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Deepanshu Chhikara

Member since 2025

Silver League

1832 points
Gen AI: Beyond the Chatbot Earned نوفمبر 28, 2025 EST
[DEPRECATED] Google Cloud: Prompt Engineering Guide Earned نوفمبر 28, 2025 EST
Vector Search and Embeddings Earned نوفمبر 28, 2025 EST
Machine Learning Operations (MLOps) for Generative AI Earned نوفمبر 27, 2025 EST
Attention Mechanism Earned نوفمبر 26, 2025 EST
Encoder-Decoder Architecture Earned نوفمبر 26, 2025 EST
[DEPRECATED]Introduction to Responsible AI Earned نوفمبر 26, 2025 EST
Introduction to Large Language Models Earned نوفمبر 26, 2025 EST
Introduction to Generative AI Earned نوفمبر 19, 2025 EST

Gen AI: Beyond the Chatbot is the first course of the Gen AI Leader learning path and has no prerequisites. This course aims to move beyond the basic understanding of chatbots to explore the true potential of generative AI for your organization. You explore concepts like foundation models and prompt engineering, which are crucial for leveraging the power of gen AI. The course also guides you through important considerations you should make when developing a successful gen AI strategy for your organization.

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Google Cloud : Prompt Engineering Guide examines generative AI tools, how they work. We'll explore how to combine Google Cloud knowledge with prompt engineering to improve Gemini responses.

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Explore AI-powered search technologies, tools, and applications in this course. Learn semantic search utilizing vector embeddings, hybrid search combining semantic and keyword approaches, and retrieval-augmented generation (RAG) minimizing AI hallucinations as a grounded AI agent. Gain practical experience with Vertex AI Vector Search to build your intelligent search engine. Explore other content in the Gemini Agent Ready (GEAR) program.

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This course is dedicated to equipping you with the knowledge and tools needed to uncover the unique challenges faced by MLOps teams when deploying and managing Generative AI models, and exploring how Gemini Enterprise Agent Platform empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.

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This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. You will learn how attention works, and how it can be used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering. This course is estimated to take approximately 45 minutes to complete.

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This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. You learn about the main components of the encoder-decoder architecture and how to train and serve these models. In the corresponding lab walkthrough, you’ll code in TensorFlow a simple implementation of the encoder-decoder architecture for poetry generation from the beginning.

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This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 3 AI principles.

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This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps. Explore other content in the Gemini Agent Ready (GEAR) program.

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This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.

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