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Dive into the revolutionary world of Large Language Models (LLMs) with our comprehensive 4-hour workshop, designed to bridge the gap between theoretical knowledge and practical skills. Whether you're a budding data scientist, an AI enthusiast, or a seasoned professional looking to expand your toolkit, this course is tailored to empower you with hands-on experience in leveraging LLMs for a variety of real-world applications. What You'll Learn: - Fundamentals and Advanced Techniques: Start with the basics of Large Language Models, including their architecture and capabilities, before progressing to advanced optimization methods such as Quantization and LoRA. - Practical Exercises: Engage in structured exercises using Kaggle datasets in Colab, fine-tuning models for tasks like question answering and text summarization with QLoRA, and exploring cutting-edge concepts such as Retrieval Augmented Generation (RAG). - Real-World Applications: Tackle engaging projects like building a semantic search engine to find movies and developing a chat interface with scholarly articles, applying your knowledge in tangible, impactful ways. - Model Publication: As a bonus, learn how to share your fine-tuned models with the world through Huggingface, enhancing your visibility in the AI community. Intended Learners: This course is perfect for individuals looking to deepen their understanding of LLMs and apply these models in innovative ways. Ideal for AI professionals, data scientists, and researchers eager to expand their skills and apply LLMs to solve complex problems.

Unlock the Hidden Potential of Large Language Models with this Google Cloud Course! Step into the transformative realm of language models and learn how to harness their expansive potential with Google Cloud and Python. This in-depth Udemy course offers a perfect fusion of theoretical insights and practical skills. About the Course: The course kicks off with a solid foundation in Large Language Models, helping students understand their complexity and functioning. As you delve into the main modules, you will become proficient in using the Google Cloud platform, effortlessly navigating the Generative AI Studio, comprehending its pricing, and selecting the best model for your needs. The course also delves into effective methods for Zero, One, and Few Shot Prompting, offering a comprehensive learning journey. We then explore the nuances of the Vertex AI Python LLM API, shedding light on parameters essential for fine-tuning models to peak performance. You'll learn about everything from token limits to temperature settings and sophisticated stop sequences in great detail. A highlight of this course is the practical labs, where students can create various tools, such as an advanced Customer Service Chatbot and a state-of-the-art Translation and Summarization AI Bot. These labs go beyond coding, applying theoretical knowledge to tangible, real-world applications. The course also ventures into the captivating area of prompt engineering. Students will learn to craft effective prompts for tasks like summarization and extraction. In addition, you'll explore text embeddings, learning about context injection in prompts and boosting model accuracy with similarity searches! By the end of the course, students will have the skills to customize their models in the Google Cloud Console, tailoring them to their specific objectives. Who Should Enroll? This course is ideal for AI enthusiasts looking to broaden their knowledge, developers who want to integrate advanced language models into their projects seamlessly, and anyone fascinated by the wonders of Google Cloud and Python in AI. Your Future Is Here! Begin a journey that combines deep theoretical knowledge with practical expertise. With its expert-led instruction and structured modules, this course is a guiding light for those passionate about the wonders of language models. Decide today and shape your future.

ChatGPT and Generative AI has disrupted the world, and is here to remain. Now you have the choice of adopting and mastering it, or falling behind. This course will help you become a prompt wizard, and use ChatGPT, Gemini (previously Bard), and other Large Language Models to 20X your productivity, boost your career, elevate your creativity and so much more. Unlike many other courses out there, this course is crafted by an AI and LLM expert, and focuses on building your intuition about Large Language Models, and providing you the right tools to use Large Language Models like ChatGPT, GPT 4 and Gemini to achieve your goals in a fast moving industry. The objective is not to give you a fish (prompt) and only feed you for a day, but it is to show you how to fish (prompt / work with LLMs) to feed you for a lifetime! We cover the following topics - Intuition about Large Language Models like ChatGPT and Gemini: how these models work, how they are built, and how to understand their functioning for existing and future LLMs - this will allow you to work with any model out there or to come! - Practical usage of ChatGPT and Gemini: learn the functionalities of ChatGPT and Gemini, the differences between them, when to use which, and how to quickly master these powerful tools - Fundamentals of Prompt Engineering: learn the basic toolbox to use prompts to control and supercharge the power of ChatGPT and other LLMs - Prompt patterns to help you achieve more faster: learn the most important prompt patterns to help you achieve your objectives, whether it is summarizing text, generating an essay, building a blogpost, writing an ebook, building a course, crafting a newsletter, building a sales funnel and more - Access ChatGPT everywhere: the best Chrome extensions to access the power of ChatGPT, ChatGPT, and Gemini on all web pages and across your different needs (e.g. twitter replies, email replies, essay writing, web page summarization) - Augment ChatGPT to get more value: what plugins are, how they work, when to use them, and how to use them (e.g. to allow ChatGPT to browse the internet, use links, do arithmetics, plan trips) December 2023 Update: Advanced Prompt Engineering: learn advanced techniques to achieve more with LLMs (ChatGPT, Gemini..) including unlocking new interactions with your LLM, automation, advanced reasoning and problem solving, Techniques to deal with long tasks: such as summarizing very long text, writing a blogpost, or generating a book Open AI APIs & Playground: including building chatbots, and the new assistant functionalities of retrieval and function calling - all with detailed walkthroughs and examples to quickly get you started! Are you ready to embrace the new tech & productivity revolution? Now is your time to get ahead of the crowd! See you on the other side!

In this course, we will explore some techniques and methods that can help you improve the performance of your LLM model beyond traditional fine tuning methods. You should purchase this course if you are a business leader or a developer who is interested in fine tuning your LLM model. These techniques and methods can help you overcome some of the limitations and challenges of fine tuning by enhancing the quality and quantity of your data, reducing the mismatch and inconsistency of your data, reducing the complexity and size of your LLM model, and improving the efficiency and speed of your LLM model. The main topics that we will cover in this course are: - Section 1: How to use data augmentation techniques to increase the quantity and diversity of your data for fine tuning your LLM model - Section 2: How to use domain adaptation techniques to reduce the mismatch and inconsistency of your data for fine tuning your LLM model - Section 3: How to use model pruning techniques to reduce the complexity and size of your LLM model after fine tuning it - Section 4: How to use model distillation techniques to improve the efficiency and speed of your LLM model after fine tuning it By the end of this course, you will be able to: - Explain the importance and benefits of improving the performance of your LLM model beyond traditional fine tuning methods - Identify and apply the data augmentation techniques that can increase the quantity and diversity of your data for fine tuning your LLM model - Identify and apply the domain adaptation techniques that can reduce the mismatch and inconsistency of your data for fine tuning your LLM model - Identify and apply the model pruning techniques that can reduce the complexity and size of your LLM model after fine tuning it - Identify and apply the model distillation techniques that can improve the efficiency and speed of your LLM model after fine tuning it This course is designed for anyone who is interested in learning how to improve the performance of their LLM models beyond traditional fine tuning methods. You should have some basic knowledge of natural language processing, deep learning, and Python programming. I hope you are excited to join me in this course.

Haystack is an end-to-end framework that accompanies you in every step of the GenAI project life cycle. Whether you want to perform document search, retrieval-augmented generation (RAG), question answering, or answer generation, Haystack can orchestrate state-of-the-art embedding models and LLMs into pipelines to build end-to-end NLP applications and solve your use case. This beginner to advanced all-encompassing course aims to swiftly show you how to leverage the Haystack 2.0 library for LLM applications. You will acquire the expertise and insights required to create state-of-the-art LLM solutions across a wide array of subjects. What you'll learn: - Haystack Foundations : Understand fundamentals of Haystack2.0 by learning Haystack components. Haystack theory with applications - Real-World Applications : Implement Haystack components with real world applications - Prompt Engineering : Learn prompt engineering techniques - Zero Shot, Few Shot and Chain of Thought - RAG Pipeline : Learn about RAG, Vector store - Haystack 2.0 Concepts : Pipelines, Components, Document Store, Retrievers - Haystack 2.0 Advance Topics : Ranker, Hybrid Retriever, Advanced Filtering, Self Correcting Loops - During the course, you will engage in practical exercises and real-world projects to solidify your grasp of the concepts and methods discussed. By the course's - conclusion, you will be skilled in utilizing Haystack to develop robust, efficient, and adaptable LLM applications for a broad range of uses. Who Should Enroll: AI developers, data scientists, business leaders looking to acquire skills in building generative AI-based applications with Haystack

Dive into the cutting-edge world of Direct Preference Optimization (DPO) and Large Language Model Alignment with this comprehensive course designed to equip you with the skills to leverage the LLaMA3 8-billion parameter model and Hugging Face's Transformer Reinforcement Learning (TRL). Using the powerful Google Colab platform, you will get hands-on experience with real-world applications, starting with the Intel Orca DPO dataset and incorporating advanced techniques like Low-Rank Adaptation (LoRA). Throughout this course, you will: - Learn to set up and utilize the LLaMA3 model within Google Colab, ensuring a smooth and efficient workflow. - Explore the capabilities of Hugging Face’s TRL framework to conduct sophisticated DPO tasks, enhancing your understanding of how language models can be fine-tuned to optimize for specific user preferences. - Implement Low-Rank Adaptation (LoRA) to modify pre-trained models efficiently, allowing for quick adaptations without the need to retrain the entire model, a crucial skill for real-world applications. - Train on the Intel Orca DPO dataset to understand the intricacies of preference data and how to manipulate models to align with these insights. - Extend your learning by applying these techniques to your own datasets. This flexibility allows you to explore various sectors and data types, making your expertise applicable across multiple industries. - Master state-of-the-art techniques that prepare you for advancements in AI and machine learning, ensuring you stay ahead in the field. This course is perfect for data scientists, AI researchers, and anyone keen on harnessing the power of large language models for preference-based machine learning tasks. Whether you're looking to improve product recommendations, customize user experiences, or drive decision-making processes, the skills you acquire here will be invaluable. Join us to transform your theoretical knowledge into practical expertise and lead the way in implementing next-generation AI solutions!

In this comprehensive course on Vector Databases, you will delve into the exciting world of cutting-edge technologies that are transforming the field of artificial intelligence (AI), particularly in generative AI. With a focus on Future-Proofing Generative AI, this course will equip you with the knowledge and skills to harness the power of Vector Databases for advanced applications, including Language Model Models (LLM), Generative Pretrained Transformers (GPT) like ChatGPT, and Artificial General Intelligence (AGI) development. Starting from the foundations, you will learn the fundamentals of Vector Databases and their role in revolutionizing AI workflows. Through practical examples and hands-on coding exercises, you will explore techniques such as vector data indexing, storage, retrieval, and conditionality reduction. You will also gain proficiency in integrating Pinecone Vector Data Base with other tools like LangChain, OpenAI API using Python to implement real-world use cases and unleash the full potential of Vector Databases. Throughout the course, we will uncover the limitless possibilities of Vector Databases in generative AI. You will discover how these databases enable content generation, recommendation systems, language translation, and more. Additionally, we will discuss performance optimization, scalability considerations, and best practices for efficient implementation. Led by an expert instructor with a PhD in computational nano science and extensive experience as a data scientist at leading companies, you will benefit from their deep knowledge, practical insights, and passion for teaching AI and Machine Learning (ML). Join us now to embark on this transformative learning journey and position yourself at the forefront of Future-Proofing Generative AI with Vector Databases. Enroll today and unlock a world of AI innovation!

Dive into the world of AI with our comprehensive Udemy course, designed for enthusiasts eager to master instruction tuning, or supervised fine-tuning (SFT), using the incredibly powerful Tiny Llama 1.1B model. This course is perfect for data scientists, ML engineers, and anyone interested in the practical applications of fine-tuning large language models. Our curriculum is specially crafted to provide you with hands-on experience using the Tiny Llama 1.1B model, trained on a vast 3 trillion tokens and paired with the Databricks-crafted Dolly 15k record dataset. Through this course, you'll not only learn the basics of SFT but also how to effectively use the HuggingFace Transformers library to prepare your dataset, set up training, and compute accuracy—all within the accessible environment of Google Colab. What You Will Learn - Introduction to Supervised Fine-Tuning (SFT): Gain a solid understanding of the principles behind SFT and its importance in tailoring state-of-the-art language models to specific tasks. - Exploring Tiny Llama 1.1B: Delve into the architecture and features of the Tiny Llama 1.1B model and discover its role in the AI ecosystem. - Dataset Preparation with Dolly 15k: Learn how to prepare and preprocess the Dolly 15k record dataset to ensure your fine-tuning process is seamless and efficient. - HuggingFace Transformers Library: Get hands-on experience with the HuggingFace library, learning how to load models onto a GPU and prepare your training environment. - Training Setup and Execution: Walk through the steps to set up and execute the fine-tuning process using Google Colab with a focus on practical implementation. - Performance Evaluation: Learn how to compute accuracy and evaluate your model's performance, using metrics to ensure your SFT efforts are effective. - Real-World Application: Translate your new skills to real-world problems, understanding how to adapt your fine-tuned model to various domains. Model Used: TinyLlama-1.1B-intermediate-step-1431k-3T Dataset Used: databricks-dolly-15k Who This Course is For - Data Scientists and Machine Learning Engineers seeking to specialize in NLP and instruction tuning. - AI Practitioners looking to implement and scale fine-tuned language models for industry applications. - Software Developers eager to enhance applications with sophisticated language understanding capabilities. - Students and Academics desiring hands-on experience with state-of-the-art AI fine-tuning techniques. Prerequisites - Proficiency in Python and familiarity with machine learning and NLP concepts. - Experience with neural network frameworks, preferably PyTorch, as used by the HuggingFace Transformers library. - A Google account to access Google Colab for hands-on exercises.

In a constantly evolving digital world, Artificial Intelligence has ceased to be a futuristic concept to become an essential tool in various areas of our daily lives. However, the challenge has always been how to make this technology accessible to those who have no programming experience. This is where this course comes to life. Have you ever wondered how to create intelligent, automated solutions without having to learn to program from scratch? This course is your answer. We offer you a unique opportunity to learn how to develop applications powered by ChatGPT and LLMs without writing a single line of code. Not only do we provide you with access to one of the most revolutionary technologies of the moment, but we give you the ability to design, prototype and launch your own AI-based solutions. Content Description: - Solid Fundamentals: Start with a clear understanding of Language Models and discover the power behind ChatGPT. - Tools at your fingertips: Learn about cutting-edge tools like LangChain and Flowise that will allow you to bring your ideas to life. - Hands-on projects: Apply your knowledge through practical projects and challenges that guarantee an immersive learning experience. - Future of AI and ChatGPT: Discover Auto-GPT and other cutting-edge models that are defining the next horizon of AI. There are no longer any barriers between you and next-generation AI applications. Take this opportunity to master ChatGPT and other AI tools, all without having to dive into complex lines of code. Are you ready to transform the future with your own intelligent solutions? Start your journey today!

Welcome to the Captivating World of LLM Prompt Engineering! This course empowers you to unlock the true potential of Large Language Models (LLMs), regardless of your experience level. Whether you're a seasoned professional or a curious beginner, this comprehensive program equips you with the skills to become a master of LLM prompt engineering. Master the Art of Crafting Powerful Prompts: - Diverse Task Applications: Craft effective prompts tailored to various tasks, including generating informative summaries, creating captivating stories, or even translating languages, all through the power of well-designed prompts. - Advanced Techniques Exploration: Move beyond the basics and delve into advanced concepts like iterative prompting, where you refine your prompt based on the LLM's initial output. Additionally, explore few-shot learning, allowing you to achieve impressive results even with limited data. - Core LLM Concepts Demystified: Gain a solid understanding of fundamental LLM properties like statelessness and quantization. Explore how these properties impact prompt design and LLM behavior. Learn to identify and mitigate potential hallucinations in LLM outputs. Unleash LLM Capabilities Through Hands-on Learning: - Code Walkthroughs Deepen Understanding: Go beyond theory with interactive code walkthroughs using Lamma 2 as a platform. Actively explore code examples to gain practical experience in setting up, configuring LLMs, working with advanced models (e.g., quantized models), and leveraging specialized notebooks like AWQ for optimized workflows. - Real-World Applications Solidify Skills: This course emphasizes the practical application of LLM prompt engineering. Learn how to tailor prompts to solve specific real-world problems, ensuring accurate and creative AI outputs. Translate your newfound knowledge into tangible results. Structured Learning Journey for Success: - - Clear and Concise Explanations: Simplify complex topics with bite-sized lessons and clear explanations. - Interactive Learning Approach: Utilize a variety of learning methods, including interactive code walkthroughs, to reinforce understanding and foster your development as an LLM prompt engineering expert. - Progressive Curriculum Design: Build your expertise step-by-step, starting with the fundamentals of LLMs and prompt engineering and progressing to advanced techniques. Embrace the Future of AI Interaction: By mastering LLM prompt engineering, you'll be at the forefront of the human-AI interaction revolution. This course equips you with the skills and knowledge to confidently navigate this exciting field and unlock the true power of LLMs. Let's embark on this journey together and explore the boundless possibilities of AI!

Welcome to 'AI for Marketing - Job-based training 2024', a first-of-its kind short program designed for marketers, jobseekers and career change aspirants who would like to specialize on AI or work as a Digital Marketing Manager equipped with AI skills. This course is specifically created as a JOB-BASED TRAINING program thereby teaching concepts hands-on and relevant to real-work environment. If you are looking for a job in Marketing or if you are a student who would like to get first experience in AI, this course is also for you. Tools you will learn: 1. Machine Learning fundamentals 2. Supervised learning 3. Unsupervised learning 4. AI applications in Marketing: ChatGPT, Tidio Chatbots, Google Analytics and many more Extra Module and Benefits: 1. AI Fundamentals and Applications: Unlock exclusive access to one of our AI modules Learn from our experts leveraging AI to enhance your productivity and understand the wide variety of applications of AI across industries 2. Career Guidance Understand how to effectively search for a job, find startups, craft a compelling CV and Cover Letter, types of job platforms and many more! Trainers: Dr. Chetana Didigu - Germany Experienced Data Scientist, Product Owner, and PhD graduate from IIM Ahmedabad and has worked 10+ years in various top companies in the world like Amazon, FLIX, Zalando, HCL. Aravinth Palaniswamy - Germany Founder of 2 startups in Germany and India, Technology Consultant, and Chief Product & Growth Officer of Moyyn, and has 10+ years of experience in Venture Building, Product and Marketing. Arvi is one of the co-founders of AI based Recruitment Automation Platform - Moyyn.

Accessing Data Privacy Risks and knowing whether an organization is compliant with specific legal parameters are two things that can bring any company down when they are oblivious of what should be done. Hence, this course will be showing you how you can implement the General Data Protection Regulation by setting a couple of things right in your organization. In this course, you will be given in-depth lessons on the General Data Protection Regulation as well as mitigating risk compliance. Our instructors are well-experienced and dedicated professionals in every sense of the word. Their method of interaction is what can be appreciated by any class of students. Our experience in the field of data cannot be overemphasized, and our achievements speak volumes. We have spent quality time and plenty of years to build our knowledge and track record on the Data Governance Control Framework, intimating us with the necessary expertise in this field of study. We have got the best assessment methods for evaluating our students’ performance in the course of their learning, and our teaching techniques are nothing short of absolute brilliance. Above all, the benefits of going through this course are enormous. Participants will be fully entrenched in the know regarding how they can implement the General Data Protection Regulation. Participants should, at the end of the day, be able to establish the vulnerability status of an organization on data privacy risks.