Prep Tests: Azure AI Engineer Associate Exam AI-102

What you'll learn Identify real-world generative AI uses and describe popular generative AI models and tools for text, code, image, audio, and video Explain generative AI prompt engineering concepts, examples, and common tools and learn techniques needed to create effective, impactful prompts Learn about tools and techniques to generate code snippets, scripts, test cases, and applications using generative AI models Develop innovative software engineering solutions using AI-powered tools and LLMs

A Cloud Developer designs, builds, analyzes, and maintains cloud-native applications. This learning path guides you through a curated collection of on-demand courses, labs, and skill badges that provide you with real-world, hands-on experience using Google Cloud technologies essential to the Cloud Developer role. Once you complete the path, check out the Google Cloud Developer certification to take the next steps on your professional journey. Applied Learning Project This specialization incorporates hands-on labs using our Qwiklabs platform. These hands on components will let you apply the skills you learn in the video lectures. Projects will incorporate topics such as Google Cloud products, which are used and configured within Qwiklabs. You can expect to gain practical hands-on experience with the concepts explained throughout the modules.

Get ready to build, train, and deploy intelligent systems that can revolutionize various industries and solve complex problems. Are you fascinated by the world of artificial intelligence and machine learning? Do you want to unlock the power of neural networks and learn how to build intelligent systems? Look no further! Join our comprehensive course on building, training, and deploying neural networks with TensorFlow, the leading framework for deep learning in Python. In this course, you will embark on an exciting journey that will take you from the fundamentals of TensorFlow to creating your very own neural networks. Whether you are a beginner in machine learning or an experienced developer looking to expand your skillset, this course is designed to cater to learners of all levels. No prior knowledge of TensorFlow or deep learning is required! Why choose this course? - Practical approach: We believe in hands-on learning, and this course is packed with real-world examples and projects that will reinforce your understanding of TensorFlow and neural networks. - User-friendly structure: Our course is organized into ten engaging lessons, allowing you to progress step-by-step at your own pace. Each lesson builds upon the previous one, ensuring a seamless learning experience. - Python-powered: Python is the language of choice for machine learning, and this course leverages its simplicity and versatility to teach you the concepts and techniques required to build powerful neural networks. What will you learn in comprehensive and user-friendly course? - Course Overview: Get acquainted with the course structure and objectives, setting the stage for your deep learning journey. - Why Learn TensorFlow: Discover the significance of TensorFlow in the world of AI and machine learning, and learn why it's the go-to framework for neural networks. - Setting up the TensorFlow Environment: Learn how to install and configure TensorFlow on your machine, ensuring a smooth development experience. - AI and Machine Learning Concepts: Build a strong foundation by exploring essential concepts in artificial intelligence and machine learning. - Applying the Machine Learning Workflow with TensorFlow and Python: Understand the end-to-end process of building machine learning models using TensorFlow and Python, from data preparation to model evaluation. - Understanding Neural Networks: Dive deep into the world of neural networks, understanding their structure, components, and functioning. - Building and Training Your First Neural Network: Roll up your sleeves and start building! Learn how to design and train your very own neural network using TensorFlow. - Monitoring and Improving Neural Network Performance: Discover techniques to monitor and evaluate the performance of your neural network, and explore strategies to enhance its accuracy and efficiency. - Deploying Your Neural Network: Learn how to deploy your trained neural network into production environments, making it available for real-world applications. - Final Words: Wrap up the course with a recap of the key concepts and insights gained, and explore avenues for further exploration and growth in the field of deep learning. Example Projects: - House Price Prediction: Harness the power of neural networks to predict house prices based on their sizes, gaining insights into regression tasks. - Cloth Type Identification: Develop a neural network that can identify different types of clothing items from images, opening doors to image classification techniques. Don't miss this golden opportunity to unlock the power of artificial intelligence and machine learning. Enroll now and take your first step towards becoming a TensorFlow hero!