In this one-hour, project-based course, you'll learn some basic elements of Unity's Cinemachine, an extremely powerful camera-control system. You'll learn how to set up different types of cameras and configure them for a variety of visual results. You'll also learn how to adjust the on-screen framing of the virtual camera to maintain a central view of the target subject. The guided project will introduce you to the following Unity concepts: - Cinemachine This series also makes use of the robot-themed Unity project created in Create Simple Enemy Behaviour with C# in Unity (Introduction to AI). If you would like to understand how the robots in this Cinemachine project have been made to patrol and chase the player, the AI project is recommended. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

By the end of this project, you will create two independent and replicable local development environments for two servers and make them communicate with each other, avoiding terminal hell, issues with dependencies, and automating the process of setting up a fresh setup of your projects. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

In this project we are going to learn about lambda expressions and it's application in python. We are going to start with what is Lambda expression and how we can define it, comparing lambda functions with regular functions in python and at the end we will learn how to use lambda functions for data manipulation and exploration in pandas. this guided-project is completely beginner friendly. you only need to have basic knowledge of python programming and some experience coding in Jupyter notebook environment.

By the end of this project, you’ll be able to create and edit smart objects in Adobe Photoshop. You’ll use smart objects to apply nondestructive edits and swap assets inside files. During this project, you’ll get used to navigating some important Photoshop tools and practice creating and importing smart objects, and you’ll learn what makes them smart in the first place. Then you’ll apply nondestructive edits and work with different kinds of smart objects. Once you’re finished, you’ll learn how to export your work. By the end of the project, you’ll be able to use smart objects to make smart and speedy edits to images.

In this course, we look at Cloud, DevOps and the Linux operating system. The course material is a good for anyone preparing for the Linux Foundation Certified IT Associate (LFCA) exam or just interested in learning more about Linux. This course is the fourth course in a series that aims to prepare you for working as an information technology professional.

This class will teach you the fundamentals of augmented reality (AR), and how to build an AR experience using ARCore. Through the four week course, you'll learn: - How to identify different types of AR experiences - Tools and platforms used in the AR landscape - What makes AR feel "real" - Popular use cases for AR - How to create an AR use flow - How AR experiences work - Tools like Google Poly and Unity to build AR experiences - Next steps to start building an AR experience using ARCore and other tools This course will break down complex AR concepts to make them easy to understand, while also sharing expert tips and knowledge from Daydream's ARCore team. The course is great for beginners who are just getting started with AR or ARCore.

In this hands-on project, we will build and train a simple artificial neural network model to detect spam/fake Instagram accounts. Fake and spam accounts are a major problem in social media. Many social media influencers use fake Instagram accounts to create an illusion of having so many social media followers. Fake accounts can be used to impersonate or catfish other people and be used to sell fake services/products. By the end of this project, you will be able to: - Understand the applications of Artificial Intelligence and Machine Learning techniques in the banking industry - Understand the theory and intuition behind Deep Neural Networks - Import key Python libraries, dataset, and perform Exploratory Data Analysis. - Perform data visualization using Seaborn. - Standardize the data and split them into train and test datasets. - Build a deep learning model using Keras with Tensorflow 2.0 as a back-end. - Assess the performance of the model and ensure its generalization using various Key Performance Indicators (KPIs). Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

By the end of this project, you will be able to leverage Gantt charts to plan, schedule, and graphically represent the progression of a project plan over time so that stakeholders and sponsors can quickly understand the status, dependencies, and future requirements. To do this, you will gain hands-on experience applying, planning and scheduling a project by creating a Gantt chart in the Miro online visual collaboration platform for teamwork. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Adobe Portfolio offers you a range of options to showcase your work. You can create a multi-page site or a one page site. The program makes it user friendly so that if you do not know HTML or CSS, you can still present your work online. Adobe Portfolio allows you to develop a portfolio that speaks to your brand and style. Adobe Portfolio supplies you with resources to develop your bio, how to promote yourself online and much more. In this project you will get your portfolio developed to share.

In this one-hour project, you will learn how to use Microsoft Azure Cloud Platform and its Kubernetes Service to deploy a Web Application in a high availability environment, using the power of containers and Kubernetes in a real-world use case. Once you're done with this project, you will be able to clone a project, create a docker container image and deploy this container like a Kubernetes POD using the Azure Kubernetes Services with just a few steps.