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Data Analyst (Data Analytics) - CPD Certified Have you ever wondered how companies get insights from massive volumes of data to stay competitive and make wise decisions? If so, then participate in our exclusive Data Analytics Course. This Data Analytics Course describes the fundamentals of data, statistics, and an introduction to data analytics. How to get data and where to find it is explained in the Data Analytics Course. Moreover, this Data Analytics Course covers data cleansing, preprocessing, and exploratory data analysis (EDA). Additionally, the Data Analytics Course provides an introduction to Python and Excel for data analytics. This thorough Data Analytics Course includes lessons on data wrangling with Pandas (python) and data visualisation using Matplotlib and Seaborn (python). Enrol in our Data Analytics Course to study the fundamentals of statistical analysis and machine learning. Special Offers of this Data Analyst (Data Analytics) Course Data Analyst (Data Analytics) Course includes a FREE PDF Certificate. Lifetime access to this Data Analyst (Data Analytics) Course Instant access to this Data Analyst (Data Analytics) Course Get FREE Tutor Support from Monday to Friday in this Data Analyst (Data Analytics) Course Courses are included in this Data Analyst (Data Analytics) Course Course 01: Cyber Security Course 02: GDPR Course 03: Business Administration [ Note: Free PDF certificate as soon as completing the Data Analyst (Data Analytics) Course] Course Curriculum of Data Analyst (Data Analytics) - CPD Certified Module 1: Introduction to Data Analytics Module 2: Basics of Data and Statistics Module 3: Data Collection and Sources Module 4: Data Cleaning and Preprocessing Module 5: Exploratory Data Analysis (EDA) Module 6: Introduction to Excel for Data Analytics Module 7: Introduction to Python for Data Analytics Module 8: Data Wrangling with Pandas (Python) Module 9: Data visualisation with Matplotlib and Seaborn (Python) Module 10: Introduction to Basic Statistical Analysis Module 11: Introduction to Machine Learning Module 12: Capstone Project - Exploratory Data Analysis Assessment Method After completing each module of the Data Analyst (Data Analytics) Course, you will find automated MCQ quizzes. To unlock the next module, you need to complete the quiz task and get at least 60% marks. Certification After completing the MCQ/Assignment assessment for this Data Analyst (Data Analytics) course, you will be entitled to a Certificate of Completion from Training Tale. The certificate is in PDF format, which is completely free to download. A printed version is also available upon request. It will also be sent to you through a courier for £13.99. Who is this course for? Data Analyst (Data Analytics) - CPD Certified For business professionals, entrepreneurs, or anybody else looking to have a thorough grasp of data analysis in a commercial setting, this Data Analytics Course is ideal. Requirements There are no specific requirements for Data Analyst (Data Analytics) Course because it does not require any advanced knowledge or skills. Career path Data Analyst (Data Analytics) - CPD Certified This Data Analytics Course will assist you in obtaining positions as a business analyst, marketing analyst, data analyst, and in related fields. Certificates Certificate of completion Digital certificate - Included

Are you ready to embark on an enlightening journey of wisdom with the Data Analytics & Database Development Using SQL bundle, and pave your way to an enriched personal and professional future? If so, then Step into a world of knowledge with our bundle - Data Analytics & Database Development Using SQL. Delve into eight immersive CPD Accredited courses, each a simple course: Course 1: Data Analytics Course 2: SQL Database Basics for Everyone Course 3: SQL for Data Science, Data Analytics and Data Visualization Course 4: Microsoft Access Databases Forms and Reports Course 5: Microsoft SQL Server Development for Everyone! Course 6: Python Programming from Scratch with My SQL Database Course 7: Google Data Studio: Data Analytics Course 8: Data Analysis and Forecasting in Excel Traverse the vast landscapes of theory, unlocking new dimensions of understanding at every turn. Let the Data Analytics & Database Development Using SQL bundle illuminate your path to wisdom. The Data Analytics & Database Development Using SQL bundle offers a comprehensive exploration into a rich tapestry of vast knowledge across five carefully curated courses. The journey is designed to enhance your understanding and critical thinking skills. Each course within the bundle provides a deep-dive into complex theories, principles, and frameworks, allowing you to delve into the nuances of the subject matter at your own pace. In the framework of the Data Analytics & Database Development Using SQL package, you are bestowed with complimentary PDF certificates for all the courses included in this bundle, all without any additional charge. Adorn yourself with the Data Analytics & Database Development Using SQL bundle, empowering you to traverse your career trajectory or personal growth journey with self-assurance. Register today and ignite the spark of your professional advancement! So, don't wait further and join the Data Analytics & Database Development Using SQL community today and let your voyage of discovery begin! Learning Outcomes: Upon completion of the Data Analytics & Database Development Using SQL Bundle, you will be able to: Attain a holistic understanding in the designated areas of study with the Data Analytics & Database Development Using SQL bundle. Establish robust bases across each course nestled within the Data Analytics & Database Development Using SQL bundle. Decipher intricate concepts through the articulate content of the Data Analytics & Database Development Using SQL bundle. Amplify your prowess in interpreting, scrutinising, and implementing theories. Procure the capacity to engage with the course material on an intellectual and profound level. Become proficient in the art of problem-solving across various disciplines. Stepping into the Data Analytics & Database Development Using SQL bundle is akin to entering a world overflowing with deep theoretical wisdom. Each course within this distinctive bundle is an individual journey, meticulously crafted to untangle the complex web of theories, principles, and frameworks. Learners are inspired to explore, question, and absorb, thus enhancing their understanding and honing their critical thinking skills. Each course invites a personal and profoundly enlightening interaction with knowledge. The Data Analytics & Database Development Using SQL bundle shines in its capacity to cater to a wide range of learning needs and lifestyles. It gives learners the freedom to learn at their own pace, forging a unique path of discovery. More than just an educational journey, the Data Analytics & Database Development Using SQL bundle fosters personal growth, enabling learners to skillfully navigate the complexities of the world. The Data Analytics & Database Development Using SQL bundle also illuminates the route to a rewarding career. The theoretical insight acquired through this bundle forms a strong foundation for various career opportunities, from academia and research to consultancy and programme management. The profound understanding fostered by the Data Analytics & Database Development Using SQL bundle allows learners to make meaningful contributions to their chosen fields. Embark on the Data Analytics & Database Development Using SQL journey and let knowledge guide you towards a brighter future. CPD 90 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Individuals keen on deepening their firm understanding in the respective fields. Students pursuing higher education looking for comprehensive theory modules. Professionals seeking to refresh or enhance their knowledge. Anyone with a thirst for knowledge and a passion for continuous learning. Requirements Without any formal requirements, you can delightfully enrol in this Data Analytics & Database Development Using SQL Bundle. Career path Armed with the Data Analytics & Database Development Using SQL bundle, your professional journey can reach new heights. The comprehensive theoretical knowledge from this bundle can unlock diverse career opportunities across several fields. Whether it's academic research, consultancy, or programme management, the Data Analytics & Database Development Using SQL bundle lays a solid groundwork. Certificates CPD Certificate Of Completion Digital certificate - Included 8 Digital Certificates Are Included With This Bundle CPD Quality Standard Hardcopy Certificate (FREE UK Delivery) Hard copy certificate - £9.99 Hardcopy Transcript: £9.99

Step confidently into a rewarding UK career with our transformative "Python Bootcamp: JavaScript, HTML & CSS Coding" bundle. This bundle covers everything from honing your Python proficiency to crafting interactive web designs with HTML and CSS and developing dynamic applications using JavaScript. Uncover the secrets of Python's application in data science, machine learning, and neural networks. Establish a strong foundation in C# coding and exploring networking, GUI development, XML handling, and more. Delve into eight immersive CPD Accredited courses, each a standalone course: Course 01: The Complete Python 3 Course: Beginner to Advanced! Course 02: JavaScript for Everyone Course 03: HTML and CSS Coding: Beginner to Advanced Course 04: Basic C# Coding Course 05: Python Data Science with Numpy, Pandas and Matplotlib Course 06: Deep Learning & Neural Networks Python - Keras Course 07: Complete Python Machine Learning & Data Science Fundamentals Course 08: Python Programming Bible | Networking, GUI, Email, XML, CGI Our comprehensive Python Bootcamp: JavaScript, HTML & CSS Coding bundle ensure you're well-prepared for diverse tech challenges. Elevate your UK career prospects with hands-on learning and real-world applications. Embrace the "Python Bootcamp: JavaScript, HTML & CSS Coding" bundle for an all-encompassing skill set bound to make you a standout in the dynamic UK job landscape. Learning Outcomes Progress from beginner to advanced Python proficiency. Craft dynamic websites using HTML and CSS. Develop user-friendly web applications with JavaScript. Analyze data using Numpy, Pandas, and Matplotlib. Explore neural networks with Python's Keras. Gain practical machine learning expertise. Unleash your potential with our comprehensive Python Bootcamp: JavaScript, HTML & CSS Coding bundle that promises to transform your career trajectory. In the rapidly evolving tech landscape, Python proficiency stands as a cornerstone of success. From web development to data analysis and machine learning, Python is the language that opens doors to countless opportunities. Our Python Bootcamp: JavaScript, HTML & CSS Coding bundle ensures you learn and master Python, securing your place at the forefront of innovation. Harness the expertise of excellent instructors who unravel the complexities of Python in a relatable and engaging manner. Dive into dynamic web design, crafting seamless interfaces with HTML and CSS, and building interactive web applications using JavaScript.Take the plunge into deep learning, understanding the intricacies of neural networks through Python's Keras library. As you progress, embrace the fundamental principles of machine learning, propelling your career to new heights. The time to seize the moment is now. The "Python Bootcamp: JavaScript, HTML & CSS Coding" bundle equips you with indispensable skills, empowering you to stand out in a competitive job market. Whether a newcomer or a seasoned professional, this Python Bootcamp: JavaScript, HTML & CSS Coding bundle ensures you're ready to conquer challenges and grasp opportunities. Embrace the power of Python today, and let it shape a future of endless possibilities. CPD 80 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Beginners to advanced learners. HTML, CSS, and JavaScript skills. Master Python programming. Numpy, Pandas, and data science. Diverse tech skill acquisition. Deep learning and machine learning Requirements Without any formal requirements, you can delightfully enrol in this course. Career path Web Developer: £25,000 - £50,000 Python Programmer: £30,000 - £60,000 Data Analyst: £25,000 - £45,000 Front-End Developer: £25,000 - £50,000 UI/UX Designer: £30,000 - £50,000 Machine Learning Engineer: £40,000 - £70,000 Full-Stack Developer: £35,000 - £60,000 Certificates CPD Certificate Of Completion Digital certificate - Included 8 Digital Certificates Are Included With This Bundle CPD Quality Standard Hardcopy Certificate (FREE UK Delivery) Hard copy certificate - £9.99 Hardcopy Transcript - £9.99

Duration 3 Days 18 CPD hours Overview In this course you?ll learn how to: Containerize and deploy a new Python script Configure the deployment with ConfigMaps, Secrets and SecurityContexts Understand multi-container pod design Configure probes for pod health Update and roll back an application Implement services and NetworkPolicies Use PersistentVolumeClaims for state persistence And more In this vendor agnostic course, you will use Python to build, monitor and troubleshoot scalable applications in Kubernetes. Introduction Objectives Who You Are The Linux Foundation Linux Foundation Training Preparing Your System Course Registration Labs Kubernetes Architecture What Is Kubernetes? Components of Kubernetes Challenges The Borg Heritage Kubernetes Architecture Terminology Master Node Minion (Worker) Nodes Pods Services Controllers Single IP per Pod Networking Setup CNI Network Configuration File Pod-to-Pod Communication Cloud Native Computing Foundation Resource Recommendations Labs Build Container Options Containerizing an Application Hosting a Local Repository Creating a Deployment Running Commands in a Container Multi-Container Pod readinessProbe livenessProbe Testing Labs Design Traditional Applications: Considerations Decoupled Resources Transience Flexible Framework Managing Resource Usage Multi-Container Pods Sidecar Container Adapter Container Ambassador Points to Ponder Labs Deployment Configuration Volumes Overview Introducing Volumes Volume Spec Volume Types Shared Volume Example Persistent Volumes and Claims Persistent Volume Persistent Volume Claim Dynamic Provisioning Secrets Using Secrets via Environment Variables Mounting Secrets as Volumes Portable Data with ConfigMaps Using ConfigMaps Deployment Configuration Status Scaling and Rolling Updates Deployment Rollbacks Jobs Labs Security Security Overview Accessing the API Authentication Authorization ABAC RBAC RBAC Process Overview Admission Controller Security Contexts Pod Security Policies Network Security Policies Network Security Policy Example Default Policy Example Labs Exposing Applications Service Types Services Diagram Service Update Pattern Accessing an Application with a Service Service without a Selector ClusterIP NodePort LoadBalancer ExternalName Ingress Resource Ingress Controller Labs Troubleshooting Troubleshotting Overview Basic Troubleshooting Steps Ongoing (Constant) Change Basic Troubleshooting Flow: Pods Basic Troubleshooting Flow: Node and Security Basic Troubleshooting Flow: Agents Monitoring Logging Tools Monitoring Applications System and Agent Logs Conformance Testing More Resource Labs Additional course details: Nexus Humans Kubernetes for App Developers training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Kubernetes for App Developers course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Overview This comprehensive course on Complete iOS 11 and Swift 4 will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Complete iOS 11 and Swift 4 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 Complete iOS 11 and Swift 4. It is available to all students, of all academic backgrounds. Requirements Our Complete iOS 11 and Swift 4 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 13 sections • 177 lectures • 19:08:00 total length •iOS 11 Course Overview: 00:11:00 •Install Xcode 9: 00:07:00 •Xcode 9 Beta 4 Update: 00:09:00 •App: Hustle - Your first iOS 11 App: 00:22:00 •Variables, operators, and how computers work: 00:17:00 •Strings in Swift: 00:15:00 •Working with numbers in Swift: 00:20:00 •Swift Functions: 00:23:00 •Booleans: 00:21:00 •Constants: 00:10:00 •Array Data Structure in Swift: 00:13:00 •Swift Loops: 00:19:00 •Dictionary Data Structure in Swift: 00:19:00 •Object Oriented Programming in Swift: 00:12:00 •Inheritance: 00:08:00 •Polymorphism: 00:08:00 •Optionals: 00:21:00 •Enumerations: 00:20:00 •Extensions: Part 1: 00:15:00 •Extensions: Part 2: 00:21:00 •Intro to Protocols, Delegates - Numbers Example: 00:13:00 •Intro to Protocols, Delegates Part 2 - Question Generator: 00:18:00 •Protocols, Delegates - Building Color Magic App UI: 00:17:00 •Protocols, Delegates - Using the Delegate Method in Color Magic App: 00:16:00 •Protocols, Delegates - Using Mutating Functions in Types: 00:18:00 •Git and Version Control - The Fun Way!: 00:12:00 •Terminal Basics - Changing Directories: 00:06:00 •Terminal Basics - Creating Directories and Files: 00:05:00 •Terminal Basics - Copying and Renaming Files: 00:09:00 •Terminal Basics - Deleting Files and Directories: 00:06:00 •Git Basics: 00:17:00 •Setting up Github: 00:05:00 •Working with Local and Remote Repositories: 00:11:00 •Handling Git Merge Conflicts: 00:17:00 •App: Swoosh 01 - Creating the Welcome Screen: 00:25:00 •App: Swoosh 02 - Working with Frames: 00:16:00 •App: Swoosh 03 - Intro to Auto Layout: 00:27:00 •App: Swoosh 04 - Working with Stack Views: 00:27:00 •App: Swoosh 05 - Intro to Segues (Changing Screens): 00:10:00 •App: Swoosh 06 - Refactoring in Xcode 9: 00:10:00 •App: Swoosh 07 - Debugging: setValue forUndefinedKey: 00:04:00 •App: Swoosh 08 - Programmatic Segues: 00:09:00 •App: Swoosh 09 - IBActions (Handling Events) and Data Models: 00:16:00 •App: Swoosh 10 - Passing Data Between View Controllers: 00:12:00 •App: Dev Profile 01 - Auto layout for iPhones: 00:22:00 •App: Dev Profile 02 - Auto layout for iPads (Size Classes): 00:20:00 •App: Window Shopper 01 - Custom Text Fields: 00:18:00 •App: Window Shopper 02 - Input Accessory Views: 00:15:00 •App: Window Shopper 03 - Unit Testing our Data: 00:17:00 •App: Window Shopper 04 - Calculation Algorithm: 00:13:00 •App: Window Shopper 05 - Custom Drawing with drawRect: 00:12:00 •App: Coder Swag 01 - Project creation: 00:23:00 •App: Coder Swag 02 - Tableviews, Delegate, and Data Source: 00:33:00 •App: Coder Swag 03 - Collection Views (Grid Layouts): 00:13:00 •App: Coder Swag 04 - Working with Data Models: 00:14:00 •App: Coder Swag 05 - Displaying Data in Collection View Cells: 00:20:00 •Intro to Chat App: 00:04:00 •App: Smack - Project Setup: 00:26:00 •App: Smack - SWReveal: 00:20:00 •App: Smack - ChannelVC UI: 00:25:00 •App: Smack - LoginVC UI: 00:22:00 •App: Smack - CreateAccountVC UI: 00:19:00 •App: Smack - Web request and API: 00:09:00 •App: Smack - Hosting API: 00:20:00 •App: Smack - Locally Hosting API: 00:18:00 •App: Smack - Creating a web request in Xcode: 00:28:00 •App: Smack - Registering a User: 00:16:00 •App: Smack - Logging in a user: 00:20:00 •App: Smack - Creating a user: 00:26:00 •App: Smack - Avatar Picker Part 1: 00:19:00 •App: Smack - Avatar Picker Part 2: 00:20:00 •App: Smack - Generate a Avatar BG Color: 00:26:00 •App: Smack - LoggedIn Interface: 00:23:00 •App: Smack - Profile View: 00:25:00 •App: Smack - Logging in users: 00:23:00 •App: Smack - Getting channels: 00:19:00 •App: Smack - Channels TableView: 00:14:00 •App: Smack - Add Channel VC: 00:19:00 •App: Smack - Sockets and Channels: 00:26:00 •App: Smack - Refining Login Flow: 00:19:00 •App: Smack - Fetching Messages: 00:20:00 •App: Smack - Sending First Message: 00:17:00 •App: Smack - Displaying Chat Messages: 00:18:00 •App: Smack - Sockets and Messages: 00:19:00 •App: Smack - Typing Users: 00:22:00 •App: Smack - Unread Channels: 00:18:00 •Where to go from here: 00:08:00 •I'm Back: 00:08:00 •Intro to App: Pixel City: 00:02:00 •Creating Xcode Project: Pixel City: 00:04:00 •Installing Alamofire / AlamofireImage Cocoapods: 00:07:00 •Building MapVC UI /Conforming to MKMapViewDelegate /Setting Delegate of mapView: 00:15:00 •Requesting Location Services in iOS 11 / Centering Map On User Location: 00:18:00 •Adding UITapGestureRecognizer to Drop Custom Pins on MapView: 00:15:00 •Setting a Custom Map Annotation Color: 00:05:00 •Animating Photos View / Programmatically adding spinner and label subviews: 00:20:00 •Adding UILabel for Pull Up View / Adding UICollectionView Programmatically: 00:17:00 •Getting API Key from Flickr / Using Flickr API URL Format: 00:14:00 •Using Alamofire to Download URLS: 00:21:00 •Using Alamofire to Download Images / Cancelling All Sessions: 00:16:00 •Setting Up UICollectionView / Adding Images / Reloading UICollectionView: 00:10:00 •Building PopVC / Presentation PopVC When UICollectionViewCell is Tapped: 00:16:00 •Adding 3D Touch Peek: 00:15:00 •Challenge 1: 00:02:00 •Setting up developer: 00:10:00 •Implementing Google AdMob: 00:19:00 •Fetching a list of Products: 00:15:00 •Starting an in-app Purchase: 00:09:00 •Testing in-app Purchases: 00:18:00 •Restoring in-app Purchases after App Deletion: 00:09:00 •Intro to App: GoalPost: 00:03:00 •Creating Xcode Project / Project Folders: 00:04:00 •Building GoalsVC: 00:14:00 •Building GoalCell: 00:14:00 •What is Core Data?: 00:06:00 •Creating Goal Core Data Entity and Attributes: 00:08:00 •Displaying Static GoalCells in UITableView / Creating GoalType Enum: 00:10:00 •Building CreateGoalVC: 00:15:00 •Creating a UIViewController Extension: 00:11:00 •Creating a UIView / UIButton Extension: 00:19:00 •Building FinishGoalVC / Passing Data from CreateGoalVC: 00:19:00 •Saving Goal Data to Persistent Store: 00:13:00 •Fixing Dismissal of FinishGoalVC: 00:07:00 •Fetching Data from Persistent Store / Filling UITableView with Fetched Data: 00:16:00 •Removing Objects from Persistent Store using UITableView Delete Action: 00:11:00 •Setting Goal Progress for UITableViewCell: 00:15:00 •Challenge 2: 00:01:00 •Intro to App: Breakpoint: 00:03:00 •Creating Xcode Project / Setting Up Project Folders: 00:05:00 •Creating Firebase Project: 00:11:00 •Setting Up DataService / Creating Firebase Database Users: 00:11:00 •Building AuthVC and LoginVC in Interface Builder: 00:18:00 •Creating InsetTextField and ShadowView Subclasses: 00:18:00 •Setting up AuthService: 00:13:00 •Building FeedVC and GroupsVC in Interface Builder: 00:16:00 •Presenting LoginVC from AppDelegate / Allowing Login with Email: 00:22:00 •Building MeVC and Adding to UITabBarController: 00:10:00 •Creating CreatePostVC and Uploading Posts to Firebase: 00:20:00 •Creating UIView Extension for Binding Views to Keyboard: 00:15:00 •Building FeedCell: 00:10:00 •Writing the Message Model and Getting All Feed Messages from Firebase: 00:21:00 •Converting UIDs into Emails and Reversing the Order of a TableView: 00:20:00 •Creating CreateGroupVC and Connecting @IBOutlets/Actions: 00:15:00 •Creating UserCell: 00:16:00 •Searching for Email Accounts to Add to Group: 00:19:00 •Adding Users to Group with didSelectRowAt indexPath: 00:21:00 •Creating Groups and pushing them to Firebase: 00:16:00 •Creating GroupCell: 00:15:00 •Creating Group Model and Getting All Groups from Firebase: 00:19:00 •Building GroupFeedVC: 00:18:00 •Initializing Group Data for a Group and Presenting on GroupFeedVC: 00:16:00 •Downloading All Message for a Group and Animating Upon New Message: 00:24:00 •Creating a UIViewController Extension for Presenting GroupFeedVC: 00:07:00 •Challenge 3: 00:02:00 •Intro to app: 00:02:00 •Intro to CoreML: 00:05:00 •What is machine learning?: 00:08:00 •Creating Xcode 9 project: 00:03:00 •Building UI: 00:18:00 •AVFoundation: 00:18:00 •Tap gestures to take snapshot on item: 00:11:00 •Core ML Xcode 9 Beta 4 Update / Fix Preview Photo Crash: 00:03:00 •Downloading CoreML models: 00:21:00 •Adding UI controls for flash control: 00:07:00 •Training your app to speak what it sees: 00:18:00 •App: RampUp - Intro to ARKit App: 00:02:00 •App: RampUp - Resources: 00:04:00 •App: RampUp - Project creation: 00:11:00 •App: RampUp - SceneKit, 3D models: 00:11:00 •App: RampUp - Ramp picker popover: 00:14:00 •App: RampUp - 3D models in SceneKit for popover: 00:18:00 •App: RampUp - 3D models in SceneKit for popover part 2: 00:12:00 •App: RampUp - Detecting taps on 3D objects: 00:17:00 •App: RampUp - Placing ramps in ARKit: 00:24:00 •App: RampUp - Moving objects in 3D space in augmented reality: 00:20:00 •ARKit - where to go next: 00:04:00 •Assignment - Complete iOS 11 and Swift 4: 00:00:00

Overview of MySql Masterclass Join our MySql Masterclass course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The MySql Masterclass course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The MySql Masterclass course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now! This MySql Masterclass Course will help you to learn: Learn strategies to boost your workplace efficiency. Hone your skills to help you advance your career. Acquire a comprehensive understanding of various topics and tips. Learn in-demand skills that are in high demand among UK employers This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this MySql Masterclass. Enrol today and complete the course to achieve a certificate that can change your career forever. Details Perks of Learning with IOMH One-To-One Support from a Dedicated Tutor Throughout Your Course. Study Online — Whenever and Wherever You Want. Instant Digital/ PDF Certificate. 100% Money Back Guarantee. 12 Months Access. Process of Evaluation After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion – Digital / PDF Certificate After completing the MySql Masterclass course, you can order your CPD Accredited Digital/ PDF Certificate for £5.99. Certificate of Completion – Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. Shipping Charges: Inside the UK: £3.99 International: £10.99 Who Is This Course for? This MySql Masterclass is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand. On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level. This course has been developed with maximum flexibility and accessibility, making it ideal for people who don’t have the time to devote to traditional education. Requirements You don’t need any educational qualification or experience to enrol in the MySql Masterclass course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career Path The certification and skills you get from this MySql Masterclass Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors.

Overview This Deep Learning & Neural Networks Python - Keras: For Dummies course will unlock your full potential and will show you how to excel in a career in Deep Learning & Neural Networks Python - Keras: For Dummies. So upskill now and reach your full potential. Everything you need to get started in Deep Learning & Neural Networks Python - Keras: For Dummies is available in this course. Learning and progressing are the hallmarks of personal development. This Deep Learning & Neural Networks Python - Keras: For Dummies will quickly teach you the must-have skills needed to start in the relevant industry. In This Deep Learning & Neural Networks Python - Keras: For Dummies Course, You Will: Learn strategies to boost your workplace efficiency. Hone your Deep Learning & Neural Networks Python - Keras: For Dummies skills to help you advance your career. Acquire a comprehensive understanding of various Deep Learning & Neural Networks Python - Keras: For Dummies topics and tips from industry experts. Learn in-demand Deep Learning & Neural Networks Python - Keras: For Dummies skills that are in high demand among UK employers, which will help you to kickstart your career. This Deep Learning & Neural Networks Python - Keras: For Dummies course covers everything you must know to stand against the tough competition in the Deep Learning & Neural Networks Python - Keras: For Dummies field.  The future is truly yours to seize with this Deep Learning & Neural Networks Python - Keras: For Dummies. Enrol today and complete the course to achieve a Deep Learning & Neural Networks Python - Keras: For Dummies certificate that can change your professional career forever. Additional Perks of Buying a Course From Institute of Mental Health Study online - whenever and wherever you want. One-to-one support from a dedicated tutor throughout your course. Certificate immediately upon course completion 100% Money back guarantee Exclusive discounts on your next course purchase from Institute of Mental Health Enrolling in the Deep Learning & Neural Networks Python - Keras: For Dummies course can assist you in getting into your desired career quicker than you ever imagined. So without further ado, start now. Process of Evaluation After studying the Deep Learning & Neural Networks Python - Keras: For Dummies course, your skills and knowledge will be tested with a MCQ exam or assignment. You must get a score of 60% to pass the test and get your certificate.  Certificate of Achievement Upon successfully completing the Deep Learning & Neural Networks Python - Keras: For Dummies course, you will get your CPD accredited digital certificate immediately. And you can also claim the hardcopy certificate completely free of charge. All you have to do is pay a shipping charge of just £3.99. Who Is This Course for? This Deep Learning & Neural Networks Python - Keras: For Dummies is suitable for anyone aspiring to start a career in Deep Learning & Neural Networks Python - Keras: For Dummies; even if you are new to this and have no prior knowledge on Deep Learning & Neural Networks Python - Keras: For Dummies, this course is going to be very easy for you to understand.  And if you are already working in the Deep Learning & Neural Networks Python - Keras: For Dummies field, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  Taking this Deep Learning & Neural Networks Python - Keras: For Dummies course is a win-win for you in all aspects.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements This Deep Learning & Neural Networks Python - Keras: For Dummies course has no prerequisite.  You don't need any educational qualification or experience to enrol in the Deep Learning & Neural Networks Python - Keras: For Dummies course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online Deep Learning & Neural Networks Python - Keras: For Dummies course. Moreover, this course allows you to learn at your own pace while developing transferable and marketable skills. Course Curriculum Course Introduction and Table of Contents Course Introduction and Table of Contents 00:11:00 Deep Learning Overview Deep Learning Overview - Theory Session - Part 1 00:06:00 Deep Learning Overview - Theory Session - Part 2 00:07:00 Choosing Between ML or DL for the next AI project - Quick Theory Session Choosing Between ML or DL for the next AI project - Quick Theory Session 00:09:00 Preparing Your Computer Preparing Your Computer - Part 1 00:07:00 Preparing Your Computer - Part 2 00:06:00 Python Basics Python Basics - Assignment 00:09:00 Python Basics - Flow Control 00:09:00 Python Basics - Functions 00:04:00 Python Basics - Data Structures 00:12:00 Theano Library Installation and Sample Program to Test Theano Library Installation and Sample Program to Test 00:11:00 TensorFlow library Installation and Sample Program to Test TensorFlow library Installation and Sample Program to Test 00:09:00 Keras Installation and Switching Theano and TensorFlow Backends Keras Installation and Switching Theano and TensorFlow Backends 00:10:00 Explaining Multi-Layer Perceptron Concepts Explaining Multi-Layer Perceptron Concepts 00:03:00 Explaining Neural Networks Steps and Terminology Explaining Neural Networks Steps and Terminology 00:10:00 First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset 00:07:00 Explaining Training and Evaluation Concepts Explaining Training and Evaluation Concepts 00:11:00 Pima Indian Model - Steps Explained Pima Indian Model - Steps Explained - Part 1 00:09:00 Pima Indian Model - Steps Explained - Part 2 00:07:00 Coding the Pima Indian Model Coding the Pima Indian Model - Part 1 00:11:00 Coding the Pima Indian Model - Part 2 00:09:00 Pima Indian Model - Performance Evaluation Pima Indian Model - Performance Evaluation - Automatic Verification 00:06:00 Pima Indian Model - Performance Evaluation - Manual Verification 00:08:00 Pima Indian Model - Performance Evaluation - k-fold Validation - Keras Pima Indian Model - Performance Evaluation - k-fold Validation - Keras 00:10:00 Pima Indian Model - Performance Evaluation - Hyper Parameters Pima Indian Model - Performance Evaluation - Hyper Parameters 00:12:00 Understanding Iris Flower Multi-Class Dataset Understanding Iris Flower Multi-Class Dataset 00:08:00 Developing the Iris Flower Multi-Class Model Developing the Iris Flower Multi-Class Model - Part 1 00:09:00 Developing the Iris Flower Multi-Class Model - Part 2 00:06:00 Developing the Iris Flower Multi-Class Model - Part 3 00:09:00 Understanding the Sonar Returns Dataset Understanding the Sonar Returns Dataset 00:07:00 Developing the Sonar Returns Model Developing the Sonar Returns Model 00:10:00 Sonar Performance Improvement - Data Preparation - Standardization Sonar Performance Improvement - Data Preparation - Standardization 00:15:00 Sonar Performance Improvement - Layer Tuning for Smaller Network Sonar Performance Improvement - Layer Tuning for Smaller Network 00:07:00 Sonar Performance Improvement - Layer Tuning for Larger Network Sonar Performance Improvement - Layer Tuning for Larger Network 00:06:00 Understanding the Boston Housing Regression Dataset Understanding the Boston Housing Regression Dataset 00:07:00 Developing the Boston Housing Baseline Model Developing the Boston Housing Baseline Model 00:08:00 Boston Performance Improvement by Standardization Boston Performance Improvement by Standardization 00:07:00 Boston Performance Improvement by Deeper Network Tuning Boston Performance Improvement by Deeper Network Tuning 00:05:00 Boston Performance Improvement by Wider Network Tuning Boston Performance Improvement by Wider Network Tuning 00:04:00 Save & Load the Trained Model as JSON File (Pima Indian Dataset) Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 1 00:09:00 Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 2 00:08:00 Save and Load Model as YAML File - Pima Indian Dataset Save and Load Model as YAML File - Pima Indian Dataset 00:05:00 Load and Predict using the Pima Indian Diabetes Model Load and Predict using the Pima Indian Diabetes Model 00:09:00 Load and Predict using the Iris Flower Multi-Class Model Load and Predict using the Iris Flower Multi-Class Model 00:08:00 Load and Predict using the Sonar Returns Model Load and Predict using the Sonar Returns Model 00:10:00 Load and Predict using the Boston Housing Regression Model Load and Predict using the Boston Housing Regression Model 00:08:00 An Introduction to Checkpointing An Introduction to Checkpointing 00:06:00 Checkpoint Neural Network Model Improvements Checkpoint Neural Network Model Improvements 00:10:00 Checkpoint Neural Network Best Model Checkpoint Neural Network Best Model 00:04:00 Loading the Saved Checkpoint Loading the Saved Checkpoint 00:05:00 Plotting Model Behavior History Plotting Model Behavior History - Introduction 00:06:00 Plotting Model Behavior History - Coding 00:08:00 Dropout Regularization - Visible Layer Dropout Regularization - Visible Layer - Part 1 00:11:00 Dropout Regularization - Visible Layer - Part 2 00:06:00 Dropout Regularization - Hidden Layer Dropout Regularization - Hidden Layer 00:06:00 Learning Rate Schedule using Ionosphere Dataset - Intro Learning Rate Schedule using Ionosphere Dataset 00:06:00 Time Based Learning Rate Schedule Time Based Learning Rate Schedule - Part 1 00:07:00 Time Based Learning Rate Schedule - Part 2 00:12:00 Drop Based Learning Rate Schedule Drop Based Learning Rate Schedule - Part 1 00:07:00 Drop Based Learning Rate Schedule - Part 2 00:08:00 Convolutional Neural Networks - Introduction Convolutional Neural Networks - Part 1 00:11:00 Convolutional Neural Networks - Part 2 00:06:00 MNIST Handwritten Digit Recognition Dataset Introduction to MNIST Handwritten Digit Recognition Dataset 00:06:00 Downloading and Testing MNIST Handwritten Digit Recognition Dataset 00:10:00 MNIST Multi-Layer Perceptron Model Development MNIST Multi-Layer Perceptron Model Development - Part 1 00:11:00 MNIST Multi-Layer Perceptron Model Development - Part 2 00:06:00 Convolutional Neural Network Model using MNIST Convolutional Neural Network Model using MNIST - Part 1 00:13:00 Convolutional Neural Network Model using MNIST - Part 2 00:12:00 Large CNN using MNIST Large CNN using MNIST 00:09:00 Load and Predict using the MNIST CNN Model Load and Predict using the MNIST CNN Model 00:14:00 Introduction to Image Augmentation using Keras Introduction to Image Augmentation using Keras 00:11:00 Augmentation using Sample Wise Standardization Augmentation using Sample Wise Standardization 00:10:00 Augmentation using Feature Wise Standardization & ZCA Whitening Augmentation using Feature Wise Standardization & ZCA Whitening 00:04:00 Augmentation using Rotation and Flipping Augmentation using Rotation and Flipping 00:04:00 Saving Augmentation Saving Augmentation 00:05:00 CIFAR-10 Object Recognition Dataset - Understanding and Loading CIFAR-10 Object Recognition Dataset - Understanding and Loading 00:12:00 Simple CNN using CIFAR-10 Dataset Simple CNN using CIFAR-10 Dataset - Part 1 00:09:00 Simple CNN using CIFAR-10 Dataset - Part 2 00:06:00 Simple CNN using CIFAR-10 Dataset - Part 3 00:08:00 Train and Save CIFAR-10 Model Train and Save CIFAR-10 Model 00:08:00 Load and Predict using CIFAR-10 CNN Model Load and Predict using CIFAR-10 CNN Model 00:16:00 RECOMENDED READINGS Recomended Readings 00:00:00

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Learn in-demand DevOps Fundementals: Maven and SonarQube for Engineers skills that are in high demand among UK employers, which will help you to kickstart your career. This DevOps Fundementals: Maven and SonarQube for Engineers course covers everything you must know to stand against the tough competition in the DevOps Fundementals: Maven and SonarQube for Engineers field.  The future is truly yours to seize with this DevOps Fundementals: Maven and SonarQube for Engineers. Enrol today and complete the course to achieve a DevOps Fundementals: Maven and SonarQube for Engineers certificate that can change your professional career forever. Additional Perks of Buying a Course From Institute of Mental Health Study online - whenever and wherever you want. One-to-one support from a dedicated tutor throughout your course. Certificate immediately upon course completion 100% Money back guarantee Exclusive discounts on your next course purchase from Institute of Mental Health Enrolling in the DevOps Fundementals: Maven and SonarQube for Engineers course can assist you in getting into your desired career quicker than you ever imagined. So without further ado, start now. Process of Evaluation After studying the DevOps Fundementals: Maven and SonarQube for Engineers course, your skills and knowledge will be tested with a MCQ exam or assignment. You must get a score of 60% to pass the test and get your certificate.  Certificate of Achievement Upon successfully completing the DevOps Fundementals: Maven and SonarQube for Engineers course, you will get your CPD accredited digital certificate immediately. And you can also claim the hardcopy certificate completely free of charge. All you have to do is pay a shipping charge of just £3.99. Who Is This Course for? This DevOps Fundementals: Maven and SonarQube for Engineers is suitable for anyone aspiring to start a career in DevOps Fundementals: Maven and SonarQube for Engineers; even if you are new to this and have no prior knowledge on DevOps Fundementals: Maven and SonarQube for Engineers, this course is going to be very easy for you to understand.  And if you are already working in the DevOps Fundementals: Maven and SonarQube for Engineers field, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  Taking this DevOps Fundementals: Maven and SonarQube for Engineers course is a win-win for you in all aspects.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements This DevOps Fundementals: Maven and SonarQube for Engineers course has no prerequisite.  You don't need any educational qualification or experience to enrol in the DevOps Fundementals: Maven and SonarQube for Engineers course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online DevOps Fundementals: Maven and SonarQube for Engineers course. Moreover, this course allows you to learn at your own pace while developing transferable and marketable skills. Course Curriculum Introduction Introduction to Maven 00:01:00 Topics Covered in this Course 00:03:00 How Maven Helps to a DevOps Engineer 00:02:00 Resource to Start 00:01:00 Setup Maven Environment on Windows Setup Maven Environment on Windows 00:01:00 Java Installation on Windows 00:05:00 Eclipse Installation 00:03:00 Create 1st Maven Project 00:04:00 Maven Coordinates 00:07:00 Default Directory Structure 00:03:00 Steps Involved to Build a Java Project 00:02:00 Maven Goals 00:06:00 Maven Goals in Action 00:07:00 Maven Goals, Repositories What is pom.xml and How it Works 00:05:00 About the Section 00:02:00 Maven Repositories 00:06:00 Maven goals - Deploy Goal for Local Repository 00:03:00 Push Maven Project onto GitHub 00:08:00 Maven on Linux Create an EC2 Instance 00:04:00 Prerequisites to Setup Maven 00:05:00 Setup Maven 00:04:00 Build Maven Project on Linux 00:10:00 Common Maven Goals 00:03:00 Create a Project with Maven Archetype 00:06:00 Plugins and dependencies in pom.xml 00:09:00 Settings.xml file 00:03:00 Tomcat Server Configurations 00:05:00 Deploy war on Tomcat Server 00:10:00 Maven in DevOps workflow Maven in DevOps workflow 00:01:00 Jenkins Installation 00:07:00 Add Maven Build Server as an Agent to Jenkins 00:07:00 Build Jenkins Job on Slave Node 00:07:00 Build a war file on Agent Node (Maven Server) 00:04:00 Additional Resources Create an AWS account 00:06:00 Install Git bash 00:03:00 Connect to a Linux with Mobaxterm 00:04:00 Install Tomcat 00:11:00 SonarQube SonarQube Introduction 00:07:00 SonarQube Installation 00:11:00 SonarQube Console Overview 00:14:00 SonarQube Installation with PostgreSQL Database 00:29:00 SonarQube Integration with Jenkins 00:15:00

Unlock the potential of business intelligence with our specialized Business Intelligence Analyst Course. Learn to analyze data, extract insights, and drive strategic decisions to optimize business performance. Gain practical skills in data visualization, reporting, and predictive analytics using industry-leading tools and techniques. Whether you're a business professional or aspiring analyst, this course equips you with the expertise to excel in leveraging data for business intelligence.

Duration 3 Days 18 CPD hours This course is intended for Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform Overview This course teaches participants the following skills: Use best practices for application development. Choose the appropriate data storage option for application data. Implement federated identity management. Develop loosely coupled application components or microservices. Integrate application components and data sources. Debug, trace, and monitor applications. Perform repeatable deployments with containers and deployment services. Choose the appropriate application runtime environment; use Google Container Engine as a runtime environment and later switch to a no-ops solution with Google App Engine flexible environment. Learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. This course uses lectures, demos, and hands-on labs to show you how to use Google Cloud services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications. Best Practices for Application Development Code and environment management. Design and development of secure, scalable, reliable, loosely coupled application components and microservices. Continuous integration and delivery. Re-architecting applications for the cloud. Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK How to set up and use Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK. Lab: Set up Google Client Libraries, Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials. Overview of Data Storage Options Overview of options to store application data. Use cases for Google Cloud Storage, Cloud Firestore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner. Best Practices for Using Cloud Firestore Best practices related to using Cloud Firestore in Datastore mode for:Queries, Built-in and composite indexes, Inserting and deleting data (batch operations),Transactions,Error handling. Bulk-loading data into Cloud Firestore by using Google Cloud Dataflow. Lab: Store application data in Cloud Datastore. Performing Operations on Cloud Storage Operations that can be performed on buckets and objects. Consistency model. Error handling. Best Practices for Using Cloud Storage Naming buckets for static websites and other uses. Naming objects (from an access distribution perspective). Performance considerations. Setting up and debugging a CORS configuration on a bucket. Lab: Store files in Cloud Storage. Handling Authentication and Authorization Cloud Identity and Access Management (IAM) roles and service accounts. User authentication by using Firebase Authentication. User authentication and authorization by using Cloud Identity-Aware Proxy. Lab: Authenticate users by using Firebase Authentication. Using Pub/Sub to Integrate Components of Your Application Topics, publishers, and subscribers. Pull and push subscriptions. Use cases for Cloud Pub/Sub. Lab: Develop a backend service to process messages in a message queue. Adding Intelligence to Your Application Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API. Using Cloud Functions for Event-Driven Processing Key concepts such as triggers, background functions, HTTP functions. Use cases. Developing and deploying functions. Logging, error reporting, and monitoring. Managing APIs with Cloud Endpoints Open API deployment configuration. Lab: Deploy an API for your application. Deploying Applications Creating and storing container images. Repeatable deployments with deployment configuration and templates. Lab: Use Deployment Manager to deploy a web application into Google App Engine flexible environment test and production environments. Execution Environments for Your Application Considerations for choosing an execution environment for your application or service:Google Compute Engine (GCE),Google Kubernetes Engine (GKE), App Engine flexible environment, Cloud Functions, Cloud Dataflow, Cloud Run. Lab: Deploying your application on App Engine flexible environment. Debugging, Monitoring, and Tuning Performance Application Performance Management Tools. Stackdriver Debugger. Stackdriver Error Reporting. Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting. Stackdriver Logging. Key concepts related to Stackdriver Trace and Stackdriver Monitoring. Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance.