683 API courses delivered Online

Learn new Android APIs such as RoomDatabase, ML Kit for face recognition, Cloud Firestore, Firebase, Maps, and the Android Studio IDE (integrated development environment)

Leverage pytest's fast, scalable, and professional-grade framework design to build and run automated test suites like a pro

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Learn to make interactive apps using Swift 4.2 and Xcode 10 and have your own applications in the App Store in just 10 days

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Duration 3 Days 18 CPD hours This course is intended for The primary audience for this course is as follows: IT Staff and Managers Network and systems personnel and engineers Small to mid-sized organizations that require fundamental knowledge on networking terms/concepts and configuration guidance for Meraki equipment. This also includes organizations looking to implement remote sites, provide a guest wireless solution, and collect user analytics. Overview Following completion of this course, students will understand, Install, Configure, Monitor, and Troubleshoot the following: Navigate and Configure the dashboard Add MX/MS devices to the Dashboard Understand and Configure Configuration Templates Understand and Configure Group Policies Manage/Configure/Integrate Users and Radius Policies Configure, Monitor, and Troubleshoot MS Switches Troubleshoot devices and Connectivity This 3-day Cisco course provide students with the skills to configure, optimize, and troubleshoot a Cisco Meraki solution. Students will learn how to install and optimize Meraki MS Switches. Students will also learn how to configure the Meraki Dashboard. Student will troubleshoot and configure the Meraki environment and learn how to diagnose and resolve user and Network issues that may arise. Introduction to Meraki The Meraki Mission Cisco Meraki: Bringing the Cloud to Enterprise Networks Cloud-Managed Networking Architecture Benefits of a Cloud-Based Solution The Meraki Full Stack: New and Unique Value Proposition Meraki Deployment ? How it works Why Customers Choose Meraki Meraki MS Switches Overview Meraki API Overview Meraki Licensing Enterprise Support Cisco Meraki Documentation Cloud Management with the Meraki Dashboard The Meraki Dashboard Dashboard: Organizational Structure Out-of-band Cloud Management Loss of Connectivity to the Cisco Meraki Cloud Meraki Dashboard Logins Create Dashboard Accounts and Organization MSP Logins - Manage Multiple Organizations Modify an Organization View Organizations Health Meraki Dashboard Best Practices Dashboard Search Meraki Help Organizational Wide Settings Configure Monitor Create and Manage Configuration Templates Network-Wide Settings Configure Meraki Switching MS Switch Platforms and Features MS Feature: Multi-gigabit Ethernet Cisco Meraki MS Access Switches Cisco Meraki MS Aggregation Switches Using Tags to search, monitor and configure Meraki Switches Meraki Switch Configuration Port Configuration Meraki Switch Monitoring Troubleshooting Tools Managing Firmware Upgrades

Overview This comprehensive course on Machine Learning for Predictive Maps in Python and Leaflet will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Machine Learning for Predictive Maps in Python and Leaflet comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Machine Learning for Predictive Maps in Python and Leaflet. It is available to all students, of all academic backgrounds. Requirements Our Machine Learning for Predictive Maps in Python and Leaflet is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 9 sections • 33 lectures • 05:59:00 total length •Introduction: 00:10:00 •Python Installation: 00:04:00 •Creating a Python Virtual Environment: 00:07:00 •Installing Django: 00:09:00 •Installing Visual Studio Code IDE: 00:06:00 •Installing PostgreSQL Database Server Part 1: 00:03:00 •Installing PostgreSQL Database Server Part 2: 00:09:00 •Adding the settings.py Code: 00:07:00 •Creating a Django Model: 00:10:00 •Adding the admin.py Code: 00:21:00 •Creating Template Files: 00:10:00 •Creating Django Views: 00:10:00 •Creating URL Patterns for the REST API: 00:09:00 •Adding the index.html code: 00:04:00 •Adding the layout.html code: 00:19:00 •Creating our First Map: 00:10:00 •Adding Markers: 00:16:00 •Installing Jupyter Notebook: 00:07:00 •Data Pre-processing: 00:31:00 •Model Selection: 00:20:00 •Model Evaluation and Building a Prediction Dataset: 00:11:00 •Creating a Django Model: 00:04:00 •Embedding the Machine Learning Pipeline in the Application: 00:42:00 •Creating a URL Endpoint for our Prediction Dataset: 00:06:00 •Creating Multiple Basemaps: 00:09:00 •Creating the Marker Layer Group: 00:10:00 •Creating the Point Layer Group: 00:12:00 •Creating the Predicted Point Layer Group: 00:07:00 •Creating the Predicted High Risk Point Layer Group: 00:12:00 •Creating the Legend: 00:09:00 •Creating the Prediction Score Legend: 00:15:00 •Resource: 00:00:00 •Assignment - Machine Learning for Predictive Maps in Python and Leaflet: 00:00:00

Learn how to program using Apache Groovy.

Delivering an interactive web experience can be challenging but not impossible. This course will provide you with the core fundamentals of front-end web programming and how to understand the DOM (Document Object Model). After that, we will take a deep dive into advanced DOM concepts, which include events, hierarchy, and bubbling.

Duration 2 Days 12 CPD hours This course is intended for This course is intended for software testers, architects, engineers, or other related roles, who wish to apply AI to software testing practices within their enterprise. While there are no specific pre-requisites for this course, it would be helpful is the attendee has familiarity with basic scripting (Python preferred) and be comfortable with working from the command line (for courses that add the optional hands-on labs). Attendees without basic scripting skills can follow along with the hands-on labs or demos. Overview This course introduces AI and related technologies from a practical applied software testing perspective. Through engaging lecture and demonstrations presented by our expert facilitator, students will explore: Exploring AI Introduction to Machine Learning Introduction to Deep Learning Introduction to Data Science Artificial Intelligence (AI) in Software Testing Implementing AI in Test Automation Innovative AI Test Automation Tools for the Future Implementing AI in Software Testing / AI in Test Automation is an introductory-level course for attendees new to AI, Machine Learning or Deep Learning who wish to automate software testing tasks leveraging AI. The course explores the essentials of AI, ML and DL and how the integrate into IT business operations and initiatives. Then the course moves to specifics about the skills, techniques and tools used to apply AI to common software testing requirements. Exploring AI AI-Initiatives The Priority: Excellence AI- Intelligence Types The Machine Learning Types The Quality Learning Initiative The Inception in Academics AI - Importance & Applications The Re-visit Learning Re-visited via AI Teaching in the world of AI Exploring AI for Self-Development AI In Academics Beyond Academics Introduction to Machine Learning What is Machine Learning? Why Machine Learning? Examples - Algorithms behind Machine Learning Introduction to Deep Learning What is Deep Learning? Why Deep Learning? Example - Deep Learning Vs Machine Learning Introduction to Data Science What is Data Science? Why Data Science? Examples - Use Cases of Data Science Artificial Intelligence (AI) in Software Testing What is AI in Software Testing? The Role of AI Testing Why do we Need AI in Software Testing? Pros and Cons of AI in Software Testing Applications of AI in Software Testing Is it time for Testers or QA Teams to worry about AI? Automated Testing with Artificial Intelligence Implementing AI in Test Automation Training the AI Bots Challenges with AI-powered Applications Examples - Real World use cases using Artificial Intelligence Demo - Facial Emotion Detection Using Artificial Intelligence Demo - Text Analysis API Using Artificial Intelligence Demo - EYE SPY Mobile App Using Artificial Intelligence Innovative AI Test Automation Tools for the Future Tools used for Implementing AI in Automation Testing What is NEXT? AI Test Automation Demo using Testim