Microsoft has introduced an in-depth generative AI course designed to help beginners, developers, and AI enthusiasts. This course is designed to build a strong foundation in artificial intelligence. The free 18-part video series explores everything from language models and prompt design to app development, ethical usage, and security.
Additionally, it seeks to make difficult ideas easier for those unfamiliar with AI. At the same time, it will offer tips for developing practical AI applications. Microsoft’s emphasis on accessible AI learning to empower people across industries is reflected in the initiative.
All You Need to Know About This Generative AI Course
The structured course progresses from basic concepts to advanced tools. Additionally, it offers practical skills and examples of use cases.
Foundations of Generative AI and Prompt Engineering
- Introduction to Generative AI and LLMs: The series begins by introducing generative AI and large language models. It explains how they are changing education in particular, among other fields. Thus, students learn about the state of AI and its increasing significance in day-to-day life.
- Comparing Different Language Models: This module focuses on major language models in the market. It examines their strengths, differences, and how they’re used across industries. Learners also learn how to assess models according to their business potential and performance.
- Responsible AI Practices: This session focuses on minimizing risk in AI outputs and the necessity of transparency. It guides users on adopting responsible strategies while building AI applications.
- Prompt Engineering Basics: Learners are introduced to prompt engineering, the technique of designing prompts to get better results. Furthermore, this basic understanding enhances the interactions of AI tools.
- Crafting Advanced Prompts: Building on the previous lesson, this part focuses on complex prompt structures. It describes how more intelligent and precise AI responses can be shaped by subtle prompts.
App Development Skills in the Generative AI Course
- Creating Text Generation Apps: This episode walks through building a text-generation tool using OpenAI. It experiments with parameters like temperature and token limits to optimize results.
- Building Chat-Based Interfaces: Users are taught to design chat interfaces using generative AI. It also contains advice on system monitoring, user experience, and behavior customization.
- Developing Search Applications: Semantic search is demystified through a practical case: building a video segment search engine. Furthermore, it employs vector embeddings to produce pertinent outcomes.
- Image Generation Apps: Learn how to create text-to-image apps using tools like DALL·E. The module describes user controls and integration for better visual content creation.
- Low-Code App Development: Low-code tools are changing how we build software. Additionally, this lesson teaches how to use Microsoft Power Platform and AI Builder to make apps with minimal code.
Advanced Concepts, Security, and AI Strategy
- Function Calling in LLMs: Function calling allows AI to interact with systems more effectively. Thus, learners acquire the skills to incorporate these calls into processes and enhance the dynamic nature of AI applications.
- Designing AI User Experience: User-centered design is the main focus of this module. It explains why trust-building and transparency are essential in AI-driven interface design.
- Securing Generative AI: Security risks in generative systems are covered. Common vulnerabilities and recommended practices for safeguarding user outputs and data are covered in the lesson.
- Understanding the AI Lifecycle: From development to deployment, this module details the full cycle of AI product creation. Furthermore, it provides metrics and monitoring tools that are essential for advancement.
- Retrieval Augmented Generation (RAG): RAG enhances model accuracy using external data sources. Learners explore creating vector databases and applying them in search-based solutions.
- Using Open-Source Models: This episode compares proprietary vs. open-source models. Additionally, it presents Hugging Face and other platforms for implementing affordable and customized solutions.
- Exploring AI Agents: AI agents automate tasks using goal-oriented logic. The different types of agents and when to use them in task-specific scenarios are covered in the lesson.
- Language Model Fine-Tuning: The final section of the series enables users to modify models to suit particular use cases. Also, it describes the technical restrictions as well as the advantages.
Empowering the Future of AI Education
This generative AI course gives beginners the tools they need to explore artificial intelligence through well-organized instruction and practical applications. Every lesson builds practical knowledge in simple terms, covering topics like protecting AI applications and prompt engineering. Therefore, this course is a great starting point for learning new technologies or building tools.
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