AI Design and Engineering with Microsoft Azure

One in ten global enterprises use at least ten artificial intelligence (AI), including chatbots and process optimization, as well as fraud analysis. This course will help you become an expert in AI and machine-learning and increase your professional standing. This course will teach you the basics of Azure, Microsoft's powerful tool to build cloud-based machine learning applications. Learn about Azure's core services and pillars: security, privacy compliance, and trust. Amazon Web Services is the company's cloud platform provider. You will also learn the basics of Amazon Web Services. You will need to manage hardware and software in order to store data, stream video, and host a website. This is an unnecessary hurdle when you deliver an application to users. This problem can be solved by cloud computing.

This course will show you how businesses use these services to be more efficient and successful. You'll find out about the differences between the three core cloud computing models: infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS) and software-as-a-service (SaaS). These models are becoming more popular than standard IT software for businesses. This course will help you understand the fundamental principles behind chatbots and digital assistants like Siri and Alexa. These two technologies, AI and cloud computing, are making it possible to create intuitive, connected experiences. Microsoft has accredited this course

Are you ready to make your first steps in your career as an artificial intelligence professional? This self-paced course combines engaging lectures with hands-on activities to give you an overview of AI and the future of software solutions. It also demonstrates how AI can be applied to real-world applications.

AI can be used in smart apps to improve efficiency and enrich the lives of people. Machine learning can be used for predictive models of AI. You'll also learn how software can be used for processing, analysing, and extracting meaning from natural language. Chatbots are able to communicate via text and speech between humans as well as AI systems.

Machine learning is an AI application that allows computers to learn from their experience and make improvements automatically. As the foundation of AI, you will learn about all aspects of machine-learning computer algorithms. Learn how AI uses machine learning along with deep learning to solve real-world problems.

How does artificial intelligence work to build better conversational user interfaces (CUIs), and how is conversation-as-a-platform (CaaP) providing new ways to interact directly with companies, important data and key services? This course will show you how intelligent applications, also known as interaction bots or chatbots provide richer, more personal and more human-like experience.

Microsoft has granted accreditation to this course

How can beginners learn Python programming? The powerful programming language is easy to learn for beginners. This course provides a solid introduction to programming concepts and how you can code in Python.

Before you can perform data analysis with Python, you will need to know the basics of syntax, variables, and types. Once you have mastered the basics, you can move on to data structures like creating and manipulating regular Python lists and NumPy arrays.

Along the way you'll learn Python functions, control flows, import packages, and other useful information. You will also discover how to do interesting calculations. You'll also be able to dive into data visualization with this Python online course. This course will allow you create stunning visualisations of real data and customize plots.

This online Python course will show you why Python is the best language for AI and machine-learning. Machine learning with Python allows computers to recognize and learn from specific patterns. Python AI can also make predictions and estimate potential answers.

Learn how Python coding allows you to create complex networks with powerful data management capabilities. You can use Python to transform large amounts of data into usable, easily-understood data.

This course will teach you how Python can be used for high-volume data presentation, including heat maps and histograms as well as raincloud plots. It will also help you to analyse the data and make better data-based decision making. Microsoft has accredited this course.

For the development of artificial intelligence systems (AI), a solid foundation in mathematics knowledge is essential. What are the essential math skills needed to study machine learning or AI?

This primer course is for you if you don't know much about mathematics or have lost your knowledge.

This course will focus on the three major branches of mathematics that are used in data science, artificial intelligence and calculation: linear algebra and calculus. The course will cover the fundamental topics in each of these areas, from functions and equations to differentiation and optimization to vectors and matrix.

These concepts and techniques will give you the foundational knowledge necessary to launch your machine learning career.

How can you improve your understanding of machine learning concepts (ML) and how Python works within these concepts?

This course in data science will provide you with a solid foundation in machine learning theories and practical experience building, validating, and deploying machine-learning models.

Learn the basics of machine learning and artificial Intelligence (AI) concepts, and how to interpret complex data relationships. You will learn how to program in Python and see how the most advanced machine learning algorithms are used in products and services.

What are the most important concepts and theories that drive AI technology? This course will cover core principles like ML categories (such supervised and unsupervised learning), common regression techniques and how machines behave and learn.

It is more art than science to effectively deploy machine learning models. This course will help you bridge the gap between IT & data science when putting a great model into production.

Once ML models have been deployed, you can use Python and Azure notebooks to gather insights. This course will teach you how to use Python and Notebooks to gather output data, requests, failure rates, and other information.