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Microsoft Azure + AI Conference

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Develops foundational skills in AI and ML, crucial for budding programmers and data enthusiasts
Equip learners to comprehend and deploy ML models spanning pre-built to custom-built
Taught by industry experts in AI and ML, Kyle Bunting, ensuring up-to-date insights
Imparts knowledge relevant to modern technological solutions, bridging theory and practice

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Activities

Coming soon We're preparing activities for Deploying and Using ML Models across the AI Spectrum. These are activities you can do either before, during, or after a course.

Career center

Learners who complete Deploying and Using ML Models across the AI Spectrum will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
As a Machine Learning Engineer, you will design, build, and maintain machine learning models. You will need a strong understanding of AI and ML, as well as experience deploying and using models in applications. This course can provide you with the skills and knowledge you need to be successful in this role.
Data Scientist
As a Data Scientist, you will research, gather, and analyze data to find insights and support decision-making. This course can help you build a foundation in using AI and ML models and learn how to deploy and use those models in applications. This knowledge will be invaluable in your role as you work with data and develop models to solve business problems.
Data Analyst
As a Data Analyst, you will use data to solve business problems. You will need to be able to gather, clean, and analyze data, as well as communicate your findings to stakeholders. This course can help you build a foundation in using AI and ML models, which can be used to automate tasks and improve the accuracy of your analysis.
Business Analyst
As a Business Analyst, you will work with stakeholders to define and document business requirements. You will need to be able to understand the business and its goals, as well as communicate effectively with stakeholders. This course can help you build a foundation in using AI and ML models, which can be used to automate tasks and improve the efficiency of your work.
Software Engineer
As a Software Engineer, you will design, develop, and maintain software applications. You will need to be able to understand the requirements of the application, as well as the technologies used to develop it. This course can help you build a foundation in using AI and ML models, which can be used to improve the performance and functionality of your applications.
Product Manager
As a Product Manager, you will be responsible for the development and launch of new products. You will need to be able to understand the market, as well as the needs of customers. This course can help you build a foundation in using AI and ML models, which can be used to identify customer needs and improve the quality of your products.
Marketing Manager
As a Marketing Manager, you will be responsible for developing and executing marketing campaigns. You will need to be able to understand the target audience, as well as the channels used to reach them. This course can help you build a foundation in using AI and ML models, which can be used to personalize marketing campaigns and improve their effectiveness.
Sales Manager
As a Sales Manager, you will be responsible for leading and motivating a sales team. You will need to be able to understand the sales process, as well as the needs of customers. This course can help you build a foundation in using AI and ML models, which can be used to identify sales opportunities and improve the efficiency of your team.
Customer Success Manager
As a Customer Success Manager, you will be responsible for ensuring the satisfaction of customers. You will need to be able to understand the needs of customers, as well as the products and services offered by your company. This course can help you build a foundation in using AI and ML models, which can be used to identify customer needs and improve the quality of your products.
Operations Manager
As an Operations Manager, you will be responsible for the day-to-day operations of a company. You will need to be able to understand the business and its goals, as well as the processes used to achieve those goals. This course can help you build a foundation in using AI and ML models, which can be used to automate tasks and improve the efficiency of your operations.
Project Manager
As a Project Manager, you will be responsible for planning, executing, and closing projects. You will need to be able to understand the project requirements, as well as the resources needed to complete the project. This course can help you build a foundation in using AI and ML models, which can be used to track project progress and identify risks.
Financial Analyst
As a Financial Analyst, you will be responsible for analyzing financial data and making recommendations. You will need to be able to understand financial statements, as well as the economic factors that affect businesses. This course may be useful for you in understanding financial trends and making more informed decisions.
Investment Banker
As an Investment Banker, you will be responsible for advising companies on mergers, acquisitions, and other financial transactions. You will need to be able to understand the financial markets, as well as the legal and regulatory environment. This course may be useful for you in understanding financial modeling and valuation techniques.
Management Consultant
As a Management Consultant, you will be responsible for advising companies on business strategy and operations. You will need to be able to understand the business and its goals, as well as the processes used to achieve those goals. This course may be useful for you in understanding business analysis and problem-solving techniques.
Technology Consultant
As a Technology Consultant, you will be responsible for advising companies on the use of technology. You will need to be able to understand the business and its goals, as well as the technology solutions that can be used to meet those goals. This course may be useful for you in understanding emerging technologies and their business applications.

Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Deploying and Using ML Models across the AI Spectrum.
Is the definitive reference on deep learning. It covers the latest advances in deep learning and provides a comprehensive overview of the field. It must-read for anyone who wants to learn about deep learning.
Comprehensive guide to machine learning with Python. It covers a wide range of topics, from data wrangling to model evaluation. It also includes several case studies that show how machine learning can be used to solve real-world problems.
Provides a comprehensive overview of machine learning with PyTorch. It covers a wide range of topics, from data wrangling to model evaluation. It great resource for anyone who wants to learn about machine learning in PyTorch.
Comprehensive guide to statistical learning. It covers a wide range of topics, from linear regression to support vector machines. It classic textbook that is used by many universities.
Provides a comprehensive overview of machine learning with TensorFlow. It covers a wide range of topics, from data wrangling to model evaluation. It great resource for anyone who wants to learn about machine learning in TensorFlow.
Is an excellent introduction to machine learning. It covers the basics of supervised and unsupervised learning algorithms, as well as deep learning. It also provides some practical examples of how machine learning can be used in the real world.
Provides a practical introduction to machine learning for hackers. It covers a wide range of topics, from data wrangling to model evaluation. It great resource for anyone who wants to learn about machine learning without the math.
Provides a practical introduction to machine learning for business. It covers a wide range of topics, from data wrangling to model evaluation. It great resource for anyone who wants to learn about how machine learning can be used to improve business.
Provides a probabilistic foundation for machine learning. It covers topics such as Bayesian inference, graphical models, and reinforcement learning. It more advanced book that is suitable for students with a strong background in mathematics.
Provides a mathematical foundation for machine learning. It covers topics such as linear algebra, calculus, and probability. It great resource for anyone who wants to learn about the mathematical underpinnings of machine learning.
Provides a practical introduction to machine learning with Python for beginners. It covers a wide range of topics, from data wrangling to model evaluation. It great resource for anyone who wants to learn about machine learning in Python.
Provides a comprehensive overview of machine learning for dummies. It covers a wide range of topics, from data wrangling to model evaluation. It great resource for anyone who wants to learn about machine learning without the math.

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