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480 Questions designed by a Salesforce Expert with 14 Certificates. - Unlock your path to Salesforce success with our comprehensive Salesforce AI Associate Practice Exams course. Designed to propel you towards achieving your Salesforce Certified Associate AI certification, this test exam offers an in-depth exploration of the key concepts and skills required for the exam. - Welcome to the Salesforce Associate AI Certification practice exam. Please note that these questions are for practical purposes only and should not be considered as the exact questions that will appear on the Salesforce Certified Associate AI exam. This practice exam assesses your knowledge in key areas outlined in the Salesforce Certified AI Associate Exam Guide. Key areas to be evaluated in this certification include, but are not limited to: 1. AI Basics: Understanding fundamental concepts of artificial intelligence. 2. Salesforce Einstein: Knowledge of Salesforce's AI platform and its capabilities. 3. AI Implementation: Ability to implement AI solutions within the Salesforce ecosystem. 4. Data Analysis: Proficiency in analyzing and utilizing data for AI-driven insights. 5. Predictive Modeling: Skills in building predictive models using AI tools. Be sure to study Salesforce's official materials and exam guides from the provided link for comprehensive preparation in these areas. Your success in the actual certification exam will depend on a thorough understanding of these topics. Best of luck!

Recently, we have seen a shift in AI that wasn't very obvious. Generative Artificial Intelligence (GAI) - the part of AI that can generate all kinds of data - started to yield acceptable results, getting better and better. As GAI models get better, questions arise e.g. what will be possible with GAI models? Or, how to utilize data generation for your own projects? In this course, we answer these and more questions as best as possible. There are 3 angles that we take: 1. Application angle: we get to know many GAI application fields, where we then ideate what further projects could emerge from that. Ultimately, we point to good starting points and how to get GAI models implemented effectively. The application list is down below. 2. Tech angle: we see what GAI models exist. We will focus on only relevant parts of the code and not on administrative code that won't be accurate a year from now (it's one google away). Further, there will be an excursion: from computation graphs, to neural networks, to deep neural networks, to convolutional neural networks (the basis for image and video generation). 3. The architecture list is down below. Ethical angle/ Ethical AI: we discuss the concerns of GAI models and what companies and governments do to prevent further harm. Enjoy your GAI journey! List of discussed application fields: - Cybersecurity 2.0 (Adversarial Attack vs. Defense) - 3D Object Generation - Text-to-Image Translation - Video-to-Video Translation - Superresolution - Interactive Image Generation - Face Generation - Generative Art - Data Compression with GANs - Domain-Transfer (i.e. Style-Transfer, Sketch-to-Image, Segmentation-to-Image) - Crypto, Blockchain, NFTs - Idea Generator - Automatic Video Generation and Video Prediction - Text Generation, NLP Models (incl. Coding Suggestions like Co-Pilot) - GAI Outlook - etc. Generative AI Architectures/ Models that we cover in the course (at least conceptually): - (Vanilla) GAN - AutoEncoder - Variational AutoEncoder - Style-GAN - conditional GAN - 3D-GAN - GauGAN - DC-GAN - CycleGAN - GPT-3 - Progressive GAN - BiGAN - GameGAN - BigGAN - Pix2Vox - WGAN - StackGAN - etc.

This course covers the fundamental technical and business concepts of Generative AI, or simply GenAI. It is the most hyped-up technology existing in the market today. Gartner has listed it on the top of its two hype curves for 2023: AI technologies hype curve and Emerging Technologies hype curve. This technology became popular since the launch of ChatGPT, a GenAI-powered chatbot, released by OpenAI, on 30th Nov 2022. ChatGPT has 100 million+ users and its website sees nearly 1.5 billion monthly visits. GenAI has a massive impact on individuals and businesses around the globe. It is a digital transformation technology, that has the potential to change the ways of doing business. Businesses around the globe are exploring how to best exploit its potential to add value to their customers. It is important that individuals have the fundamental knowledge of this technology, which will play a significant role in shaping their lives in the coming years- so that they can be more ethically aware and socially responsible while using GenAI. Businesses too must cultivate this knowledge to understand their customer needs better and offer the best GenAI solutions for them. However, most of the content available today is either too high-level or too complex with lots of technical diagrams and jargon. This has inspired me to develop this course with substantial content in a simplified and easy-to-understand language for people with both technical and non-technical backgrounds. This course currently contains four sections: 1. Overview 2. Business Impact 3. Architecture 4. Training More sections such as Prompt Engineering, Inference, will be added soon. The lecture videos contain a simplified explanation of the technical and business concepts for people with both technical and non-technical backgrounds. For the audience interested in exploring the technicalities further, kindly refer to the additional content attached to some of the lectures. If you have any questions or doubts, kindly email me through the Udemy platform. You can also connect with me through LinkedIn. Happy Learning!

Welcome to our Comprehensive Course on ChatGPT, Google Gemini, Github Copilot, Generative AI, and Artificial Intelligence! Are you prepared to advance your skills in these dynamic fields? Whether you're a seasoned professional or a newcomer, our course provides understanding of AI fundamentals to mastering Generative AI, building LLM based programs using ChatGPT and Gemini models. Key Features: - Artificial Intelligence Fundamentals: Build a solid foundation in AI, exploring key concepts and practical applications of Deep Learning and Generative AI. - Boosting Productivity with Effective Prompt Engineering: Discover the secrets of ChatGPT through mastering prompt engineering. Optimize prompts for maximum productivity and creativity. Elevate your career with impressive resumes and interview preparations using ChatGPT's capabilities. - Exploring Alternatives and Diving into DALL-E: Delve into alternative models like Bard and Bing in chat-based AI. Compare DALL-E variants to understand their unique features. - OpenAI Deep Dive: Navigate the OpenAI ecosystem confidently, exploring models, APIs, and integration with tools like Postman. - Generative AI Internals: Dive deep into Generative AI internals, understanding its impact on industries. - Jupyter Notebook and Practical Examples: Master Jupyter Lab for seamless interaction with OpenAI models through practical examples. - Token Pricing, SQL Interaction, and Hands-on Programs: Understand token pricing and leverage generative models for natural language interactions with data. - Advanced Generative AI: Explore advanced techniques like embeddings and fine-tuning for real-world scenarios. - Github Copilot: Revolutionizing Code Development: Discover Github Copilot's revolutionary impact on code development, enhancing productivity and efficiency. - Real-World Project Implementation: Apply knowledge to hands-on projects integrating various OpenAI models. - Google Gemini models: Learn the basics and applications of Google Gemini, comparing it with ChatGPT4. - LangChain: Learn building LLM applications using LCEL(LangChain Expression Language) framework, RAG (Retrieval augmented generation), & building AI agents for complex tasks. - OpenAI Sora - Text to Video Model: Master OpenAI Sora's architecture and diffusion models. - Generative AI Future: Address job displacement concerns and explore new opportunities in the ever-evolving landscape. Join Us on this AI Adventure: Unlock Your Potential Enroll now and embark on an exciting adventure into the realms of ChatGPT, Gemini, Generative AI, Github Copilot, and Artificial Intelligence. Whether you're aiming to enhance your career, optimize productivity, or explore AI's frontiers, our course is your comprehensive guide. Shape the future of technology with confidence. Let's unlock your potential together!

The JN0-251 Mist AI, Associate (JNCIA-MistAI) Exam is an essential certification for professionals seeking to enhance their expertise in managing and troubleshooting Juniper Mist AI networks. This comprehensive course is designed to help individuals prepare for the certification exam by providing a series of realistic practice tests. With the increasing demand for efficient network management solutions, the JN0-251 certification holds significant value in the IT industry. By successfully passing this exam, candidates demonstrate their ability to configure, troubleshoot, and maintain Juniper Mist AI networks effectively. The course focuses on extensive practice tests, consisting of multiple-choice questions designed to mimic the format and difficulty level of the actual JNCIA-MistAI exam. These practice tests are carefully crafted to cover all the essential topics, concepts, and skills required to excel in the certification. Each question in the practice tests is supplemented with detailed explanations, providing learners with a comprehensive understanding of the correct answers and the underlying reasoning behind them. These explanations serve as valuable learning resources, allowing candidates to strengthen their knowledge and fill any gaps in their understanding. The course is entirely centered around the practice tests and explanations, making it highly focused and time-efficient. By utilizing this approach, learners can streamline their exam preparation process and maximize their chances of success. The practice tests are regularly updated to align with the latest exam syllabus and ensure that candidates are well-prepared for any potential changes or updates. Through this course, participants will acquire the necessary skills to identify common mistakes, recognize key concepts, and exhibit competence in solving complex problems related to Juniper Mist AI networks. Moreover, the detailed explanations provided for each question enable learners to grasp the underlying theories, protocols, and technologies associated with Juniper Mist AI. Whether you are a network engineer, administrator, or any professional seeking a thorough understanding of Juniper Mist AI networks, the JN0-251 Mist AI, Associate (JNCIA-MistAI) Exam practice tests course is an invaluable resource. Enhance your knowledge, boost your confidence, and improve your prospects by enrolling in this comprehensive exam preparation course today.

UPDATE: Added 90 new questions with explanations. The course "Exam AI-900: Microsoft Azure AI Fundamentals Practice Tests" is a meticulously designed resource for individuals aspiring to gain the AI-900 certification exam conducted by Microsoft. This foundational certification aims to validate your understanding and expertise in the key concepts of AI, and their implementation in the Microsoft Azure ecosystem. The course brings to you a comprehensive set of practice tests that mirror the format, style, and difficulty of the actual AI-900 exam. It delves into the fundamentals of AI workloads and considerations, principles of machine learning on Azure, computer vision workloads on Azure, natural language processing workloads on Azure, and conversational AI workloads on Azure. Through these practice tests, you will gain extensive exposure to the various facets of the exam. Each question within the practice tests is followed by an in-depth explanation of the correct answer, providing you with a better understanding of the underlying concepts. This practice-oriented approach aims to reinforce your understanding of the key AI principles and prepare you for the exam. By enrolling in the "Exam AI-900: Microsoft Azure AI Fundamentals Practice Tests" course, you'll enhance your readiness for the actual certification exam, gaining a comprehensive understanding of Azure AI fundamentals in the process. The scope of the exam: - Identify features of common AI workloads - Identify guiding principles for responsible AI - Identify common machine learning types - Describe core machine learning concepts - Describe capabilities of visual tools in Azure Machine Learning Studio - Identify common types of computer vision solution - Identify Azure tools and services for computer vision tasks - Identify features of common NLP Workload Scenarios - Identify Azure tools and services for NLP workloads - Identify considerations for conversational AI solutions on Azure Is it possible to take the practice test more than once? Certainly, you are allowed to attempt each practice test multiple times. Upon completion of the practice test, your final outcome will be displayed. With every attempt, the sequence of questions and answers will be randomized. Is there a time restriction for the practice tests? Indeed, each test comes with a time constraint of 120 seconds for each question. What score is required? The target achievement threshold for each practice test is to achieve at least 70% correct answers. Do the questions have explanations? Yes, all questions have explanations for each answer. Am I granted access to my responses? Absolutely, you have the opportunity to review all the answers you submitted and ascertain which ones were correct and which ones were not. Are the questions updated regularly? Indeed, the questions are routinely updated to ensure the best learning experience. Additional Note: It is strongly recommended that you take these exams multiple times until you consistently score 90% or higher on each test. Take the challenge without hesitation and start your journey today. Good luck!

Unlock the Power of Machine Learning & AI: Master the Art of Turning Data into Insight Discover the Future of Technology with Our Comprehensive Machine Learning & AI Course - Featuring Generative AI, Deep Learning, and Beyond! In an era where Machine Learning (ML) and Artificial Intelligence (AI) are revolutionizing industries across the globe, understanding how giants like Google, Amazon, and Udemy leverage these technologies to extract meaningful insights from vast data sets is more critical than ever. Whether you're aiming to join the ranks of top-tier AI specialists—with an average salary of $159,000 as reported by Glassdoor—or you're driven by the fascinating challenges this field offers, our course is your gateway to an exciting new career trajectory. Designed for individuals with programming or scripting backgrounds, this course goes beyond the basics, preparing you to stand out in the competitive tech industry. Our curriculum, enriched with over 145 lectures and 20+ hours of video content, is crafted to provide hands-on experience with Python, guiding you from the fundamentals of statistics to the cutting-edge advancements in generative AI. Why Choose This Course? - Updated Content on Generative AI: Dive into the latest in AI with modules on transformers, GPT, ChatGPT, the OpenAI API, Advanced Retrieval Augmented Generation (RAG), LLM agents, langchain, and self-attention based neural networks. - Real-World Application: Learn through Python code examples based on real-life scenarios, making the abstract concepts of ML and AI tangible and actionable. - Industry-Relevant Skills: Our curriculum is designed based on the analysis of job listings from top tech firms, ensuring you gain the skills most sought after by employers. - Diverse Topics Covered: From neural networks, TensorFlow, and Keras to sentiment analysis and image recognition, our course covers a wide range of ML models and techniques, ensuring a well-rounded education. - Accessible Learning: Complex concepts are explained in plain English, focusing on practical application rather than academic jargon, making the learning process straightforward and engaging. Course Highlights: - Introduction to Python and basic statistics, setting a strong foundation for your journey in ML and AI. - Deep Learning techniques, including MLPs, CNNs, and RNNs, with practical exercises in TensorFlow and Keras. - Extensive modules on the mechanics of modern generative AI, including transformers and the OpenAI API, with hands-on projects like fine-tuning GPT, Advanced RAG, langchain, and LLM agents. - A comprehensive overview of machine learning models beyond GenAI, including SVMs, reinforcement learning, decision trees, and more, ensuring you have a broad understanding of the field. - Practical data science applications, such as data visualization, regression analysis, clustering, and feature engineering, empowering you to tackle real-world data challenges. - A special section on Apache Spark, enabling you to apply these techniques to big data, analyzed on computing clusters. No previous Python experience? No problem! We kickstart your journey with a Python crash course to ensure you're well-equipped to tackle the modules that follow. Transform Your Career Today Join a community of learners who have successfully transitioned into the tech industry, leveraging the knowledge and skills acquired from our course to excel in corporate and research roles in AI and ML. "I started doing your course... and it was pivotal in helping me transition into a role where I now solve corporate problems using AI. Your course demystified how to succeed in corporate AI research, making you the most impressive instructor in ML I've encountered." - Kanad Basu, PhD Are you ready to step into the future of technology and make a mark in the fields of machine learning and artificial intelligence? Enroll now and embark on a journey that transforms data into powerful insights, paving your way to a rewarding career in AI and ML.

Learn how to create state of the art AI for video games using Unity. I believe in a practical approach in learning so this course will be primarily project-based. You won't just learn dry theory and forget everything within a matter of days but instead apply the learned concepts to two actual Unity-Projects: - Catch: A simple digital replica of play every kid's favourite game: catch - Colony Simulation: A game like Rimworld or Oxygen Not Included, where you can't control the NPCs directly, but instead they are controlled by the AI and you need to help them survive by making sure they've got enough to eat. Also this course contains a free exclusive Behavior-Designer Educational-License, which would normally cost ~90$. Behavior Designer is the industry-standard solution for Behaviortrees and generously provided me with an exclusive Educational License, which they specifically built for this course. So you won't get it anywhere else. Also you will of course get full lifetime access to the course. We'll start with the simplest AI-System that there is, namely State-Machines. After that we'll improve State-Machines and make them more extensible with the State-Pattern. Then we'll hit the main topic which is one of the more advanced techniques that are used in Indie- and AAA-Gameproductions alike: BehaviorTrees. Lastly we'll have a glimpse at one of the more experimental AI-Approaches, namely Genetic Algorithms, which are more of a niche topic but have the potential for very interesting game-mechanics that stand out of the crowd. Whereas this course is already rather extensive and covers the most important aspects of AI for modern gamedevelopment, I can't possibly cover everything of this huge field. For example I won't address machine learning because this topic alone would fill a whole bunch of courses and really isn't that practical for most Game-AIs because of the lack of control you have over it. By the end of the course you'll be confident with the most important AI-Techniques- and Design Patterns for modern Gamedevelopment. So what are you waiting for, join me now and start creating astonishing AI-Systems yourself.

Complete Step by Step on How to create videos using only AI tools: ChatGPT and Flexclip Start to Finish. AI is coming whether you like it or not but the question is whether you adapt to it to benefit from it or you get left behind. Choice is yours! All you need is just two AI Tools. I have included the whole process of creating the video from start to finish. First part has what is included in the course then the simple requirements, then the demonstration of the two platforms we used in the course. Steps are simple and exact without wasting anytime, I do not like to include any unnecessary information. After that we include the whole process as listed below. Creating an Intro video & audio file for your channel. Creating the script. Converting the script to audio files. Selecting the video files. Matching the video files with audio files. Creating the Outro video and audio file. Creating keywords for the video using ChatGPT. Uploading the video file to youtube channel from start to finish. Please share this content with others if this can benefit them. Thank you for taking the course. Hope you will use what you learnt here to upload your videos to social media platforms. Please let me know if you have any questions. Have a Great Day HAPPY LEARNING!

This is a self-paced lab that takes place in the Google Cloud console. In this lab, you learn how to perform multimodal retrieval augmented generation (RAG) using Vertex AI Gemini API.

Google Cloud Google Cloud ML Google Cloud MLOps MLOps MLOps MLOps MLOps ? Students will access the Vertex AI Feature Store at the SDK layer.

L'intelligence artificielle (IA) et le machine learning (ML) représentent une évolution importante de l'informatique et transforment rapidement un grand nombre de secteurs. Le cours ""Innovating with Google Cloud Artificial Intelligence"" explore comment les organizations peuvent utiliser l'IA et le ML pour repenser leurs processus métier. Ce cours fait partie du parcours de formation Cloud Digital Leader. Il vise à aider les participants à évoluer dans leur poste et à bâtir l'avenir de leur entreprise.