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The series CompTIA A+ 900 Certification Advanced Diploma provides an extensive lesson about CompTIA A+ 900 Certification. A+ Certification is one of the leading certificates in the computer industry. It certifies the competency of PC Service Specialists. Sponsored by CompTIA - the Computing Technology Industry Association, and tests, the course is administered by Pearson VUE. The course includes more than 50 lessons related to the Computer industry. The course starts by describing firmware and BIOS configuration options. After that, the course will teach you about the motherboard basics including motherboard sizes, form factors, and AMD CPU socket types. The course also includes topics such as Expansion slots, RAM types and features, install and configure PC expansion cards, install and configure storage device, CPU's and cooling methods and PC connection interfaces. The course will also focus on power supplies, PC connectors, printing technologies, networking tools, etc. In short, the course provides all the necessary information about computer hardware and operating system. Course Highlights The price is for the whole course including final exam - no hidden fees Accredited Certificate upon successful completion Efficient exam system with instant results Track progress within own personal learning portal 24/7 customer support via live chat This valuable course is suitable for anyone interested in working in this sector or who simply wants to learn more about the topic. If you're an individual looking to excel within this field then CompTIA A+ 900 Certification Advanced Diploma is for you. We've taken this comprehensive course and broken it down into several manageable modules which we believe will assist you to easily grasp each concept - from the fundamental to the most advanced aspects of the course. It really is a sure pathway to success. All our courses offer 12 months access and are designed to be studied at your own pace so you can take as much or as little time as you need to complete and gain the accredited qualification. We pride ourselves on having friendly and experienced instructors who provide full weekday support and are ready to help with any of your queries. So, if you need help, just drop them an email and await a speedy response. Furthermore, you can check the validity of your qualification and verify your certification on our website at anytime. So, why not improve your chances of gaining professional skills and better earning potential. Assessment and Certification At the end of the course, you will be required to sit an online multiple-choice test. Your test will be assessed automatically and immediately so that you will instantly know whether you have been successful. After you have successfully passed the final exam, you will be able to order an Accredited Certificate of Achievement at an additional cost of £19 for a PDF copy and £29 for an original print copy sent to you by post or for both £39. Career Path Not only does our accredited course look good on your CV, setting you apart from the competition, it can be used as a stepping stone to greater things. Further advance your learning, launch a new career or reinvigorate an existing one. On successful completion of this course, you have the potential to achieve an estimated salary of £30,000. The sky really is the limit. Course Curriculum Configuring BIOS Firmware 00:07:00 BIOS Configuration Options 00:25:00 Motherboards Motherboard Sizes Form Factors 00:14:00 The Motherboard 00:12:00 AMD CPU Socket Types 00:11:00 Expansion Slots Expansion Cards 00:13:00 Bus Speeds 00:28:00 RAM Types and Features Memory 00:06:00 Types of RAM 00:07:00 Install and Configure PC Expansion Cards Ports 00:11:00 SCSI Connections 00:14:00 Audio Video Connections 00:26:00 Install and Configure Storage Devices Storage Devices 00:17:00 Hard Drives 00:17:00 Media Capacity 00:21:00 CPU's and Cooling Methods CPU Types and Characteristics 00:14:00 PC Connection Interfaces Physical Connections USB 00:11:00 Physical Connections VGA 00:11:00 Wireless Connections Bluetooth 00:06:00 Power Supplies Power Supply Specifications 00:16:00 Custom Computer Specifications What is a Standard Client 00:13:00 Audio Video Editing Workstations 00:08:00 Installing Displays Display Device Types 00:20:00 Backlighting 00:12:00 PC Connectors DVI to HDMI 00:13:00 Installing Peripheral Standard Input Device Types 00:16:00 Expansion Card Types 00:11:00 Multimedia Devices 00:11:00 Installing Multifunction Devices and SOHO Networks SOHO Networks 00:17:00 WPS 00:16:00 Encryption 00:14:00 Printer Technologies Printers 00:02:00 Printer Technologies Topic B Inkjet Printers 00:13:00 Printer Maintenance Technical Printer Components 00:09:00 Local and Network-Based Printers 00:22:00 Networking Network Interface Card Characteristics 00:20:00 Fiber Optic Cables 00:14:00 Properties and Characteristics of TCP/IP TCP IP 00:14:00 IP Address Classes 00:14:00 Addressing Schemes 00:17:00 TCP vs. UDP Ports 00:09:00 LDAP 00:04:00 Wi-Fi Networking Standards and Encryption Types Standards 00:03:00 Install and Configure SOHO Wireless/Wired Router Setting up your Router 00:10:00 Define Appropriate NAT Policies 00:16:00 Architecture and Internet Connection Types LANs 00:08:00 Network Topologies 00:11:00 ISPs 00:06:00 Networking Tools Cable Testers 00:13:00 Laptop Hardware Components Laptops 00:09:00 Laptop Expansion Options 00:10:00 Auto-Switching and Fixed Input Power Supplies 00:09:00 Mobile Devices What is Mobile Technology 00:09:00 Mobile Device Features 00:09:00 Bluetooth Configuration Method 00:08:00 Mobile Device Ports and Accessories Mobile Device Connection Types 00:10:00 Troubleshooting Mobile Devices 00:11:00 Troubleshooting Theory Troubleshooting Theory 00:16:00 Boot to Incorrect Device 00:16:00 PC Indicator Lights 00:10:00 Repair vs. Replace 00:10:00 Troubleshooting RAID Arrays and Hard Drives Drive and Array Troubleshooting Tools 00:06:00 Common RAID Array Issues 00:17:00 Troubleshooting Video Common Video and Display Issues 00:01:00 Troubleshooting Network Issues Common Network Issues 00:12:00 Troubleshooting Printers Common Printer Troubleshooting Tools 00:14:00 Windows Operating Systems Microsoft Windows 00:12:00 Microsoft Windows Features 00:17:00 Other Operating Systems 01:00:00 Installation Types 00:14:00 Customizing System Options 00:19:00 Command Line Tools The Command Prompt 00:12:00 Microsoft Operating System Features and Tools Administrative Tools 00:41:00 Task Manager 00:28:00 Memory Diagnostic Tool 00:46:00 Control Panel Utilities The Control Panel 00:11:00 Internet Options 00:10:00 Types of User Accounts 00:11:00 Computer My Computer 00:13:00 Permissions 00:31:00 System 00:10:00 Windows Networking on Client Desktops Workgroups 00:20:00 Network Connection Types 00:18:00 Preventative Maintenance Data Backup and Restoration 00:11:00 Scheduling Tasks 00:26:00 Features and Functionality of the Mac OS and Linux Operating Systems Patch Management in Mac OS X and Linux 00:09:00 Screen Sharing 00:06:00 Mac OS Multitouch Gestures - Touchscreen 00:09:00 Client Side Virtualization What is Virtualization 00:08:00 Virtual Desktop Infrastructure 00:12:00 Cloud-based Concepts SaaS (Software as Service) 00:09:00 Network Host Properties Server Roles 00:12:00 Mobile Operating Systems Open Source Software 00:03:00 Mobile Device Network and E-mail Mobile Device Hotspot 00:10:00 Security Malware 00:09:00 Social Engineering 00:13:00 Prevention Methods Physical Security 00:14:00 Hard Drive Sanitation 00:14:00 User Education 00:26:00 Windows Security Settings Users and Groups 00:11:00 Security Best Practices Password Best Practices 00:04:00 Securing Mobile Devices Locks 00:07:00 Troubleshooting Common PC Tools Operating System Troubleshooting Tools 00:12:00 Application Errors 00:16:00 Common Network Issues 00:12:00 Common Security Issues 00:10:00 Common PC Security Issues Browser Issues 00:06:00 Common Mobile Operating Systems Troubleshooting Dim Display 00:09:00 No Sound from Speakers 00:07:00 Common Safety Practices Static Electricity 00:14:00 Electrical Hazards 00:12:00 General Power Issues 00:10:00 Hazardous Material Disposal Procedures 00:07:00 Maintenance Tools and Techniques Professional Conduct 00:11:00 Types of Hardware Toolkits 00:11:00 Hard Drive Self-Tests 00:05:00 Computer Component Maintenance Techniques 00:10:00 Privacy and Licensing Concepts Incident Response 00:08:00 Proper Communication and Professionalism 00:07:00 Set Expectations 00:06:00 Mock Exam Mock Exam - CompTIA A+ 900 Certification Advanced Diploma 00:20:00 Final Exam Final Exam - CompTIA A+ 900 Certification Advanced Diploma 00:20:00
Overview of Data Science & Machine Learning with Python Join our Data Science & Machine Learning with Python 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 Data Science & Machine Learning with Python course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Data Science & Machine Learning with Python 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 Data Science & Machine Learning with Python 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 Data Science & Machine Learning with Python. 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 Data Science & Machine Learning with Python 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 Data Science & Machine Learning with Python 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 Data Science & Machine Learning with Python 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 Data Science & Machine Learning with Python Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:04:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using NumPy 00:04:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:06:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Data Science & Machine Learning with Python 00:00:00
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Course Curriculum Section 1: Introduction Unit 1: Welcome to the Course 00:03:00 Section 2: Introduction to Affiliate Marketing Unit 1: What is Affiliate Marketing 00:06:00 Unit 2: Why Affiliate Marketing is Beneficial to Companies 00:02:00 Unit 3: Benefits of Doing Affiliate Marketing 00:03:00 Unit 4: Why Affiliate Marketing is Awesome 00:01:00 Section 3: Before You Begin with Affiliate Marketing Unit 1: 3 Things to Do Before Starting 00:02:00 Unit 2: Understand Different Types of Affiliate Sites 00:02:00 Unit 3: Always Provide Affiliate Disclosure 00:02:00 Section 4: Steps for Affiliate Marketing Unit 1: Steps to Start Affiliate Marketing 00:01:00 Unit 2: Choose a Profitable Niche 00:03:00 Unit 3: Setup Your Website 00:03:00 Section 5: Affiliate Marketing Compensation Model Unit 1: Different Types of Compensation Model 00:03:00 Unit 2: What Are Void Affiliate Transactions 00:03:00 Section 6: Finding & Applying to Affiliate programs Unit 1: How to Find Affiliate Programs 00:02:00 Unit 2: Steps to Choose an Affiliate Program 00:02:00 Unit 3: Working with Affiliate Networks 00:02:00 Unit 4: Download the List of 50 Affiliate Programs & Networks 00:01:00 Section 7: Create Content for Your Affiliate Marketing Website Unit 1: Types of Articles You Can Write 00:04:00 Unit 2: What Are Keywords & How to Find Them 00:05:00 Unit 3: How to Write SEO Friendly Articles 00:02:00 Unit 4: Including Affiliate Links in Articles 00:01:00 Section 8: Strategies to Generate Traffic Unit 1: Why Promoting Content is Important 00:01:00 Unit 2: Promoting with Social Media 00:02:00 Unit 3: Promoting through Pinterest 00:02:00 Unit 4: Using Q & A Forums 00:01:00 Unit 5: Running Paid Ads 00:02:00 Unit 6: Influencer Outreach Method 00:02:00 Unit 7: Using YouTube for Affiliate Marketing 00:02:00 Section 9: Conclusion Unit 1: Conclusion 00:01:00 Resources Resources - Affiliate Marketing 00:00:00
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