2585 Courses delivered On Demand

Be enthralled in a full guide to building a game environment in UE5, from creating a landscape to making water flow through your mountains, and learn the best way to place environmental details with this course for beginners. We will go over the entire Quixel library and add realistic elements using the Niagara particle system to build our 3D environments.

With this 2-in-1 course, you will get access to AWS Technical Essentials and AWS Certified Solutions Architect - Associate certification exam content.

This course is designed to demonstrate and help you learn the core concepts of working with jQuery. jQuery can help you develop web projects more quickly. jQuery makes creating dynamic and interactive web content easy! Learn the fundamentals of jQuery and find out why it's so amazing to work with. You can do so many great things with jQuery.

This course is a comprehensive guide to the Blazor framework and covers everything from basic features to advanced concepts, including data binding, routing, and lifecycle methods. This is a basic course to start with and requires no prior knowledge of Blazor with some knowledge of C# or any other high-level programming language skills.

Using Blueprints in UE5, you can learn game development without coding. This beginner-friendly course will teach you how to use Unreal Engine's visual coding system. There is no prior experience required, and each lesson will gradually increase your knowledge.

Get Agile certified and learn about the key and most important concepts and tools for Agile project management (Scrum)

In this course, we will process massive streams of real-time data using Spark Streaming and create Spark applications using the Scala programming language (v2.12). We will also get our hands-on with some real live Twitter data, simulated streams of Apache access logs, and even data used to train machine learning models.

In this self-paced course, you will learn how to use TensorFlow 2 to build convolutional neural networks (CNNs). You will learn how to apply CNNs to several practical image recognition datasets and learn about techniques that help improve performance, such as batch normalization, data augmentation, and transfer learning.

In this self-paced course, you will learn how to use TensorFlow 2 to build recurrent neural networks (RNNs). You will learn about sequence data, forecasting, Elman Unit, GRU, and LSTM. You will also learn how to work with image classification and how to get stock return predictions using LSTMs. We will also cover Natural Language Processing (NLP) and learn about text preprocessing and classification.

In this self-paced course, you will learn how to use TensorFlow 2 to build deep neural networks. You will learn the basics of machine learning, classification, and regression. We will also discuss the connection between artificial and biological neural networks and how that inspires our thinking in deep learning.