using NisusAI’s tools and features.
Students will learn the step-by-step process to deploy an AI assistant, making it operational for end-users.
Students will gain the ability to adjust and refine AI assistant deployments based on performance and user feedback.
Students will learn how to securely share their AI assistants with others using the NisusAI platform.
In this course, you will learn how to build your very own AI assistant by combining key concepts and techniques. Whether you're just starting out or looking to deepen your knowledge, this course will guide you step by step through the process of developing a functional and intelligent AI assistant.
We will begin by teaching you how to upload and structure documents so that the model can understand and use the information effectively. You’ll learn how to break down large amounts of data into manageable pieces that an AI model can process.
Next, we will cover prompt writing, which is essential for guiding the AI assistant in how to respond to user interactions. You'll learn how to craft effective prompts that instruct the model to behave like a helpful assistant.
We'll also dive into model selection—choosing the right model is crucial for building an assistant tailored to specific tasks. You’ll explore different models, understand their strengths, and see how to select the one that best suits your project.
Finally, we’ll focus on parameter tuning, where you’ll adjust the model’s settings to optimize its performance. You'll learn how to control creativity, accuracy, and response style to ensure the AI assistant works just the way you want.
By the end of the course, you will have all the knowledge and tools needed to build and refine a fully functional AI assistant that can assist users effectively in various tasks.