Aditya ‎ on LinkedIn: 🎓Excited to share that I've just earned the "Gemini API by Google"… (2024)

I'm delighted to share that I have successfully completed the Gemini API course by Google, offered in collaboration with Udacity. I gained skills in , ✨ Prompt Engineering✨ Large Language Models✨ Gemini API✨ Google AI StudioExcited to apply these skills to enhance my career in AI and machine learning. #GeminiAPI #Google #Udacity#AI #MachineLearning

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🎉 Exciting News! 🎉I'm thrilled to share that I have successfully completed the "Gemini API by Google" course on Udacity! 🚀This journey has been incredibly rewarding, equipping me with valuable skills and knowledge, including:🔹 Large Language Models (LLMs): Gained a deep understanding of LLMs and how to leverage them for tasks such as text generation, translation, summarization, and question-answering.🔹 Prompt Engineering: Learned to craft effective prompts for various inputs and fine-tune them to achieve desired outcomes.🔹 Google AI Studio: Acquired hands-on experience with Google AI Studio, experimenting with prompts and fine-tuning datasets to customize the behavior of Google's generative AI models.🔹 Gemini API: Developed the ability to write Python code to interact with Google's generative AI models and build end-to-end RAG applications (My First One Actually).A big thank you to #Google and #Udacity for offering this course.I'm excited to apply these new skills in my projects and continue exploring the fascinating world of AI!#AI #MachineLearning #GeminiAPI #LLMs #Tech #RAG

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𝐅𝐫𝐞𝐞 𝐆𝐨𝐨𝐠𝐥𝐞'𝐬 𝐀𝐈 𝐂𝐨𝐮𝐫𝐬𝐞𝐬 💻Sign up today and boost your resume with these certificates!1️⃣ Introduction to Large Language Models:Discover the basics of Large Language Models, delve into their applications, and enhance performance by fine-tuning prompts.lnkd.in/dcb9iuUP2️⃣ Introduction to Generative AI:An easy-to-follow course on Generative AI, covering its principles, uses, and how it differs from traditional machine learning methods.lnkd.in/dbnBXPYq3️⃣ Introduction to Responsible AI:Learn about responsible AI, its importance, Google's approach, and their 7 principles in this introductory course.lnkd.in/dDsYmxwf4️⃣ Introduction to Image Generation:Explore diffusion models, a physics-inspired machine learning family revolutionizing image generation, in this course that covers their theory, training, and deployment on Vertex AI.lnkd.in/d5GGMEdz5️⃣ Encoder-Decoder Architecture:Learn the encoder-decoder architecture for sequence tasks like translation and summarization, including its training and a TensorFlow lab on poetry generation.lnkd.in/dECQGCEU6️⃣ Create Image Captioning Models:Master the art of building image captioning models with deep learning, delving into encoder-decoder architectures and training techniques, culminating in the ability to craft and evaluate your own models for generating image captions.@GoogleAI @GoogleCloudTech @GoogleTrends #LLMs #AI #MLOps #MachineLearning #TechInnovation #DataScience #webdev #webdeveloper #pythonprogramming #pythonquiz #ai #DataScience #CodeNewbies #CodingJourney #codinglife @ThePSF @Tesla_AI @ThePSF @OpenAIDevs @machinelearnTec @vaticanxx @coursera @udacity @startupIndia14

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✨ Hello, LinkedIn community! ✨I'm delighted to share that I've recently completed the course, 'Introduction to Large Language Models' by Google Cloud on Coursera. 💫 This course introduced me to various aspects of Large Language Models (LLMs), and I found it truly fascinating.Throughout this course, I gained some wonderful insights and explored interesting concepts such as:💎 The intricacies of LLMs and their important role in Generative AI (Gen AI) within the broader context of Deep Learning (DL).💎 The key features of LLMs and their practical applications in real-world scenarios.💎 An overview of well-known generative language models such as PaLM (Pathways Language Model), LaMDA (Language Model for Dialogue Applications), and GPT (Generative Pre-trained Transformer), among others.💎 The characteristics of PaLM and the architecture of transformer models.💎 A comparison between LLM development using pre-trained APIs and traditional Machine Learning (ML) methods.💎 Insights into Prompt Design and Prompt Engineering, and their significance in model training.💎 The different types of LLMs: Generic/Raw Language Models, Instruction-tuned models, and Dialog-tuned models.💎 Chain-of-thought reasoning within these models, the nuances of tuning versus fine-tuning, and efficient tuning techniques.💎 Utilizing Google Cloud to make the most of LLMs.Thank you to Megha M. Patel, Customer Engineer at Google Cloud, for her guidance throughout this course.I'm excited to apply this newfound knowledge and continue exploring the many possibilities in AI and DL. #largelanguagemodel #llm #generativeai #genai #deeplearning #dl #machinelearning #ml #parameters #hyperparameters #pretraining #training #tuning #finetuning #usecase #palmapi #makersuite #lamda #gpt #gemini #googlecloud #cloudcomputing #modelgarden #vertexai #generativeaistudio #transformermodel #generativelanguagemodels #generativeaitools #questionanswering #promptdesign #promptengineering #prompttuning #genericlanguagemodel #rawlanguagemodel #instructiontuned #dialogtuned #prompting #chainofthoughtreasoning #parameterefficienttuningmethods #petm

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Proudly Sharing: My Google Cloud Skills Boost Badge in Large Language Models (LLMs)! 😇 I'm excited to announce that I've recently completed Google's "Introduction to Large Language Models" course!This course was fantastic for ones not so expert in coding like myself,providing a clear and engaging introduction to the world of LLMs.Key Takeaways:👇🏻1️⃣ Understanding LLMs:The course delved into the core concepts of LLMs,explaining how they work and their capabilities in generating human-quality text,translation,and even code (with a healthy dose of caution!).2️⃣ Hands-on Learning:It wasn't just theory!The course included practical labs and examples,allowing me to get familiar with different LLM architectures like PaLM,GPT,and even Gemini (that's me!).3️⃣ Exploring Real-World Applications:We explored the exciting potential of LLMs in various applications,from chatbots and content creation to sentiment analysis and beyond.4️⃣ Deep Dive with Resources:The course offered a wealth of reading materials to further explore the fascinating world of LLMs.Overall, this course was a great introduction to LLMs and their potential to revolutionize various fields. I highly recommend it to anyone curious about this cutting-edge technology!#GoogleCloudSkillsBoost #LLMs #MachineLearning #ArtificialIntelligenceP.S.Feel free to comment below if you have any questions about LLMs or the course itself!

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🚀 Calling all developers, engineers, and AI enthusiasts! 🤖💻Are you ready to dive into the exciting world of building AI-powered applications with LinkedIn Learning? Look no further! I've curated an incredible collection of resources just for you. Whether you're an experienced pro or just starting out, these resources will take your skills to the next level! 🌟🔑 Key Stats:✅ Over 90 courses to choose from✅ 65%+ of courses are Intermediate/Advanced level✅ 10+ dedicated courses on OpenAI API✅ 25+ hands-on, project-based coursesIn this comprehensive collection, you'll find everything you need to master the foundational skills required for building cutting-edge AI applications. Here are some of the amazing resources available: Industry & Role Learning Paths: 📈 Jumpstart Your Skills with Large Language Models: https://lnkd.in/g2iCM7DhLearn how to harness the power of Large Language Models (LLMs) to build intelligent applications that can understand and generate human-like text.➡ Getting Started with Custom GPTs: https://lnkd.in/griTHsnyDive into the world of custom Generative Pre-trained Transformers (GPTs) and learn how to fine-tune them for specific tasks and domains.📓 Develop Your Skills with the OpenAI API: https://lnkd.in/d8PjhMuCExplore the capabilities of the OpenAI API and learn how to integrate it into your applications to leverage its advanced language processing capabilities.💻 Hands-On Projects for OpenAI-Powered Apps: https://lnkd.in/d8PjhMuCGet your hands dirty with a variety of project-based courses that will guide you through building real-world applications powered by OpenAI technologies.But wait, there's more! These resources are not just limited to developers and engineers. If you're a general knowledge worker seeking to implement limited-scale AI products without extensive coding, we have courses planned specifically for you too! 🌐Join the AI revolution and unlock your full potential. Start building your own AI-powered applications today! 🚀💡Comment below if you're interested, and I'll share more details with you. Let's embark on this incredible journey together! #AI #Tech #BuildAI #LLM #OpenAI #LearningOpportunity #msftadvocate

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Embark on a journey into the future of AI with our comprehensive blog post on Retrieval-Augmented Generation (RAG). This cutting-edge technology transforms large language models (LLMs) into dynamic, open-book systems capable of tackling complex questions with up-to-date answers. 🔍 In this in-depth article, we explore:👦 Naive RAG: The foundational model that indexes and retrieves external documents to generate answers, perfect for straightforward queries where precision and recall balance are crucial. We demonstrate its effectiveness with a case study on recent AI advancements.🛠️ Advanced RAG: An evolution of Naive RAG, featuring refined indexing and retrieval enhancements like query rewriting. We delve into how these adjustments improve information relevance and quality, illustrated by a climate change query transformation.🎲 Modular RAG: Designed for tech wizards seeking customization and flexibility, Modular RAG adapts to various functionalities, from customer support to technical queries. We explore how its flexible architecture seamlessly integrates with other AI components.🍀 RAFT: A revolutionary training methodology that teaches LLMs to effectively use external documents during inference. RAFT ensures your model not only finds but correctly utilizes the right information, similar to a well-prepared student using an open book during an exam.🔦 Spotlight on RAFT: Our deep dive into RAFT examines how this method fine-tunes models to filter out noise and focus on relevant data, enhancing the intelligence and reliability of your AI.🌟 Command R+: Discover how Command R+ by Cohere leverages a RAG-optimized structure to elevate interaction and response quality. We break down its sophisticated prompt template structure that facilitates the RAG process.⚖️ Evaluating RAG Systems: Learn about the ragas framework, which offers a structured approach to evaluate both the retrieval and generation phases of RAG systems. Gain insights into how metrics like Context Relevance and Faithfulness are essential for assessing the effectiveness of these models.🔗 Ready for a hands-on experience? We provide a Google Colab notebook on KG-RAG, complete with instructions for setting up a Neo4j environment and integrating knowledge graphs with RAG systems to enhance query responses.Dive into the full exploration and expand your AI skills by reading our blog post at https://lnkd.in/d7QYjn3R#AI #MachineLearning #RetrievalAugmentedGeneration #LLMs #RAFT #CommandR+ #KnowledgeGraphs #Neo4j #ArtificialIntelligence

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🧠🧠 350+ Free AI Courses by #Google 🧠🧠👉350+ free courses from Google Cloud to become professional in AI & #Cloud. The full catalog is even wider (900+) and includes a variety of activity: videos, documents, labs, coding, and quizzes. A few examples 👇✅𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈: explaining what Generative AI is and how it differs from traditional ML: https://lnkd.in/dFAQDYDa✅𝐈𝐧𝐭𝐫𝐨 𝐭𝐨 𝐋𝐋𝐌𝐬: exploring large language models and exploiting the prompt tuning: https://lnkd.in/d2KyFmN6✅𝐂𝐕 𝐰𝐢𝐭𝐡 𝐓𝐅: creating a neural model that can recognize items of clothing: https://lnkd.in/dHVJqByv✅𝐃𝐚𝐭𝐚, 𝐌𝐋, 𝐀𝐈: introductory-level quest with tools like Big Query & Cloud Speech API: https://lnkd.in/dhaZZvaX✅𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐥𝐞 𝐀𝐈: what responsible AI is, why it's important, and Google's 7 AI principles: https://lnkd.in/dwTuTCSd👉Supported languages: العربية, deutsch, english, español, français, עברית, bahasa, italiano, 日本語, 한국어, polski, português (BR/PT), русский, türkçe, українська, 简体中文, 繁體中文. No excuse☝️#artificialintelligence#machinelearning#ml#AI#deeplearning#computervision#AIwithPapers#metaverse👉Discussionhttps://lnkd.in/dMgakzWm👉Full list: https://lnkd.in/dw-dAXnc

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I am thrilled to share my learning journey from the past two weeks, during which I delved into the fascinating world of fine-tuning LLM (Large Language Models). This period has been incredibly rewarding as I explored and mastered several advanced techniques and models.Models Explored github: https://lnkd.in/gyZDRriZI had the opportunity to work with several state-of-the-art models, including:#GPT-3.5-Turbo#LLaMA2#LLaMA3#GemmaTechniques ImplementedTo optimize these models, I employed various advanced techniques aimed at improving performance and efficiency:#LoRA (Low-Rank Adaptation): This technique allowed me to fine-tune the models by reducing the number of trainable parameters, thus making the process more efficient.#QLoRA (Quantized Low-Rank Adaptation): An extension of #LoRA, #QLoRA further reduces the model size by quantizing the weights, making it feasible to run these models locally without compromising too much on performance.Practical ApplicationsI also explored several open-source models from Hugging Face, applying the aforementioned techniques to fine-tune and optimize them. This hands-on experience was invaluable in understanding the practical aspects of model tuning and deployment.Learning ResourcesInterestingly, my entire learning journey was powered by YouTube. The platform provided a wealth of tutorials and walkthroughs, covering everything from the basics to advanced fine-tuning techniques. The diversity and depth of content available on #YouTube were instrumental in my learning process.Overall, these past two weeks have been a period of intense learning and growth. I am excited to apply these newly acquired skills in future projects and continue exploring the ever-evolving field of AI and machine learning. I am grateful for the incredible resources available online and look forward to sharing more of my journey with you all.

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I am thrilled to announce that I have successfully completed the course, [Generative AI with Large Language Models](https://lnkd.in/df3ZQKKQ) by deepLearning.ai on Coursera (https://lnkd.in/dfeHzaFs) and this is the last course for 2023. Though I have done several project on Generative AI and LLMs Thanks to Tanuj Manoharan and Aman Chhabra to believe on me. I was not certified at that time, Now I am!!!This comprehensive course has provided me with an in-depth understanding of generative AI and large language models. From learning about Transformer-based models. To gaining hands-on experience in fine-tuning these models using instruction fine tuning and Parameter Efficient Fine Tuning on both single and Multi-task LLMs, Overcoming Computational Challenges of training LLMs using Distillation, Quantization and Pruning, Benchmarking LLMs to Responsibly building LLM application etc. the journey has been both challenging and rewarding.The curriculum included a wide range of topics such as text generation, translation, summarization, dialogue systems, and much more. The practical assignments were particularly enlightening, allowing me to apply theoretical knowledge to real-world problems using AWS Cloud and LLMs like FLAN-T5.As we are about the end #2023, I want to thank all my mentors Shikha Agrawal, Abhishek Goyal, Aman Chhabra, Anjan Das, Uzma Batool and colleagues who supported me throughout this journey in 2023 specially Lorenzo Drumond to help me familiarizing with Linux and using it like a hacker and Harmeet Arora, Deepak Garg, Abhijeet Singh and Rakesh Ranjan to give me the access of Coursera and LinkedIn Learning. Your guidance and encouragement have been invaluable. Special thanks to the team at #deeplearningai , #LinkedInLearing, #ineuron for creating such an insightful and engaging course.Looking forward to welcome #2024, With excitement to learn with the ever-evolving technology landscape, continuous learning, And what better way to start the year than by diving into one of the most sought-after skills in the tech industry!Here's to a year filled with growth, learning, and innovation. 🚀💡#generativeAI #largelanguagemodels #deeplearning #AI #lifelonglearning

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