Beginning Generative AI in 2025
Details For Beginning Generative AI in 2025:
In 18 episodes, Microsoft’s extensive and free course “Generative AI for Beginners” covers the fundamentals of generative artificial intelligence from an introductory to an expert level.
AI enthusiasts, developers, students, and professionals in the technology sector are the target audience for this course, which includes educational videos, hands-on activities, Python and TypeScript coding examples, and more resources.
More Details:
- Degree level: No Degree Is Necessary
- Offered by: Microsoft Company
- Topic: Microsoft’s AI Education
- Cost: Free
- Deadline: Not Specified
- Location: Online
Section 1: Overview of Large Language Models (LLMs) and Generative Artificial Intelligence:
- familiarity with the fundamental ideas of generative AI, the operation of big language models, and the range of sectors in which they are used.
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Section 2: Analysis and Contrast of Various Language Models:
Comparing several huge language models, their uses, and how to pick the best model for a given situation.
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Section 3: Appropriate Application of Generative AI
investigation of moral standards, responsibility, and preventative measures for the application of generative AI.
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Section 4: Comprehending the Fundamentals of Prompt Engineering
knowledge of prompt engineering’s principles, elements, and methods for improving commands to get better results from AI models.
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Section 5: Formulating Complex Prompts:
gaining knowledge of sophisticated rapid engineering strategies to raise the caliber and precision of language model responses.
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Section 6: Developing Applications for Text Generation:
instruction on how to use the OpenAI library and associated ideas like prompts, temperature, and tokens to develop text generating apps.
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Part 7: Building Chat Applications:
Guidance on creating and integrating AI-based chat applications, along with important tips for their design and implementation.
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Section 8: Developing Search Applications for Vector Databases:
- An introduction to the idea of embeddings, the construction of a vector database, and the application of semantic search.
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Section 9: Developing Applications for Image Generation:
- instruction in the creation of picture generation programs and the use of models like DALL-E and Midjourney.
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Section 10: Developing Low-Code AI Applications:
- An introduction to artificial intelligence and low-code development platforms.
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Section 11: Combining Function Calls with External Applications:
- familiarity with the idea of function calls, their uses, and how to incorporate them into Azure OpenAI applications.
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Section 12: AI-Powered UX Design:
- An analysis of how to build transparency and trust in AI systems by applying user experience (UX) design concepts.
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Section 13: Protecting Applications of Artificial Intelligence:
- recognizing vulnerabilities and dangers related to AI systems and devising security measures for them.
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Section 14: Applications of Generative Artificial Intelligence Lifecycle:
analyzing the generative AI application lifetime and how to upgrade and manage it to stay up to date with new developments in technology.
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Section 15: Database Querying and Retrieval-Augmented Generation (RAG):
- familiarity with the RAG idea, its uses, and how to incorporate it into programs that query databases.
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Section 16: Hugging Faces and Open Source Models:
- An introduction to open-source language models, including their benefits and applications on Hugging Face and Azure AI Studio.
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Section 17: Agents with Artificial Intelligence:
- knowledge of artificial intelligence agents, their different frameworks, and the range of uses they have in AI applications.
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Section 18: Optimizing Big Language Models:
- Gaining knowledge of language model fine-tuning, including its advantages, difficulties, and application to enhance model performance.
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