In this course, you’ll learn the fundamentals of the Python programming language, along with programming best practices. You’ll learn to represent and store data using Python data types and variables, and use conditionals and loops to control the flow of your programs. You’ll harness the power of complex data structures like lists, sets, dictionaries, and tuples to store collections of related data. You’ll define and document your own custom functions, write scripts, and handle errors. Lastly, you’ll learn to find and use modules in the Python Standard Library and other third-party libraries.
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In this program, students will enhance their skills by building and deploying sophisticated machine learning solutions using popular open-source tools and frameworks, and gain practical experience running complex machine learning tasks using the built-in Azure labs accessible inside the Udacity classroom.
Learn advanced machine learning techniques and algorithms and how to package and deploy your models to a production environment. Gain practical experience using Amazon SageMaker to deploy trained models to a web application and evaluate the performance of your models. A/B test models and learn how to update the models as you gather more data, an important skill in industry.
You’ll learn how to evaluate the business value of an AI product. You’ll start by building familiarity and fluency with common AI concepts. You’ll then learn how to scope and build a data set, train a model, and evaluate its business impact. Finally, you’ll learn how to ensure a product is successful by focusing on scalability, potential biases, and compliance. Along the way, you’ll review case studies and examples to help you focus on how to define metrics to measure the business value for a proposed product.