Course Description
Develop higher-order skills in creating a Gemini-inspired multimodal AI system through this comprehensive guide. Apply foundational neural architecture concepts, analyze multimodal integration strategies, and evaluate efficient training methods. Guided by structured tutorials, synthesize your knowledge to design, implement, and assess advanced AI systems capable of reasoning across diverse modalities for real-world innovations.
Course curriculum
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1
Gemini: Google's AI That Reads , Sees, Hears and Understands
- Introduction
- Intro to Gemini models
- Function Calling with Gemini
- Why Gen-AI
- Are LLMs Really Intelligent
- LLMs at Google- A brief history
- Q&A Session
Certificate of Completion
Unlock a lifetime-valid certificate from Analytics Vidhya upon completing the course—your achievement is forever recognized!
Who should Enroll?
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Individuals looking to enhance their skills in building advanced AI systems and understanding multimodal capabilities.
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Professionals and students eager to explore state-of-the-art neural architectures and expand their expertise in multimodal AI applications.
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Software Engineers and Data Scientists who wish to apply practical knowledge of AI model creation and optimization to solve real-world problems.
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Anyone passionate about AI advancements, eager to learn practical techniques for creating state-of-the-art NLP solutions.
About the Instructor
Aditya Rane - AI Consultant at Google | Gen AI Specialist | Teacher
Aditya Rane is an accomplished AI professional with diverse experience spanning product development, consulting, software development, and IT support. He specializes in formulating and delivering high-impact solutions powered by artificial intelligence, leveraging his expertise to drive transformative outcomes. Aditya is deeply passionate about open-source software (OSS), reflecting his commitment to fostering innovation and collaboration within the tech community.
FAQs
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Q: What prior knowledge is required for this course?
A: A foundational understanding of Python and machine learning concepts is recommended. Familiarity with PyTorch and basic NLP techniques is a plus but not mandatory.
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Q: Will this course cover advanced AI topics like transformers and multimodal AI?
A: Yes, the course delves into transformers, decoder-only architectures, and multimodal AI, equipping you with the skills to build and optimize advanced AI systems.
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Q: Is this course hands-on or theoretical?
A: This course emphasizes a practical, hands-on approach with step-by-step implementation tutorials to help you build AI systems from scratch.
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Q: Is this course suitable for beginners?
A: Absolutely! The course is designed to provide practical skills for developing AI systems tailored to solving real-world problems across various domains.
Key Takeaways
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Understand transformer fundamentals with step-by-step guidance, including masked self-attention and position encoding.
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Build and train models using PyTorch, focusing on practical coding skills for NLP.
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Create a fully functional ChatGPT-style language model from scratch, ready for real-world use.