4095 Technology courses in Coventry delivered Online

Learn about the jQuery library from scratch and stretch your journey from a beginner-level to advanced-level professional with a step-by-step and comprehensive course. A basic understanding of the JavaScript Document Object Model and CSS is suggested as a prerequisite to this course.

Recognised Accreditation This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. What is CPD? Employers, professional organisations, and academic institutions all recognise CPD, therefore a credential from CPD Certification Service adds value to your professional goals and achievements. Benefits of CPD Improve your employment prospects Boost your job satisfaction Promotes career advancement Enhances your CV Provides you with a competitive edge in the job market Demonstrate your dedication Showcases your professional capabilities What is IPHM? The IPHM is an Accreditation Board that provides Training Providers with international and global accreditation. The Practitioners of Holistic Medicine (IPHM) accreditation is a guarantee of quality and skill. Benefits of IPHM It will help you establish a positive reputation in your chosen field You can join a network and community of successful therapists that are dedicated to providing excellent care to their client You can flaunt this accreditation in your CV It is a worldwide recognised accreditation What is Quality Licence Scheme? This course is endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. Benefits of Quality License Scheme Certificate is valuable Provides a competitive edge in your career It will make your CV stand out Course Curriculum Course 1: Basics Of Solar Energy System Introduction To PV System Construction 00:23:00 Solar Heating, Solar Irradiation And Panels 00:37:00 Effect of Insolation and Temperature on V-I Curve 00:04:00 PV Installation, Short Circuit And Open Circuit Tests Using Avometer 00:15:00 Solar Wires And Cables Installation Process 00:22:00 Mounting Of PV System 00:04:00 Shading and Tilt angle 00:15:00 Half Cell Technology In PV System 00:25:00 Importance of Charge Controller 00:03:00 PWM And MPPT Charge Controllers 00:14:00 Understanding More About MPPT Charge Controller 00:24:00 Junction Box 00:03:00 Wiring of Junction Box 00:05:00 Function, Types And Data Sheet Of Inverter 00:55:00 Determining PV Array Max Voltage 00:09:00 Course 2: Batteries In PV System Construction and Types of Batteries Used 00:08:00 Charging of Lead Acid Batteries and Hydrometer 00:06:00 Mainitance of Batteries and Methods of Charging 00:03:00 Cycle of Batteries 00:03:00 Course 3: Components and Design of Off Grid System Off-Grid Solar System 00:02:00 Advantages of Off-Grid Solar System 00:01:00 Equipment of Off Grid Solar System 00:04:00 Inverter Selection in PV System 00:02:00 Example 1 On Designing an Off Grid System 00:01:00 Determine Power Consumption Demands 00:04:00 Sizing of The PV Modules and Inverter Sizing 00:05:00 Battery Sizing 00:08:00 Solar Charge Controller Sizing 00:04:00 MPPT Charge Controller Sizing 00:10:00 Example 2 Design of an Off Grid System 00:19:00 Course 4: Components and Design of On Grid System Gried-Tied Solar System 00:02:00 Advantages of Grid-Tied Solar System 00:03:00 Equipment of Grid-Tied Solar System 00:03:00 Example Design of an ON Grid System 00:10:00 PV Energy According to Area 00:02:00 Course 5: Design of PV System Using PVSyst Program Design of Grid Connected System Using PVSyst Program 00:12:00 Design of an Off Grid Solar Energy System Using PVSyst Program 00:28:00 Design Mega PV System Using PVSyst Program 00:29:00 Course 6: Solar Water Pumping System Introduction To Water Pumping System And Steps Of Design 00:24:00 Solved Example On Solar Pumping System Design 00:22:00 Course 7: Protection Of Solar Energy System Introduction to Protection of PV System 00:06:00 Selection of Fuses and Protection of String 00:13:00 Protection of Arrays 00:06:00 Protection of Inverter 00:07:00 Protection of Transformer 00:06:00 Surge Protection Device 00:02:00 Grounding of PV System 00:06:00 Types of BusBars in PV System and Selection of BusBars 00:12:00 Course 7: Design of PV System Using Excel Sheet Design Of Off Grid PV System Using Excel Sheet 00:26:00 Course 8: Basics of Autocad and Single Line Diagram of PV System Introduction To Autocad 00:02:00 How to Get Free Licence from Autocad. 00:04:00 Starting Autocad and Changing Background 00:02:00 Drawing a Line in Autocad 00:04:00 Drawing a Rectangle in Autocad 00:04:00 Drawing a Circle in Autocad 00:01:00 Drawing a Polygon in Autocad 00:03:00 Drawing an Arc in Autocad 00:01:00 Drawing a PolyLine in Autocad 00:03:00 Multiple Lines Using the Offset Feature 00:03:00 Adding Text to Autocad 00:03:00 Extending Lines in Autocad 00:01:00 Selection in Autocad 00:04:00 F-shortcuts in Autocad 00:01:00 Dimensions in Autocad 00:04:00 Multi Spiral Line and MLD in Autocad 00:02:00 Block and Explode Commands In Autocad 00:02:00 Move and Scale Commands in Autocad 00:01:00 Rotate, Mirror and Fillet Commands in Autocad 00:02:00 Area Calculation and Adding Layer in Autocad 00:03:00 Saving your File and Autosave Feature 00:07:00 Drawing Fluorescent Symbol Using Autocad 00:06:00 Autocad Classic Mode and Workspace 00:03:00 Single Line Diagram Of PV System And Selection Of Fuses And Breakers 00:45:00 Course 9: Design Of Grounding System Effect Of Current On Human Body 00:09:00 Types Of Electric Hazards 00:08:00 Classification of Earthing Systems 00:23:00 Components Of Earthing System 00:09:00 Design and Resistance of Earthing Electrode 00:12:00 Design and Resistance of Earthing Conductor 00:13:00 Measurement of Earth Resistance by Megger and Three Point Method 00:03:00 Design Earthing or Ground Grid Using ETAP 00:21:00 Course 10: MATLAB and ETAP PV Simulation Simulation Of PV Cell In MATLAB And Obtaining V-I Characteristics 00:28:00 Get a Complete Grid-Connected PV System For Free 00:25:00 Simulation of PV System in ETAP 00:24:00 Obtain Your Certificate Order Your Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00

Embark on a captivating journey into the world of artificial intelligence with our course, 'Machine Learning Basics.' This voyage begins with an immersive introduction, setting the stage for an exploration into the intricate and fascinating realm of machine learning. Envision yourself unlocking the mysteries of algorithms and data patterns, essential skills in today's technology-driven landscape. The course offers a comprehensive foray into the core principles of machine learning, starting from the very basics and gradually building to more complex concepts, making it an ideal path for beginners and enthusiasts alike. As you delve deeper, each section unravels a vital component of machine learning. Grasp the essentials of regression analysis, understand the role of predictors, and navigate through the functionalities of Minitab, a key tool in data analysis. Journey through the structured world of regression trees and binary logistic regression, and master the art of classification trees. The course also emphasizes the importance of data cleaning and constructing robust data models, culminating in the achievement of learning success. This course is not just an educational experience; it's a gateway to the future of data science and AI. Learning Outcomes Comprehend the basic principles and applications of machine learning. Develop proficiency in regression analysis and predictor identification. Gain practical skills in Minitab for data analysis. Understand and apply regression and classification trees. Acquire expertise in data cleaning and model creation. Why choose this Machine Learning Basics course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Machine Learning Basics course for? Novices eager to delve into machine learning. Data enthusiasts looking to enhance their analytical skills. Professionals in IT and related fields expanding their expertise. Academics and students in computer science and data studies. Career changers interested in the field of data science and AI. Career path Data Analyst - £30,000 to £55,000 Machine Learning Engineer - £40,000 to £80,000 AI Developer - £35,000 to £75,000 Business Intelligence Analyst - £32,000 to £60,000 Research Scientist (Machine Learning) - £45,000 to £85,000 Software Engineer (AI Specialization) - £38,000 to £70,000 Prerequisites This Machine Learning Basics does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Machine Learning Basics was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Section 01: Introduction Introduction to Supervised Machine Learning 00:06:00 Section 02: Regression Introduction to Regression 00:13:00 Evaluating Regression Models 00:11:00 Conditions for Using Regression Models in ML versus in Classical Statistics 00:21:00 Statistically Significant Predictors 00:09:00 Regression Models Including Categorical Predictors. Additive Effects 00:20:00 Regression Models Including Categorical Predictors. Interaction Effects 00:18:00 Section 03: Predictors Multicollinearity among Predictors and its Consequences 00:21:00 Prediction for New Observation. Confidence Interval and Prediction Interval 00:06:00 Model Building. What if the Regression Equation Contains 'Wrong' Predictors? 00:13:00 Section 04: Minitab Stepwise Regression and its Use for Finding the Optimal Model in Minitab 00:13:00 Regression with Minitab. Example. Auto-mpg: Part 1 00:17:00 Regression with Minitab. Example. Auto-mpg: Part 2 00:18:00 Section 05: Regression Trees The Basic idea of Regression Trees 00:18:00 Regression Trees with Minitab. Example. Bike Sharing: Part1 00:15:00 Regression Trees with Minitab. Example. Bike Sharing: Part 2 00:10:00 Section 06: Binary Logistics Regression Introduction to Binary Logistics Regression 00:23:00 Evaluating Binary Classification Models. Goodness of Fit Metrics. ROC Curve. AUC 00:20:00 Binary Logistic Regression with Minitab. Example. Heart Failure: Part 1 00:16:00 Binary Logistic Regression with Minitab. Example. Heart Failure: Part 2 00:18:00 Section 07: Classification Trees Introduction to Classification Trees 00:12:00 Node Splitting Methods 1. Splitting by Misclassification Rate 00:20:00 Node Splitting Methods 2. Splitting by Gini Impurity or Entropy 00:11:00 Predicted Class for a Node 00:06:00 The Goodness of the Model - 1. Model Misclassification Cost 00:11:00 The Goodness of the Model - 2 ROC. Gain. Lit Binary Classification 00:15:00 The Goodness of the Model - 3. ROC. Gain. Lit. Multinomial Classification 00:08:00 Predefined Prior Probabilities and Input Misclassification Costs 00:11:00 Building the Tree 00:08:00 Classification Trees with Minitab. Example. Maintenance of Machines: Part 1 00:17:00 Classification Trees with Miitab. Example. Maintenance of Machines: Part 2 00:10:00 Section 08: Data Cleaning Data Cleaning: Part 1 00:16:00 Data Cleaning: Part 2 00:17:00 Creating New Features 00:12:00 Section 09: Data Models Polynomial Regression Models for Quantitative Predictor Variables 00:20:00 Interactions Regression Models for Quantitative Predictor Variables 00:15:00 Qualitative and Quantitative Predictors: Interaction Models 00:28:00 Final Models for Duration and TotalCharge: Without Validation 00:18:00 Underfitting or Overfitting: The 'Just Right Model' 00:18:00 The 'Just Right' Model for Duration 00:16:00 The 'Just Right' Model for Duration: A More Detailed Error Analysis 00:12:00 The 'Just Right' Model for TotalCharge 00:14:00 The 'Just Right' Model for ToralCharge: A More Detailed Error Analysis 00:06:00 Section 10: Learning Success Regression Trees for Duration and TotalCharge 00:18:00 Predicting Learning Success: The Problem Statement 00:07:00 Predicting Learning Success: Binary Logistic Regression Models 00:17:00 Predicting Learning Success: Classification Tree Models 00:09:00

Duration 5 Days 30 CPD hours This course is intended for This course is recommended for technical professionals who support, install, deploy or administer Check Point products. This course is recommended for technical professionals who perform advanced deployment configurations of Check Point products. Overview CCSA Know how to perform periodic administrator tasks. Describe the basic functions of the Gaia operating system. Recognize SmartConsole features, functions, and tools. Understand how SmartConsole is used by administrators to give user access. Learn how Check Point security solutions and products work and how they protect networks. Understand licensing and contract requirements for Check Point security products. Describe the essential elements of a Security Policy. Understand the Check Point policy layer concept. Understand how to enable the Application Control and URL Filtering software. Blades to block access to various applications. Describe how to configure manual and automatic NAT. Identify tools designed to monitor data, determine threats and recognize opportunities for performance improvements. Describe different Check Point Threat Prevention solutions for network attacks. Articulate how the Intrusion Prevention System is configured, maintained and tuned. Understand the Infinity Threat Prevention system. Knowledge about Check Point's IoT Protect. CCSE Provide an overview of the upgrade service and options available. Explain how to perform management upgrade and migration. Articulate the process using CPUSE features. Articulate the purpose and function of Management High Availability. Explain Primary vs Secondary, Active vs Standby and Synchronization. Explain disaster recovery steps in case the primary management server becomes unavailable. Provide overview of Central Deployment in SmartConsole. Articulate an understanding of Security Gateway cluster upgrade methods. Explain about Multi Version Cluster (MVC) upgrades. Discuss Gaia Commands and how they are used. Explain the main processes on s and s. Describe how to work with scripts and SmartTasks to configure automatic actions. Explain the Management Data Plane Separation (MDPS) Explain kernel operations and traffic flow Articulate Dynamic and Updatable Objects in Security Gateways Explain the policy installation flow and files used. Describe the use of policy installation history. Explain concurrent and accelerated install policy. Describe an overview of APIs and ways to use and authenticate. Explain how to make changes in GAIA and management configuration. Explain how to install policy using API. Explain how the SecureXL acceleration technology enhances and optimizes Security Gateway performance. Learn basic concepts and develop skills necessary to administer IT security fundamental tasks. CCSA Outline Configure the Security Management Server. Use the WebUI to run the First Time Wizard. Install the Smart Console. Install the Alpha Gateway using the network detailed in the course topology. Demonstrate how the Security Management Server and Gateway communicate. Test SIC Status. Create multiple administrators and apply different roles and permissions for simultaneous administration. Validate existing licenses for products installed on the network. Create and configure host, network and group objects. Create a simplified Security Policy. Demonstrate how to use Security Zones in policy. Demonstrate how to share a layer between Security Polices. Configure Network Address Translation for server and network objects. Enable Identity Awareness. Deploy user access roles for more granular control of the security Policy. Generate network Traffic and use traffic visibility tools to monitor the data. Use SmartConsole and SmartView Monitor to view status, alerts, and block suspicious traffic. CCSE Outline Prepare for a Security Management Server Upgrade Upgrade the Security Management Server Deploy a Secondary Security Management Server Configure a Distributed Log Server Upgrade a Security Gateway from SmartConsole Work with the Command Line Use Scripts and SmartTasks Configure Dynamic Objects Monitor Traffic Verify Policy Installation and Status Work with Gaia and Management APIs Work with Acceleration Features Configure a Locally Managed Site to Site VPN Configure a Site to Site VPN with an Interoperable Device Configure Remote Access VPN Configure Mobile Access VPN Configure a High Availability Cluster Work with ClusterXL Configure Policy Compliance Deploy SmartEvent

Duration 4 Days 24 CPD hours This course is intended for The workshop is designed for data scientists who currently use Python or R to work with smaller datasets on a single machine and who need to scale up their analyses and machine learning models to large datasets on distributed clusters. Data engineers and developers with some knowledge of data science and machine learning may also find this workshop useful. Overview Overview of data science and machine learning at scale Overview of the Hadoop ecosystem Working with HDFS data and Hive tables using Hue Introduction to Cloudera Data Science Workbench Overview of Apache Spark 2 Reading and writing data Inspecting data quality Cleansing and transforming data Summarizing and grouping data Combining, splitting, and reshaping data Exploring data Configuring, monitoring, and troubleshooting Spark applications Overview of machine learning in Spark MLlib Extracting, transforming, and selecting features Building and evaluating regression models Building and evaluating classification models Building and evaluating clustering models Cross-validating models and tuning hyperparameters Building machine learning pipelines Deploying machine learning models Spark, Spark SQL, and Spark MLlib PySpark and sparklyr Cloudera Data Science Workbench (CDSW) Hue This workshop covers data science and machine learning workflows at scale using Apache Spark 2 and other key components of the Hadoop ecosystem. The workshop emphasizes the use of data science and machine learning methods to address real-world business challenges. Using scenarios and datasets from a fictional technology company, students discover insights to support critical business decisions and develop data products to transform the business. The material is presented through a sequence of brief lectures, interactive demonstrations, extensive hands-on exercises, and discussions. The Apache Spark demonstrations and exercises are conducted in Python (with PySpark) and R (with sparklyr) using the Cloudera Data Science Workbench (CDSW) environment. The workshop is designed for data scientists who currently use Python or R to work with smaller datasets on a single machine and who need to scale up their analyses and machine learning models to large datasets on distributed clusters. Data engineers and developers with some knowledge of data science and machine learning may also find this workshop useful. Overview of data science and machine learning at scaleOverview of the Hadoop ecosystemWorking with HDFS data and Hive tables using HueIntroduction to Cloudera Data Science WorkbenchOverview of Apache Spark 2Reading and writing dataInspecting data qualityCleansing and transforming dataSummarizing and grouping dataCombining, splitting, and reshaping dataExploring dataConfiguring, monitoring, and troubleshooting Spark applicationsOverview of machine learning in Spark MLlibExtracting, transforming, and selecting featuresBuilding and evauating regression modelsBuilding and evaluating classification modelsBuilding and evaluating clustering modelsCross-validating models and tuning hyperparametersBuilding machine learning pipelinesDeploying machine learning models Additional course details: Nexus Humans Cloudera Data Scientist Training 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 Cloudera Data Scientist Training 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.

Duration 3 Days 18 CPD hours This course is intended for This course is ideal for those who regularly deploy or manage Meraki networks and want to deepen their technical expertise and understanding of the full Meraki product suite and features. This may include professionals with job titles or in roles such as: Consulting Systems Engineer Deployment Engineer Network Administrator Network Manager Network Engineer Site Reliability Engineer Systems Engineer Technical Solutions Architect Wireless Design Engineer Wireless Engineer Overview After completing the course, you should be able to: Plan new Cisco Meraki architectures and expand existing deployments Design the network for scalable management and high availability Describe how to automate and scale Meraki deployments with dashboard tools Use dynamic routing protocols to expand networks and improve WAN performance Describe proper QoS, policy and performance-based routing configurations across a Cisco Meraki network and WAN optimization through traffic shaping Describe Virtual Private Network (VPN) and Wide Area Network (WAN) topologies and how to integrate them Secure, expand, and shape the network Implement switched network concepts and practices, and configure guests networks Implement wireless configurations concepts and practices Describe endpoint management concepts and practices using Cisco Meraki Systems Manager Describe physical security concepts and practices Gain network insight by monitoring applications Describe how to prepare monitoring, logging, and alerting services Set up reporting and auditing capabilities in the Cisco Meraki dashboard Monitor and troubleshoot issues using Cisco Meraki tools The course, Engineering Cisco Meraki Solutions Part 2 (ECMS2) v2.1 elevates your knowledge of Cisco© Meraki? technology suite. In this advanced technical training course, you?ll learn how to plan for network deployments and integrations using the Cisco Meraki platform. Through practical hands-on instruction and experiences, you will learn how to operate Meraki networks and troubleshoot complex network incidents using the Meraki Dashboard and analytics. You will also learn how to design Meraki architectures for redundancy, high-density, and scalability by implementing comprehensive Meraki product features to meet design objectives. This course is the second of two courses that prepares you for Cisco Meraki certification. Course Outline Planning new Cisco Meraki architectures and expanding existing deployments Designing for scalable management and high availability Automating and scaling Meraki deployments Designing routing and practices on the Meraki platform Describing Quality of Service (QoS) and traffic shaping design Building VPN and WAN topologies Securing, expanding, and shaping the network Describing network concepts and practices Implementing wireless configuration practices and concepts Describing Endpoint management concepts and practices Describing physical security concepts and practices Gaining network insight through monitoring applications Preparing monitoring, logging, and alerting services Setting up reporting and auditing capabilities in the Cisco Meraki Dashboard Gaining visibility and resolving issues using Meraki features and built-in troubleshooting tools Additional course details: Nexus Humans Cisco Engineering Cisco Meraki Solutions Part 2 (ECMS2) v2.1 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 Cisco Engineering Cisco Meraki Solutions Part 2 (ECMS2) v2.1 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.

Duration 5 Days 30 CPD hours This course is intended for The skills covered in this course converge on four areas-software development, IT operations, applied math and statistics, and business analysis. Target students for this course should be looking to build upon their knowledge of the data science process so that they can apply AI systems, particularly machine learning models, to business problems. So, the target student is likely a data science practitioner, software developer, or business analyst looking to expand their knowledge of machine learning algorithms and how they can help create intelligent decisionmaking products that bring value to the business. A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. This course is also designed to assist students in preparing for the CertNexus Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210) certification Overview In this course, you will develop AI solutions for business problems. You will: Solve a given business problem using AI and ML. Prepare data for use in machine learning. Train, evaluate, and tune a machine learning model. Build linear regression models. Build forecasting models. Build classification models using logistic regression and k -nearest neighbor. Build clustering models. Build classification and regression models using decision trees and random forests. Build classification and regression models using support-vector machines (SVMs). Build artificial neural networks for deep learning. Put machine learning models into operation using automated processes. Maintain machine learning pipelines and models while they are in production Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions. Solving Business Problems Using AI and ML Topic A: Identify AI and ML Solutions for Business Problems Topic B: Formulate a Machine Learning Problem Topic C: Select Approaches to Machine Learning Preparing Data Topic A: Collect Data Topic B: Transform Data Topic C: Engineer Features Topic D: Work with Unstructured Data Training, Evaluating, and Tuning a Machine Learning Model Topic A: Train a Machine Learning Model Topic B: Evaluate and Tune a Machine Learning Model Building Linear Regression Models Topic A: Build Regression Models Using Linear Algebra Topic B: Build Regularized Linear Regression Models Topic C: Build Iterative Linear Regression Models Building Forecasting Models Topic A: Build Univariate Time Series Models Topic B: Build Multivariate Time Series Models Building Classification Models Using Logistic Regression and k-Nearest Neighbor Topic A: Train Binary Classification Models Using Logistic Regression Topic B: Train Binary Classification Models Using k-Nearest Neighbor Topic C: Train Multi-Class Classification Models Topic D: Evaluate Classification Models Topic E: Tune Classification Models Building Clustering Models Topic A: Build k-Means Clustering Models Topic B: Build Hierarchical Clustering Models Building Decision Trees and Random Forests Topic A: Build Decision Tree Models Topic B: Build Random Forest Models Building Support-Vector Machines Topic A: Build SVM Models for Classification Topic B: Build SVM Models for Regression Building Artificial Neural Networks Topic A: Build Multi-Layer Perceptrons (MLP) Topic B: Build Convolutional Neural Networks (CNN) Topic C: Build Recurrent Neural Networks (RNN) Operationalizing Machine Learning Models Topic A: Deploy Machine Learning Models Topic B: Automate the Machine Learning Process with MLOps Topic C: Integrate Models into Machine Learning Systems Maintaining Machine Learning Operations Topic A: Secure Machine Learning Pipelines Topic B: Maintain Models in Production

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Discover the keys to success in the real estate industry with our comprehensive Estate Agent & Letting Agent Diploma. Gain essential skills in property marketing, negotiation, and client management. Master the art of property valuation and leasing while staying updated on industry regulations. Elevate your career in real estate with this diploma, designed to empower you with the knowledge and expertise needed to thrive as an estate or letting agent. Enroll now to unlock a rewarding future in the dynamic world of property management.

Who is this course for? The Interior Design Visualization Professional Certificate is perfect for individuals aspiring to launch their interior design business. Learn essential skills in AutoCAD, SketchUp, Photoshop, InDesign, Vray, and 3ds Max. If you prefer to book over the phone, simply call 02077202581. Click here for more info: Website Duration: 120 hours. 1-on-1 Training. When can I book: (Choose your preferred day and time once a week). Monday to Saturday: 9 am - 7 pm (Flexible timing with advance booking). Module 1: Introduction to Interior Design Visualization (4 hours) Understanding the Significance of Visualization in Interior Design Familiarity with Software Used: AutoCAD, 3ds Max, SketchUp, V-Ray, Photoshop, and InDesign Workflow Overview and Best Practices for Interior Design Visualization Module 2: AutoCAD for Interior Design (16 hours) Basics of AutoCAD and Its Interface Utilizing Drawing and Editing Tools for Accurate Floor Plans and Elevations Creating and Modifying 2D and 3D Objects Application of Layers, Line Types, and Hatches for Clarity Precision in Measurements and Annotations Module 3: 3ds Max for Interior Design (16 hours) Introduction to 3ds Max Interface Furniture, Fixtures, and Architectural Element Modeling Techniques Material and Texture Application for Realism Lighting Strategies for Interior Scenes V-Ray Introduction for High-Quality Rendering Scene Setup and Camera Placement for Effective Visualization Module 4: SketchUp for Interior Design (12 hours) Introduction to SketchUp and Its Interface Creating 3D Models of Interiors, Furniture, and Objects Enhancing Visuals with Materials and Textures Efficient Use of SketchUp Plugins and Extensions Seamless File Exchange Between SketchUp and Other Software Module 5: V-Ray for Interior Design Rendering (12 hours) Principles of Photorealistic Rendering Installation and Setup of V-Ray in 3ds Max and SketchUp Configuring V-Ray Settings for Optimal Rendering Advanced Material Application for Realistic Surfaces Lighting Techniques for Atmosphere and Mood Creation Module 6: Photoshop for Interior Design Visualization (12 hours) Introduction to Photoshop Interface Image Enhancement: Color, Contrast, and Saturation Adjustments Post-Processing Effects for a Polished Look Integration of 2D Elements like Textures and Patterns Creating Composite Images Using Multiple Render Passes Module 7: InDesign for Portfolio Presentation (8 hours) Introduction to InDesign Interface Designing a Visually Appealing Portfolio Layout Effective Organization and Presentation of Interior Design Visualizations Integration of Images, Text, and Graphics for Cohesive Portfolios Portfolio Export for Print and Digital Distribution Module 8: Project Work and Final Presentation (4 hours) Application of Learned Skills on a Comprehensive Interior Design Visualization Project Refinement and Polish under Instructor's Guidance Preparation and Delivery of Final Presentation Showcasing the Project Note: The course outline encompasses 80 instructional hours. The actual duration may vary based on class pace and additional practice and project work. Final Project (With Full-Time Tutor Assistance): Students will develop and present their best work in a final presentation at the end of the course. Projects are to be submitted via email to training@realanimationworks.com, and timely submission is crucial to avoid delays or interruption of sessions. Please be aware: Failure to attend a session or notify us of absence within 48 hours of the session time results in session loss and full class fee charges due to the personalized nature of the sessions. Students can request breaks or extended pauses by providing written notice through email. Benifits and Jobs after this course: Master Design Tools: Proficiency in AutoCAD, 3ds Max, SketchUp, V-Ray, Photoshop, and InDesign for interior design visualizations. Advanced 3D Skills: Expertise in detailed 3D modeling, realistic rendering, and precise lighting techniques. Portfolio Development: Create compelling portfolios using InDesign, blending images and text professionally. Career Opportunities: Interior Visualization Specialist 3D Modeler Architectural Visualizer Interior Design Consultant Digital Content Creator Freelance Interior Visualizer Virtual Reality Designer Educator/Trainer Certificate Program in Interior Design Visualization: Maintain a dedicated notebook for effective organization of study notes. Schedule makeup sessions for missed coursework, subject to available time slots. Keep detailed records and create a specialized design folder to monitor progress and nurture creative ideas. Allocate focused time for self-guided practice and project work. Receive certification from our esteemed professional design team upon successful completion of the program. Post-Program Achievements: Upon completion of the certificate program, you will: Gain confidence in software proficiency and a strong understanding of underlying principles. Demonstrate the ability to create high-quality visual representations for architectural and interior design projects. Feel well-prepared for career opportunities, backed by your software expertise. Ongoing Support: We are pleased to offer lifelong complimentary email and phone support, ensuring swift assistance with any inquiries or challenges you may face. Software Access: Access to necessary software is available via download from the developer's website or at student-friendly rates. Please note that student software usage is limited to non-commercial projects. Payment Flexibility: Choose from various payment options including internet bank transfers, credit cards, debit cards, and PayPal. Additionally, we offer installment plans tailored to our students' needs.