The Complete Guide To Google Gemini (With Gemini Ultra!)
Learn To Use Gemini Ultra, Gemini Pro, Gemini Vision, Google AI Studio, Vertex AI, and More. Develop with AI for FREE!
4.46 (1429 reviews)
7 934
students
8.5 hours
content
Feb 2024
last update
$89.99
regular price
What you will learn
Understand the Fundamentals of Google's Groundbreaking Gemini Models
Develop Expertise in Prompt Engineering
Master Google's Generative AI Studio to Build, Test, and Iterate on Complex Prompts
Utilize Gemini Vision Pro for Image and Video Related Tasks
Build AI-Powered Applications with the Gemini Python and Node JS SDKs
Explore and Utilize Google's Vertex AI Platform, an Enterprise Platform for AI at Scale
Master Gemini Model Parameters: Temperature, Top-K, Top-P, and More
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Our Verdict
The Complete Guide To Google Gemini offers valuable lessons on LLMs, Bard expertise, and prompt engineering. Despite room for improvement in depth and real-world applications, this course is worth exploring if you're eager to familiarize yourself with the cutting-edge Gemini technology. It empowers learners to harness the potential of AI, fostering creativity while offering a firm foundation in LLMs.
What We Liked
- The course provides a comprehensive introduction to Google Gemini and its variants, including Nano, Pro, and Ultra, which is crucial for understanding the landscape of Large Language Models (LLMs).
- Google Bard expertise is taught in-depth, enabling learners to harness the power of multimodal prompts and integrate AI with daily digital tools like email management, data visualization, and writing code.
- Prompt engineering skills are explained in a straightforward manner, helping learners craft complex prompts for image and video inputs using Gemini Vision Pro.
- Hands-on experience is offered through Google's Generative AI Studio, showing learners how to build, test, and iterate on prompts effectively, fine-tuning model parameters.
Potential Drawbacks
- The course lacks depth in some areas like enterprise-level AI development using Vertex AI, where registrations, authentication, and API usage could be explored further.
- Examples for industry use cases and real-world businesses would enrich the learning experience and enhance understanding of how to integrate AI into data flows within business processes.
- The course material, though updated, sometimes feels insufficient in comparison to promises made in the course description and could benefit from more examples and deep dives.
- Given the rapid advancements in AI technology, keeping the content up-to-date and consistently relevant is an area needing improvement.
5733220
udemy ID
28/12/2023
course created date
17/01/2024
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