1194 Courses delivered Online

Are you embarking on the journey of mastering data analytics and visualisation in the UK? The 'Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7' is your beacon. Positioned to illuminate the intricate realm of Power BI, this course offers a comprehensive look into the foundational aspects and the advanced features that make Microsoft's tool a standout. With sections meticulously designed ranging from the fundamentals, like data transformation, to advanced concepts, such as integrating Power BI with Python and storytelling with data, this course ensures learners grasp the complete spectrum. With the rising emphasis on data analytics in today's business world, this course acquaints you with Power BI's prowess. It prepares you for the sought-after Microsoft Power BI certification in the UK. Learning Outcomes Comprehend the fundamental aspects of Power BI, from initiating a project to understanding the user interface. Develop proficiency in advanced data transformation techniques and data model creation. Integrate Python with Power BI and harness the benefits of both for enhanced data analytics. Master the art of 'Storytelling with Data' to deliver impactful presentations and reports. Understand and implement Row-Level Security and harness Power BI Cloud services efficiently. Why choose this Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are 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. Who is this Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7 for? Individuals keen on obtaining the Microsoft power bi certification UK. Analysts and data professionals aspiring to enhance their data visualisation skills. Business professionals wanting to leverage Power BI for insightful business decision-making. Tech enthusiasts aiming to amalgamate programming (Python) with data analytics. Those seeking to stay updated with the latest trends in Power BI and its evolving capabilities. Career path Data Analyst: Average Salary £30,000 - £40,000 Annually Business Intelligence Developer: Average Salary £35,000 - £45,000 Annually Power BI Developer: Average Salary £40,000 - £50,000 Annually Data Visualisation Specialist: Average Salary £32,000 - £42,000 Annually Business Intelligence Manager: Average Salary £45,000 - £55,000 Annually Data Strategy Consultant: Average Salary £50,000 - £60,000 Annually Prerequisites This Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This course 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. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £135 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Section 01: Introduction Welcome! 00:01:00 What is Power BI? 00:03:00 Download & Installing Power BI Desktop 00:04:00 Getting to know the interface 00:03:00 Mini Project: Transform Data 00:07:00 Mini Project: Visualize Data 00:05:00 Mini Project: Creating a Data Model 00:07:00 Course Outline: What will you learn in this course? 00:05:00 How to learn best with this course? 00:03:00 Section 02: Preparing our Project Creating our initial project file 00:04:00 Working with the attached project files 00:04:00 Section 03: Data Transformation - The Query Editor Exploring the Query Editor 00:06:00 Connecting to our data source 00:07:00 Editing rows 00:08:00 Changing data types 00:08:00 Replacing values 00:03:00 Close & Apply 00:03:00 Connecting to a csv file 00:03:00 Connecting to a web page 00:05:00 Extracting characters 00:06:00 Splitting & merging columns 00:09:00 Creating conditional columns 00:06:00 Creating columns from examples 00:09:00 Merging Queries 00:17:00 Pivoting & Unpivoting 00:06:00 Appending Queries 00:08:00 Practice & Solution: Population table 00:15:00 The Fact-Dimension-Model 00:09:00 Practice: Load the dimension table 00:04:00 Organizing our queries in groups 00:03:00 Entering data manually 00:05:00 Creating an index column 00:03:00 Workflow & more transformations 00:05:00 Module summary 00:05:00 Exercise 1 - Instruction 00:02:00 Exercise Solution 00:11:00 Section 04: Data Transformation - Advanced Advanced Editor - Best practices 00:09:00 Performance: References vs. Duplicating 00:10:00 Performance: Enable / Disable Load & Report Refresh 00:05:00 Group by 00:05:00 Mathematical Operations 00:05:00 Run R Script 00:15:00 Using Parameters to dynamically transform data 00:06:00 M formula language: Basics 00:07:00 M formula language: Values, Lists & Tables 00:14:00 M formula language: Functions 00:13:00 M formula language: More functions & steps 00:05:00 Exercise 2 - Instructions 00:01:00 Exercise 2 - solution 00:05:00 Section 05: Creating a Data Model Understanding the relationship 00:05:00 Create & edit relationships 00:06:00 One-to-many & one-to-one relationship 00:06:00 Many-to-many (m:n) relationship 00:08:00 Cross filter direction 00:06:00 Activate & deactivate relationships 00:06:00 Model summary 00:03:00 Exercise 3 Create Model 00:03:00 Exercise 3 Solution 00:02:00 Section 06: Data Visualization Our first visual 00:08:00 The format tab 00:12:00 Understanding tables 00:10:00 Conditional formatting 00:09:00 The Pie Chart 00:06:00 All about the filter visual 00:13:00 The filter pane for developers 00:09:00 Cross filtering & edit interactions 00:04:00 Syncing slicers across pages 00:07:00 Creating drill downs 00:08:00 Creating drill throughs 00:07:00 The tree map visual 00:07:00 The decomposition tree 00:05:00 Understanding the matrix visual 00:05:00 Editing pages 00:07:00 Buttons & Actions 00:09:00 Bookmarks to customize your report 00:10:00 Analytics and Forecasts with line charts 00:10:00 Working with custom visuals 00:07:00 Get data using R Script & R Script visual 00:08:00 Asking questions - Q&A visual 00:04:00 Wrap up - data visualization 00:08:00 Section 07: Power BI & Python Python in Power BI - Plan of attack 00:03:00 Setting up Python for Power BI 00:03:00 Transforming data using Python 00:11:00 Creating visualizations using Python 00:08:00 Violin plots, pair plots & ridge plots using Python 00:15:00 Machine learning (BayesTextAnalyzer) using Python 00:00:00 Performance & Troubleshooting 00:03:00 Section 08: Storytelling with Data Introduction 00:01:00 Show Empathy & Identify the Requirement 00:03:00 Finding the Most Suitable KPI's 00:02:00 Choose an Effective Visualization 00:04:00 Make Use of Natural Reading Pattern 00:03:00 Tell a Story Using Visual Cues 00:05:00 Avoid Chaos & Group Information 00:02:00 Warp Up - Storytelling with Data 00:02:00 Section 09: DAX - The Essentials Introduction 00:03:00 The project data 00:04:00 Measures vs. Calculated Columns 00:15:00 Automatically creating a date table in DAX 00:08:00 CALENDAR 00:05:00 Creating a complete date table with features 00:04:00 Creating key measure table 00:03:00 Aggregation functions 00:06:00 The different versions of COUNT 00:14:00 SUMX - Row based calculations 00:09:00 Section 10: DAX - The CALCULATE function CALCULATE - The basics 00:11:00 Changing the context with FILTER 00:07:00 ALL 00:08:00 ALL SELECTED 00:03:00 ALL EXCEPT 00:07:00 Section 11: Power BI Service - Power BI Cloud How to go on now? 00:03:00 Power BI Pro vs Premium & Signing up 00:04:00 Exploring the interface 00:04:00 Discovering your workspace 00:03:00 Connecting Power BI Desktop & Cloud 00:04:00 Understanding datasets & reports 00:03:00 Working on reports 00:04:00 Updating reports from Power BI Desktop 00:04:00 Creating and working with workspaces 00:07:00 Installing & using a data gateway 00:13:00 Get Quick Insights 00:03:00 Creating dashboards 00:04:00 Sharing our results through Apps 00:10:00 Power BI Mobile App 00:05:00 Creating the layout for the Mobile App 00:04:00 Wrap up Power BI Cloud 00:07:00 Section 12: Row-Level Security Introduction 00:03:00 Creating a Row-Level Security 00:05:00 Row-Level Security in the Cloud 00:04:00 Row-Level Security & Data Model 00:05:00 Dynamic Row-Level Security 00:07:00 Dynamic Many-to-Many RLS 00:04:00 Hierarchical Row-Level Security 00:13:00 Section 13: More data sources JSON & REST API 00:10:00 Setting up a local MySQL database 00:14:00 Connecting to a MySQL database in Power BI 00:05:00 Connecting to a SQL database (PostgreSQL) 00:05:00 Section 14: Next steps to improve & stay up to date Congratulations & next steps 00:06:00 The End 00:01:00 Resources Resources - Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7 00:00:00 Assignment Assignment - Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7 04:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

Are you ready to be at the helm, steering the ship into a realm where data is the new gold? In the infinite world of data, where information spirals at breakneck speed, lies a universe rich in potential and discovery: the domain of Data Science and Visualisation. This 'Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3' course unravels the wonders of extracting meaningful insights using Python, the worldwide leading language of data experts. Harnessing the strength of Python, you'll delve deep into data analysis, experience the finesse of visualisation tools, and master the art of Machine Learning. The need to understand, interpret, and act on this data has become paramount, with vast amounts of data increasing the digital sphere. Envision a canvas where raw numbers are transformed into visually compelling stories, and machine learning models foretell future trends. This course provides a meticulous pathway for anyone eager to learn the data representation paradigms backed by Python's robust libraries. Dive into a curriculum rich with analytical explorations, visual artistry, and machine learning predictions. Learning Outcomes Understanding the foundations and functionalities of Python, focusing on its application in data science. Applying various Python libraries like NumPy and Pandas for effective data analysis. Demonstrating proficiency in creating detailed visual narratives using tools like matplotlib, Seaborn, and Plotly. Implementing Machine Learning algorithms in Python using scikit-learn, ranging from regression models to clustering techniques. Designing and executing a holistic data analysis and visualisation project, encapsulating all learned techniques. Exploring advanced topics, encompassing recommender systems and natural language processing with Python. Attaining the confidence to independently analyse complex data sets and translate them into actionable insights.   Video Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/Data-Science-and-Visualisation-with-Machine-Learning.mp400:0000:0000:00Use Up/Down Arrow keys to increase or decrease volume. Why buy this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 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. Who is this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 course for? Aspiring data scientists aiming to harness the power of Python. Researchers keen to enrich their analytical and visualisation skills. Analysts aiming to add machine learning to their toolkit. Developers striving to integrate data analytics into applications. Business professionals desiring data-driven decision-making capabilities. Career path Data Scientist: £55,000 - £85,000 Per Annum Machine Learning Engineer: £60,000 - £90,000 Per Annum Data Analyst: £30,000 - £50,000 Per Annum Data Visualisation Specialist: £45,000 - £70,000 Per Annum Natural Language Processing Specialist: £65,000 - £95,000 Per Annum Business Intelligence Developer: £40,000 - £65,000 Per Annum Prerequisites This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 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. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £85 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview 00:07:00 Set-up the Environment for the Course (lecture 1) 00:09:00 Set-up the Environment for the Course (lecture 2) 00:25:00 Two other options to setup environment 00:04:00 Python Essentials Python data types Part 1 00:21:00 Python Data Types Part 2 00:15:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00 Python Essentials Exercises Overview 00:02:00 Python Essentials Exercises Solutions 00:22:00 Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. 00:03:00 NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes. 00:28:00 NumPy Essentials - Indexing, slicing, broadcasting & boolean masking 00:26:00 NumPy Essentials - Arithmetic Operations & Universal Functions 00:07:00 NumPy Essentials Exercises Overview 00:02:00 NumPy Essentials Exercises Solutions 00:25:00 Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. 00:02:00 Pandas Introduction 00:02:00 Pandas Essentials - Pandas Data Structures - Series 00:20:00 Pandas Essentials - Pandas Data Structures - DataFrame 00:30:00 Pandas Essentials - Handling Missing Data 00:12:00 Pandas Essentials - Data Wrangling - Combining, merging, joining 00:20:00 Pandas Essentials - Groupby 00:10:00 Pandas Essentials - Useful Methods and Operations 00:26:00 Pandas Essentials - Project 1 (Overview) Customer Purchases Data 00:08:00 Pandas Essentials - Project 1 (Solutions) Customer Purchases Data 00:31:00 Pandas Essentials - Project 2 (Overview) Chicago Payroll Data 00:04:00 Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00 Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach 00:13:00 Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials - Exercises Overview 00:06:00 Matplotlib Essentials - Exercises Solutions 00:21:00 Python for Data Visualization using Seaborn Seaborn - Introduction & Installation 00:04:00 Seaborn - Distribution Plots 00:25:00 Seaborn - Categorical Plots (Part 1) 00:21:00 Seaborn - Categorical Plots (Part 2) 00:16:00 Seborn-Axis Grids 00:25:00 Seaborn - Matrix Plots 00:13:00 Seaborn - Regression Plots 00:11:00 Seaborn - Controlling Figure Aesthetics 00:10:00 Seaborn - Exercises Overview 00:04:00 Seaborn - Exercise Solutions 00:19:00 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1) 00:19:00 Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2) 00:14:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview) 00:11:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions) 00:37:00 Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) 00:15:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00 Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) 00:03:00 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types.. 00:15:00 Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00 scikit-learn - Linear Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Linear Regression Model Hands-on (Part 2) 00:19:00 Good to know! How to save and load your trained Machine Learning Model! 00:01:00 scikit-learn - Linear Regression Model (Insurance Data Project Overview) 00:08:00 scikit-learn - Linear Regression Model (Insurance Data Project Solutions) 00:30:00 Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc. 00:10:00 scikit-learn - Logistic Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Logistic Regression Model - Hands-on (Part 2) 00:20:00 scikit-learn - Logistic Regression Model - Hands-on (Part 3) 00:11:00 scikit-learn - Logistic Regression Model - Hands-on (Project Overview) 00:05:00 scikit-learn - Logistic Regression Model - Hands-on (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality . 00:08:00 scikit-learn - K Nearest Neighbors - Hands-on 00:25:00 scikt-learn - K Nearest Neighbors (Project Overview) 00:04:00 scikit-learn - K Nearest Neighbors (Project Solutions) 00:14:00 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging. 00:18:00 scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1) 00:19:00 scikit-learn - Decision Tree and Random Forests (Project Overview) 00:05:00 scikit-learn - Decision Tree and Random Forests (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) 00:07:00 scikit-learn - Support Vector Machines - Hands-on (SVMs) 00:30:00 scikit-learn - Support Vector Machines (Project 1 Overview) 00:07:00 scikit-learn - Support Vector Machines (Project 1 Solutions) 00:20:00 scikit-learn - Support Vector Machines (Optional Project 2 - Overview) 00:02:00 Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method .. 00:11:00 scikit-learn - K Means Clustering - Hands-on 00:23:00 scikit-learn - K Means Clustering (Project Overview) 00:07:00 scikit-learn - K Means Clustering (Project Solutions) 00:22:00 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) 00:09:00 scikit-learn - Principal Component Analysis (PCA) - Hands-on 00:22:00 scikit-learn - Principal Component Analysis (PCA) - (Project Overview) 00:02:00 scikit-learn - Principal Component Analysis (PCA) - (Project Solutions) 00:17:00 Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance 00:06:00 Python for Recommender Systems - Hands-on (Part 1) 00:18:00 Python for Recommender Systems - - Hands-on (Part 2) 00:19:00 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) 00:13:00 NLTK - NLP-Challenges, Data Sources, Data Processing .. 00:13:00 NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00 NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW. 00:19:00 NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes 00:13:00 NLTK - NLP - Pipeline feature to assemble several steps for cross-validation 00:09:00 Resources Resources - Data Science and Visualisation with Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

Embarking on the CompTIA Security+ course is akin to unlocking a treasure trove of cybersecurity knowledge. Imagine standing at the forefront of digital security, equipped with the latest tools and techniques to safeguard information systems. This course, meticulously designed with fourteen comprehensive sections, offers an immersive journey from the basics of risk management to the complexities of securing dedicated systems. The curriculum is tailored to blend theoretical knowledge with real-world applications, ensuring learners grasp the essence of cybersecurity in today's technology-driven world. Whether it's understanding the nuances of cryptography or mastering the art of incident response, CompTIA Security+ is your gateway to becoming a cybersecurity connoisseur. Delving into this course, you'll navigate through a landscape where every section is a stepping stone to mastering security competencies.  The course begins with an introduction to the fundamental principles of cybersecurity, setting the stage for more advanced topics like identity and account management, and securing wireless LANs. Each section is a meticulously crafted module, aimed at building a robust understanding of both the threats and the defenses in the cyber world. By the time you reach the final sections on secure protocols, applications, and testing infrastructure, you will have developed a holistic view of network security, ready to apply your knowledge in a variety of real-world scenarios. CompTIA Security+ is not just a course; it's a journey through the dynamic landscape of network security. As you progress from one section to another, you'll not only learn about securing individual systems and public servers but also about the importance of physical security in protecting digital assets. This course is a blend of theory and practicality, providing an in-depth understanding of the latest security tools and techniques. It's an opportunity to transform yourself into a sought-after professional in the cybersecurity domain, equipped with the knowledge to protect and defend against the ever-evolving cyber threats. Learning Outcomes Develop a comprehensive understanding of risk management strategies and their application in cybersecurity. Acquire proficiency in various cryptographic methods and their importance in securing data. Gain insights into effective identity and account management to enhance system security. Learn to utilize essential security tools for safeguarding individual and network systems. Master the skills to implement and manage security measures for both wired and wireless networks. Why buy this CompTIA Security+? 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. Certification After studying the course materials of the CompTIA Security+ there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? Individuals aiming to start a career in cybersecurity. IT professionals seeking to deepen their knowledge in network security. System administrators wanting to enhance their security skills. Students interested in acquiring a foundational understanding of cybersecurity principles. Professionals aiming to achieve the CompTIA Security+ certification for career advancement. Prerequisites This CompTIA Security+ does not require you to have any prior qualifications or experience. You can just enrol and start learning.This CompTIA Security+ 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. Career path Cybersecurity Analyst: £30,000 - £60,000 annually Information Security Manager: £40,000 - £75,000 annually Network Security Engineer: £35,000 - £65,000 annually Security Consultant: £35,000 - £70,000 annually Systems Administrator (with security specialization): £25,000 - £50,000 annually IT Security Coordinator: £28,000 - £55,000 annually Course Curriculum Section 01: Introduction Introduction to CompTIA Security+ SY0-601 00:03:00 About the CompTIA Security+ SY0-601 Exam 00:03:00 Section 02: Risk Management Defining Risk 00:08:00 Threats and Vulnerabilities 00:07:00 Threat Intelligence 00:11:00 Risk Management Concepts 00:07:00 Security Controls 00:09:00 Risk Assessments and Treatments 00:06:00 Quantitative Risk Assessments 00:07:00 Qualitative Risk Assessments 00:04:00 Business Impact Analysis 00:05:00 Data Types and Roles 00:11:00 Security and the Information Life Cycle 00:09:00 Data Destruction 00:06:00 Personnel Risk and Policies 00:10:00 Third-Party Risk Management 00:09:00 Agreement Types 00:07:00 Exam Question Review 00:02:00 Wiping Disks with the dd Command Lab 00:06:00 Ask Me Anything (AMA) 00:02:00 Section 03: Cryptography Cryptography Basics 00:16:00 Data Protection 00:09:00 Cryptographic Methods 00:07:00 Symmetric Cryptosystems 00:13:00 Symmetric Block Modes 00:08:00 Asymmetric Cryptosystems 00:13:00 Diffie-Hellman 00:07:00 Hashing 00:09:00 Understanding Digital Certificates 00:08:00 Trust Models 00:05:00 Public Key Infrastructure 00:04:00 Certificate Types 00:14:00 Touring Certificates 00:09:00 Cryptographic Attacks 00:05:00 Password Cracking 00:10:00 Password Cracking Demo 00:06:00 Exam Question Review 00:02:00 SSH Public Key Authentication Lab 00:09:00 Ask Me Anything (AMA) 00:02:00 Section 04: Identity and Account Management Identification, Authentication, and Authorization 00:08:00 Enabling Multifactor Authentication 00:05:00 Authorization 00:05:00 Accounting 00:05:00 Authentication Methods 00:14:00 Access Control Schemes 00:07:00 Account Management 00:13:00 Network Authentication 00:09:00 Identity Management Systems 00:06:00 Exam Question Review 00:02:00 Creating LInux Users and Groups Lab 00:06:00 Ask Me Anything (AMA) 00:01:00 Section 05: Tools of the Trade Touring the CLI 00:16:00 Shells 00:06:00 The Windows Command Line 00:05:00 Microsoft PowerShell 00:13:00 Linux Shells 00:12:00 Python Scripts 00:06:00 Windows Command-Line Tools 00:16:00 Linux Command-Line Tools 00:10:00 Network Scanners 00:05:00 Network Scanning with Nmap 00:09:00 Network Protocol Analyzers 00:08:00 Using Wireshark to Analyze Network Traffic 00:09:00 Using tcpdump to Analyze Network Traffic 00:08:00 Log Files 00:09:00 Centralized Logging 00:09:00 Configuring Linux Log Forwarding 00:08:00 Exam Question Review 00:03:00 Lunux Shell Script Lab 00:07:00 Nmap Lab 00:05:00 Ask Me Anything (AMA) 00:02:00 Section 06: Securing Individual Systems Malware 00:14:00 Weak Configurations 00:12:00 Common Attacks 00:09:00 Driver and Overflow Attacks 00:08:00 Password Attacks 00:08:00 Bots and Botnets 00:06:00 Disk RAID Levels 00:10:00 Securing Hardware 00:11:00 Securing Endpoints 00:09:00 Exam Question Review 00:02:00 Linux Software RAID Lab 00:08:00 Ask Me Anything (AMA) 00:02:00 Section 07: The Basic LAN The OSI Model 00:13:00 ARP Cache Poisoning 00:09:00 Other Layer 2 Attacks 00:05:00 Network Planning 00:07:00 Load Balancing 00:06:00 Securing Network Access 00:06:00 Honeypots 00:06:00 Firewalls 00:08:00 Proxy Servers 00:06:00 Network and Port Address Translation 00:07:00 IP Security (IPsec) 00:09:00 Virtual Private Networks (VPNs) 00:10:00 Intrusion Detection and Prevention Systems (IDS/IPS) 00:13:00 Exam Question Review 00:03:00 Linux Snort IDS Lab 00:07:00 Ask Me Anything (AMA) 00:01:00 Section 08: Securing Wireless LANs Wi-Fi Encryption Standards 00:10:00 RFID, NFC, and Bluetooth 00:07:00 Wi-Fi Coverage and Performance 00:08:00 Wi-Fi Discovery and Attacks 00:12:00 Cracking WPA2 00:10:00 Wi-Fi Hardening 00:11:00 Exam Question Review 00:02:00 WPA2 Cracking Lab 00:06:00 Ask Me Anything (AMA) 00:01:00 Section 09: Securing Public Servers Defining a Public Server 00:01:00 Common Attacks and Mitigations 00:10:00 Containers and Software-Defined Networking 00:11:00 Hypervisors and Virtual Machines 00:08:00 Cloud Deployment Models 00:09:00 Cloud Service Models 00:08:00 Securing the Cloud 00:10:00 Exam Question Review 00:02:00 Docker Container Lab 00:04:00 Ask Me Anything (AMA) 00:02:00 Section 10: Securing Dedicated Systems Embedded Systems 00:13:00 Industrial Control System (ICS) 00:07:00 Internet of Things (IoT) Devices 00:10:00 Connecting to Dedicated and Mobile Systems 00:11:00 Security Constraints for Dedicated Systems 00:05:00 Mobile Device Deployment and Hardening 00:11:00 Exam Question Review 00:03:00 Smartphone Hardening Lab 00:03:00 Ask Me Anything (AMA) 00:02:00 Section 11: Physical Security Physical Security Overview 00:01:00 Physical Security 00:10:00 Keylogger Demo 00:05:00 Environmental Controls 00:05:00 Exam Question Review 00:02:00 Physical Security Lab 00:03:00 Ask Me Anything (AMA) 00:03:00 Section 12: Secure Protocols and Applications DNS Security 00:05:00 FTP Packet Capture 00:03:00 Secure Web and E-mail 00:12:00 Request Forgery Attacks 00:05:00 Cross-Site Scripting Attacks 00:07:00 Web Application Security 00:08:00 Web App Vulnerability Scanning 00:06:00 Exam Question Review 00:03:00 OWASP ZAP Web App Scan Lab 00:04:00 Ask Me Anything (AMA) 00:02:00 Section 13: Testing Infrastructure Testing Infrastructure Overview 00:05:00 Social Engineering 00:06:00 Social Engineering Attacks 00:11:00 Vulnerability Assessments 00:09:00 Penetration Testing 00:10:00 Security Assessment Tools 00:12:00 The Metasploit Framework 00:08:00 Exam Question Review 00:02:00 Hping3 Forged Packet Lab 00:06:00 Ask Me Anything (AMA) 00:02:00 Section 14: Dealing with Incidents Incident Response Overview 00:03:00 Incident Response Plans (IRPs) 00:06:00 Threat Analysis and Mitigating Actions 00:08:00 Digital Forensics 00:10:00 Gathering Digital Evidence 00:10:00 Business Continuity and Alternate Sites 00:06:00 Data Backup 00:10:00 Exam Question Review 00:01:00 Autopsy Forensic Browser Lab 00:05:00 Ask Me Anything (AMA) 00:02:00 Assignment Assignment - CompTIA Security+ 00:00:00

Develop essential critical thinking and problem-solving skills with our comprehensive guide. Enhance your ability to analyze, evaluate, and solve complex challenges. Unlock a powerful toolkit for success in academics, professional endeavors, and everyday life. Explore practical strategies and gain a competitive edge in decision-making. Elevate your cognitive abilities with this indispensable resource for personal and professional growth.