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Free Download GenAI World - LLM, Fine-tuning, RAG & Prompt engineering Published 10/2024 Created by Rabbitt Learning MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 12 Lectures ( 42m ) | Size: 561 MB The single source of truth What you'll learn: Understand the fundamentals of prompting in the context of large language models (LLMs). Learn the importance of prompt engineering for optimizing model perform Explore advanced concepts like Direct Preference Optimization (DPO) and Parameter-Efficient Fine-Tuning (PEFT). Gain insights into Retrieval Augmented Generation (RAG), understanding its components and how it enhances LLM capabilities. Requirements: Yes, students should have: A foundational understanding of artificial intelligence and machine learning concepts, especially related to language models. Proficiency in Python programming, as the course includes detailed code examples and exercises. Familiarity with deep learning frameworks. Basic knowledge of natural language processing (NLP) and transformer models. Access to necessary computational resources, such as a GPU-enabled environment. Description: This course covers everything from Large Language Models (LLMs), prompt engineering to parameter-efficient fine-tuning (PEFT) and advanced concepts like Direct Preference Optimization (DPO). You'll also dive deep into Retrieval Augmented Generation (RAG) to enhance your LLMs' capabilities by integrating retrieval systems for superior responses.By the end of this course, you'll be equipped to create AI solutions that align perfectly with human intent and outperform standard models. What You'll Learn:Craft powerful and effective prompts for LLMs to optimize outputs.Master Direct Preference Optimization (DPO) and PEFT for domain-specific fine-tuning.Implement Retrieval Augmented Generation (RAG) to elevate model performance.Gain insights into state-of-the-art LLM capabilities, focusing on practical and advanced techniques.Develop customized solutions with hands-on code examples and exercises. What you will Get A foundational understanding of artificial intelligence and machine learning concepts, especially related to language models. Proficiency in Python programming, as the course includes detailed code examples and exercises. Familiarity with deep learning frameworks. Basic knowledge of natural language processing (NLP) and transformer models. Access to necessary computational resources, such as a GPU-enabled environment. In addition to the core topics, our course also features real-world case studies on fine-tuning, prompt engineering, and Retrieval Augmented Generation (RAG). These case studies offer practical, hands-on insights into how these techniques are applied in real AI projects .These case studies provide a practical framework for applying the theoretical concepts covered in the course, helping learners implement these methods in their own projects. Who this course is for: This course is ideal for: Machine learning engineers and data scientists looking to enhance their skills in fine-tuning large language models. AI researchers and practitioners interested in advanced techniques like RAG, PEFT, and QLoRA. Developers and programmers aiming to implement AI solutions that require domain-specific model customization. Students and academics studying artificial intelligence, machine learning, or natural language processing. Anyone interested in state-of-the-art AI technologies and how to apply them effectively in real-world scenarios. Homepage https://www.udemy.com/course/genai-world-llm-fine-tuning-rag-prompt-engineering/ Rapidgator https://rg.to/file/f59fdf8623032aa4f829304a12fe9127/nonlu.GenAI.World..LLM.Finetuning.RAG..Prompt.engineering.rar.html Fikper Free Download https://fikper.com/Tb2IRzSxjq/nonlu.GenAI.World..LLM.Finetuning.RAG..Prompt.engineering.rar.html No Password - Links are Interchangeable

Free Download GenAI Cybersecurity and Ethical Hacking - Zero to Hero Pro Published 9/2024 Created by Paul Carlo Tordecilla MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 111 Lectures ( 7h 30m ) | Size: 4.11 GB Transform into a Cybersecurity Expert with Hands-On Training in Ethical Hacking, AI, and Machine Learning What you'll learn: Students enrolled in this course will gain a comprehensive understanding of cybersecurity and IT security fundamentals. They will learn strategies to protect against hackers and prevent hacking attempts. They will delve into IT security and information security (INFOSEC). Students will develop robust cybersecurity defense strategies. The course covers networking basics and their crucial role in cybersecurity. Learners will explore ethical hacking techniques, starting from a beginner's perspective. They will progress to mastery of Kali Linux command line essentials. They will learn how to conduct information gathering, reconnaissance, and vulnerability analysis. Students will explore exploit techniques and engage in hands-on exploitation using the Metasploit Framework. Advanced security measures such as password attacks, wireless security, and web application security are integral parts of the curriculum. Students will learn automated web vulnerability scanning and social engineering. The course delves into the integration of artificial intelligence into cybersecurity strategies. It covers topics like cybersecurity with Generative AI and OpenAI. Students will utilize Python for cybersecurity applications. They will master threat detection and response with GenAI. Practical experience with tools like Splunk is provided. Techniques for anonymous browsing and privacy protection are taught. Through hands-on projects, students will develop an AI hacking tool. They will perform packet analysis and encryption. Students will build an AI-powered Windows Event Log Analyzer with OpenAI integration and machine learning. Requirements: To take this course, students should have basic computer knowledge. They should be familiar with using a computer and navigating operating systems. An understanding of basic networking concepts is helpful but not mandatory. A computer running Windows, macOS, or Linux with internet access is required. Students should be able to install software such as Kali Linux, Python, and other tools discussed in the course. No prior experience in cybersecurity or programming is necessary. A willingness to engage in hands-on projects and practical exercises is essential. Students should have an open mind and a keen interest in learning about both defensive and ethical hacking techniques. Description: Are you prepared for that transformative journey into the world of cybersecurity and ethical hacking? "GenAI Cybersecurity and Ethical Hacking: Zero to Hero Pro " is a comprehensive learning course, with state-of-the-art tools that will surely wake up your cybersecurity master ship skills in today's rapidly evolving digital landscape.We start from square one and take you through the absolute basics of networking, IT security, and INFOSEC. We understand how to counter hackers and prevent hacking attempts with our discussion on cybersecurity defense strategies. As we continue, we will then dive into actual hacking techniques into information gathering, reconnaissance, vulnerability analysis, and various forms of exploitation using tools like Kali Linux and the Metasploit Framework.It deals with leading-edge technologies, focusing on artificial intelligence and machine learning in revolutionizing cybersecurity. In this program, you have the opportunity to go deep into topics such as Cybersecurity with Generative AI and OpenAI and learn how to implement threat detection and response capabilities using GenAI. You would be working on real-world projects; these include developing an AI hacking tool, packet analysis, and encryption, along with building an AI-powered Windows Event Log Analyzer by integrating OpenAI.Instead, the course will focus more on the development of students' skills in anonymous browsing, protection of privacy, password attack, wireless security, web application security, and also social engineering. Learn Splunk in the best way with hands-on experience: Automate web vulnerability scanning and stay ahead of the curve of potential threats.By the end of this course, you will be equipped with a full-scale skill set that covers the traditional cybersecurity approach along with innovative AI-driven approaches. This would be the opening to become a guardian of the digital world for those who are either entering a career or are upgrading their knowledge.Enroll now and step closer to GenAI Cybersecurity and Ethical Hacking: Zero to Hero Pro! Who this course is for: This course is ideal for beginners and aspiring professionals who are new to cybersecurity and ethical hacking and wish to start a career in this dynamic field. It is suitable for students and enthusiasts eager to learn about both the fundamentals and advanced topics in cybersecurity. IT professionals, including network administrators and system administrators looking to enhance their cybersecurity skills, will find this course valuable. Security professionals seeking to update their knowledge with the latest AI-powered tools and techniques are encouraged to enroll. The course is beneficial for ethical hackers and security enthusiasts aiming to expand their toolkit with AI and machine learning applications. It is also for anyone interested in understanding the operation of cyber threats and how to defend against them. Additionally, AI and machine learning enthusiasts curious about the intersection of these technologies with cybersecurity will greatly benefit from this course. Professionals looking to apply AI and machine learning concepts to real-world security challenges will also find this course valuable. 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Free Download Mastering Genai - Fine-Tune & Adapt Llms Effectively Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1006.46 MB | Duration: 1h 7m Harness Advanced Techniques in AI: From Fine-Tuning to Ethical Deployment and Optimization What you'll learn Understand and describe the architecture of Generative AI models like GPT and BERT. Apply fine-tuning methods to adapt LLMs to specific tasks and industries. Evaluate and optimize LLM performance through advanced techniques Implement ethical guidelines and best practices in the deployment of GenAI models Requirements Basic understanding of AI concepts and terminology; no advanced technical skills required. Familiarity with Python programming to follow along with coding demos and exercises. Description Explore the cutting-edge field of Generative AI with our course, 'Mastering GenAI: Fine-Tune & Adapt LLMs Effectively.' Designed for professionals and enthusiasts alike, this course offers a deep dive into the mechanisms of large language models such as GPT and BERT. You'll learn how to fine-tune these models to meet specific requirements, ensuring they perform optimally across various industries.Through a mix of theoretical insights and practical exercises, parti[beeep]nts will explore different fine-tuning techniques including supervised, unsupervised, and reinforcement learning methods. The course will also address the critical aspects of model optimization, such as hyperparameter tuning and avoiding overfitting, to enhance both efficiency and accuracy.A significant focus will be on the ethical deployment of these technologies. You'll learn to navigate the complexities of AI ethics, ensuring your AI solutions are fair and equitable. This course will prepare you to effectively adapt and deploy AI models, making you a valuable asset in any tech-driven industry.By the end of this course, parti[beeep]nts will not only understand the theoretical underpinnings of generative AI but also be proficient in implementing and optimizing these models in a practical, ethical, and efficient manner. Whether you're looking to innovate within your organization, kickstart a career in AI, or academically explore AI technologies, this course will serve as a vital stepping stone to achieving those goals. Overview Section 1: Introduction Lecture 1 What is Gen AI ? Lecture 2 What are LLMs ? Section 2: Real-world Large Language Models Lecture 3 Decision Making: Build, Purchase, or Enhance Lecture 4 Introduction to Zero-shot Classification Lecture 5 Demonstrating a Proof of Concept Lecture 6 Essentials of Training and Fine-tuning Section 3: Fine-tuning Techniques for LLMs Lecture 7 Training and Fine-tuning Lecture 8 Supervised Fine-tuning vs. Parameter Efficient Fine-tunin Lecture 9 Approaches to Fine-tuning Lecture 10 Reinforcement learning from human feedback This course is ideal for AI enthusiasts, data scientists, and developers interested in extending their expertise into the realm of fine-tuning and adapting large language models,Suitable for IT professionals looking to leverage GenAI for improving business processes and creating innovative solutions.,Perfect for academic researchers and students in computer science who want practical experience with state-of-the-art AI technologies.,Security architects and engineers who aim to understand the cybersecurity implications of deploying generative AI models in their operations. Homepage https://www.udemy.com/course/fine-tuning-and-adapting-genai-models/ Rapidgator https://rg.to/file/67d204c8d2478aefbe5e4b8e60c55482/ezmxr.Mastering.Genai.FineTune..Adapt.Llms.Effectively.part1.rar.html https://rg.to/file/63884c75c2442f161a951af07e9588ef/ezmxr.Mastering.Genai.FineTune..Adapt.Llms.Effectively.part2.rar.html Fikper Free Download https://fikper.com/8vPTUwz27k/ezmxr.Mastering.Genai.FineTune..Adapt.Llms.Effectively.part1.rar.html https://fikper.com/kXOripHkgH/ezmxr.Mastering.Genai.FineTune..Adapt.Llms.Effectively.part2.rar.html No Password - Links are Interchangeable

Free Download GenAI and Predictive AI Architecture Foundations Released: 09/2024 Duration: 1h 16m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 157 MB Level: Intermediate | Genre: eLearning | Language: English Get a clear understanding of how AI solutions actually work, starting with their basic architectures and advancing to system components and architectural differences between generative AI and predictive AI systems. Join LinkedIn Top Voice and best-selling author Thomas Erl as he breaks down and explains, in plain English, the foundational building blocks and the primary moving parts behind contemporary AI solution environments. This course provides genuine insight into how AI systems function in the real world, and is essential for professionals already working with application and enterprise architectures, as well as professionals in the AI and data science fields. Homepage https://www.linkedin.com/learning/genai-and-predictive-ai-architecture-foundations?u=121350530 TakeFile https://takefile.link/ng378cbfiiuv/wmlwn.GenAI.and.Predictive.AI.Architecture.Foundations.rar.html Rapidgator https://rg.to/file/96dcdb1f7b91625374811c94b2392617/wmlwn.GenAI.and.Predictive.AI.Architecture.Foundations.rar.html No Password - Links are Interchangeable

Free Download [NEW] GitHub Copilot - Use GenAI to Write Terraform For You! Published 9/2024 Created by Bryan Krausen • 130,000+ Enrollments Worldwide MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 26 Lectures ( 3h 44m ) | Size: 1.64 GB Increase Your Productivity! Leverage GenAI to Write and Optimize Your HashiCorp Terraform Code with GitHub Copilot What you'll learn: Use GitHub Copilot for developing Terraform code, leveraging GenAI capabilities effectively. Accelerate your Terraform development cycles by utilizing GitHub Copilot to generate and optimize infrastructure-as-code (IaC) scripts Improve code quality and consistency through automated suggestions and templates provided by GitHub Copilot Learn techniques to troubleshoot and customize GitHub Copilot's suggestions to better align with specific project requirements and best practices in Terraform d Requirements: Familiarity with the basics of Terraform, including understanding resources, providers, variables, and state management. An active GitHub account is necessary to access GitHub Copilot and to practice code examples provided in the course Familiarity with using a text editor or integrated development environment (IDE) of choice (e.g., VS Code) to edit and manage code files Description: Are you ready to supercharge your HashiCorp Terraform coding with the power of AI? Welcome to the course that will revolutionize the way you approach Infrastructure as Code (IaC) in your DevOps workflow.Imagine having an AI-powered coding assistant that understands HashiCorp Terraform as well as you do, helping you quickly write, optimize, and troubleshoot your infrastructure configurations. That's exactly what GitHub Copilot offers, and in this course, you'll learn how to unlock its full potential.Throughout this course, we'll build complex environments using AWS, using only FREE resources so you can learn without incurring any costs. All skills and concepts can easily be used to build any environment you need and you can even provision resources on other public clouds using the same workflows.Throughout the course, we'll learn and master topics such as:Getting you up to speed with GitHub CopilotShowing you how to integrate this game-changing tool into your existing Terraform and DevOps workflowsUnderstanding how Copilot can help you write Terraform code (HCL) faster, with fewer errors, and more confidenceLearning how to navigate the nuances of AI-generated code, ensuring it's not only functional but also secure and efficient for your infrastructure needs.You'll learn how to develop new code, improve existing code, and even prepare your environment to take advantage of GitHub Copilot.But this course isn't just about learning the tool-it's about transforming the way you work. You'll explore real-world scenarios where Copilot can be your secret weapon, turning tedious coding tasks into quick wins. Whether you're managing cloud infrastructure, automating deployments, or simply looking to improve your Terraform skills, this course is designed to give you the edge in the fast-paced world of DevOps.By the end of this course, you won't just be proficient with GitHub Copilot; you'll be a Terraform powerhouse, capable of leveraging AI to streamline your DevOps processes and deliver results faster than ever before.Don't miss out on this opportunity to elevate your Terraform and DevOps skills-enroll today and take your coding to the next level with GitHub Copilot! Who this course is for: Professionals looking to streamline and automate their Terraform workflow using advanced AI tools like GitHub Copilot Developers interested in enhancing their Terraform skills and leveraging AI-driven assistance to write efficient infrastructure code Individuals responsible for designing and managing cloud infrastructure, seeking to adopt AI technologies for faster and more reliable Terraform deployments Homepage https://www.udemy.com/course/githubcopilot/ Rapidgator https://rg.to/file/4049426a807e13c8d87e674b5ba4b601/urfgj.NEW.GitHub.Copilot.Use.GenAI.to.Write.Terraform.For.You.part1.rar.html https://rg.to/file/06b494a87e2bf69c1ed3615fd14ea71d/urfgj.NEW.GitHub.Copilot.Use.GenAI.to.Write.Terraform.For.You.part2.rar.html Fikper Free Download https://fikper.com/5CKStp0IuW/urfgj.NEW.GitHub.Copilot.Use.GenAI.to.Write.Terraform.For.You.part1.rar.html https://fikper.com/EzJcp7OVfd/urfgj.NEW.GitHub.Copilot.Use.GenAI.to.Write.Terraform.For.You.part2.rar.html No Password - Links are Interchangeable

Free Download GenAI Application Architecture - Scalable & Secure AI Design Published 9/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 2h 40m | Size: 2.51 GB Build scalable, secure, and efficient GenAI applications with AWS, MLOps, monitoring, and cloud-native architecture What you'll learn Design Scalable GenAI Applications: Learn to architect and build scalable GenAI applications using the LGPL architecture, focusing on Layer, Gate, Pipes Implement Resiliency and Error Handling: Understand how to incorporate error handling, monitoring, logging, and disaster recovery to create resilient GenAI Apps Ensure Security and Cost Efficiency: Develop secure and cost-effective GenAI solutions by leveraging AWS security services, containerization Automate and Optimize with MLOps & CI/CD: Learn to implement MLOps, CI/CD, and Explainable AI (XAI) for streamlined deployment and future-proofing GenAI apps Requirements Basic Knowledge of AI and Machine Learning: Understanding of fundamental AI and machine learning concepts. Familiarity with AWS: Experience with AWS services such as Lambda, S3, and DynamoDB is recommended. Programming Skills: Intermediate-level knowledge of Python is essential. Basic Understanding of Software Architecture: Familiarity with software architecture principles such as scalability, load balancing, and error handling. Description Master the essential techniques and best practices for designing and architecting scalable, secure, and cost-effective Generative AI (GenAI) applications. In this course, you'll explore the principles of the LGPL architecture (Layers, Gates, Pipes, and Loops) and how they apply to building GenAI systems using modern cloud services like AWS. We'll cover critical topics such as load balancing, containerization, error handling, monitoring, logging, and disaster recovery. This course is ideal for those looking to understand GenAI architecture, ensuring applications are resilient, secure, and efficient.What You'll Learn:Architect scalable and secure GenAI applications using the LGPL model.Understand core concepts such as containerization, load balancing, and disaster recovery.Learn best practices for monitoring, logging, and error handling in GenAI systems.Explore MLOps, CI/CD, and security strategies for future-proofing AI applications.This course focuses on the architecture and principles behind building robust GenAI systems, providing the knowledge needed to design effective AI solutions.Enroll now to transform your GenAI Application Architecture skills to the next level. Master GenAI Application Architecture - the core best practices and techniques for building secure, efficient, scalable GenAI Applications.Ready to take your skills to the next level? Join me, and let's get started. See you inside the course! Who this course is for AI Developers and Engineers: Those looking to build scalable, secure, and cost-effective GenAI applications. Cloud Architects: Professionals working with AWS who want to implement GenAI architectures using best practices. Machine Learning Enthusiasts: Individuals with a foundational understanding of machine learning and programming who want to expand into GenAI development. Software Engineers: Engineers seeking to integrate AI into cloud-native applications and implement MLOps pipelines Homepage https://www.udemy.com/course/genai-application-architecture/ Rapidgator https://rg.to/file/eb0dab6db8b173a5e31e2c1124e05cb1/idmrc.GenAI.Application.Architecture.Scalable..Secure.AI.Design.part1.rar.html https://rg.to/file/a15457d993ba63048e481b780ea9f7a6/idmrc.GenAI.Application.Architecture.Scalable..Secure.AI.Design.part2.rar.html https://rg.to/file/ce1437543d5df735599d92cd55596194/idmrc.GenAI.Application.Architecture.Scalable..Secure.AI.Design.part3.rar.html Fikper Free Download https://fikper.com/kOled1XDOx/idmrc.GenAI.Application.Architecture.Scalable..Secure.AI.Design.part1.rar.html https://fikper.com/5kl1QK2FDE/idmrc.GenAI.Application.Architecture.Scalable..Secure.AI.Design.part2.rar.html https://fikper.com/sW8thybbOP/idmrc.GenAI.Application.Architecture.Scalable..Secure.AI.Design.part3.rar.html No Password - Links are Interchangeable