21553 Courses

The 'Electrical Circuits Laws and Methods' course is designed to provide a comprehensive understanding of electric circuits, laws, and analytical methods. It covers fundamental concepts, basic laws, methods of analysis, circuit theorems, operational amplifiers, and capacitors and inductors. Students will learn essential principles to analyze and design electrical circuits effectively. Learning Outcomes: Understand the basic concepts of electric circuits, including electric charge, current, voltage, power, and energy. Apply Ohm's Law and other basic laws to analyze resistive circuits and determine currents and voltages. Use nodal and mesh analysis methods to analyze and solve complex electrical circuits with various sources. Apply circuit theorems such as the Superposition Theorem, Thevenin's Theorem, and Norton's Theorem to simplify circuit analysis. Comprehend the properties and applications of operational amplifiers in various amplifier configurations. Analyze capacitors and inductors in DC circuits, calculate their stored energy, and understand their equivalent capacitance and inductance in series and parallel configurations. Why buy this Electrical Circuits Laws and Methods? 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 Electrical Circuits Laws and Methods 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? The Electrical Circuits Laws and Methods course is designed for undergraduate and graduate electrical engineering students as a foundational study of circuit theory. It is suitable for electronics enthusiasts eager to grasp the functioning and design of electrical circuits for various applications. Engineering technicians and technologists working in fields like telecommunications and manufacturing can benefit from this course to better understand and troubleshoot electrical circuits in practical settings. Electrical technicians and electricians can enhance their problem-solving abilities and theoretical knowledge of electrical circuits by taking this course. Hobbyists and DIY enthusiasts interested in electronics projects will find value in learning circuit design and troubleshooting through this course. Professionals in engineering and related fields can use this course for continuing education to refresh their knowledge and stay up-to-date with advancements in electrical circuit theory and methods. Prerequisites This Electrical Circuits Laws and Methods does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Electrical Circuits Laws and Methods 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 Electrical Engineer: £28,000 - £70,000 per year Electronics Engineer: £30,000 - £75,000 per year Electrician: £24,000 - £45,000 per year Power Systems Engineer: £32,000 - £80,000 per year Telecommunications Engineer: £28,000 - £70,000 per year Automation and Control Systems Engineer: £35,000 - £80,000 per year Course Curriculum Unit 1- Basic Concepts Module 1- What Is an Electric Circuit 00:02:00 Module 2-System of Units 00:07:00 Module 3- What Is an Electric Charge 00:05:00 Module 4- What Is an Electric Current 00:08:00 Module 5-Example 1 00:01:00 Module 6- Example 2 00:02:00 Module 7- Example 3 00:02:00 Module 8- What Is Voltage 00:07:00 Module 9- What Is Power 00:06:00 Module 10- What Is Energy 00:04:00 Module 11- Example 4 00:03:00 Module 12-Example 5 00:03:00 Module 13- Dependent and Independent Sources 00:05:00 Module 14- Example 6 Part 1 00:04:00 Module 15- Example 6 Part 2 00:01:00 Module 16- Application 1 Cathode Ray Tube 00:04:00 Module 17-Example 10 00:03:00 Module 18- Application 2 Electricity Bills 00:02:00 Module 19- Example 8 00:03:00 Unit 2- Basic Laws Module 1- Introduction to Basic Laws 00:01:00 Module 2- Definition of Resistance 00:06:00 Module 3- Ohm's Law 00:02:00 Module 4- Types of Resistances 00:06:00 Module 5- Open and Short Circuit 00:05:00 Module 6- Definition of Conductance 00:04:00 Module 7-Example 1 00:01:00 Module 8- Example 2 00:03:00 Module 9- Example 3 00:03:00 Module 10- Branch, Node and Loops 00:07:00 Module 11- Series and Parallel Connection 00:04:00 Module 12- KCL 00:04:00 Module 13- KVL 00:03:00 Module 14- Example 4 00:05:00 Module 15- Example 5 00:02:00 Module 16- Example 6 00:06:00 Module 17- Series Resistors and Voltage Division 00:07:00 Module 18-Parallel Resistors and Current Division 00:12:00 Module 19- Analogy between Resistance and Conductance 00:07:00 Module 20-Example 7 00:03:00 Module 21-Example 8 00:04:00 Module 22- Introduction to Delta-Wye Connection 00:06:00 Module 23-Delta to Wye Transformation 00:05:00 Module 24- Wye to Delta Transformation 00:07:00 Module 25-Example 9 00:03:00 Module 26- Example 10 00:15:00 Module 27- Application Lighting Bulbs 00:03:00 Module 28-Example 11 00:05:00 Unit 3- Methods of Analysis Module 1- Introduction to Methods of Analysis 00:02:00 Module 2- Nodal Analysis with No Voltage Source 00:15:00 Module 3-Example 1 00:04:00 Module 4-Cramer's Method 00:04:00 Module 5-Nodal Analysis with Voltage Source 00:07:00 Module 6- Example 2 00:05:00 Module 7- Example 3 00:13:00 Module 8-Mesh Analysis with No Current Source 00:10:00 Module 9-Example 4 00:04:00 Module 10- Example 5 00:06:00 Module 11-Mesh Analysis with Current Source 00:07:00 Module 12-Example 6 00:08:00 Module 13-Nodal Vs Mesh Analysis 00:04:00 Module 14-Application DC Transistor 00:04:00 Module 15-Example 7 00:04:00 Unit 4- Circuit Theorems Module 1-Introduction to Circuit theorems 00:02:00 Module 2-Linearity of Circuit 00:07:00 Module 3-Example 1 00:04:00 Module 4-Superposition Theorem 00:07:00 Module 5- Example 2 00:04:00 Module 6-Example 3 00:06:00 Module 7-Source Transformation 00:08:00 Module 8-Example 4 00:05:00 Module 9-Example 5 00:03:00 Module 10-Thevenin Theorem 00:10:00 Module 11-Example 6 00:06:00 Module 12-Example 7 00:05:00 Module 13- Norton's Theorem 00:05:00 Module 14-Example 8 00:03:00 Module 15-Example 9 00:05:00 Module 16-Maximum Power Transfer 00:05:00 Module 17-Example 10 00:03:00 Module 18-Resistance Measurement 00:05:00 Module 19-Example 11 00:01:00 Module 20-Example 12 00:04:00 Module 21-Summary 00:05:00 Unit 5- Operational Amplifiers Module 1-Introduction to Operational Amplifiers 00:03:00 Module 2-Construction of Operational Amplifiers 00:07:00 Module 3-Equivalent Circuit of non Ideal Op Amp 00:10:00 Module 4-Vo Vs Vd Relation Curve 00:03:00 Module 5-Example 1 00:09:00 Module 6-Ideal Op Amp 00:07:00 Module 7- Example 2 00:04:00 Module 8-Inverting Amplifier 00:05:00 Module 9-Example 3 00:05:00 Module 10-Example 4 00:02:00 Module 11-Non Inverting Amplifier 00:08:00 Module 12-Example 5 00:03:00 Module 13-Summing Amplifier 00:05:00 Module 14-Example 6 00:02:00 Module 15-Difference amplifier 00:06:00 Module 16-Example 7 00:08:00 Module 17-Cascaded Op Amp Circuits 00:06:00 Module 18-Example 8 00:04:00 Module 19-Application Digital to Analog Converter 00:06:00 Module 20-Example 9 00:04:00 Module 21-Instrumentation Amplifiers 00:05:00 Module 22-Example 10 00:01:00 Module 23-Summary 00:04:00 Unit 6- Capacitors and Inductors Module 1-Introduction to Capacitors and Inductors 00:02:00 Module 2-Capacitor 00:06:00 Module 3-Capacitance 00:02:00 Module 4-Voltage-Current Relation in Capacitor 00:03:00 Module 5-Energy Stored in Capacitor 00:06:00 Module 6-DC Voltage and Practical Capacitor 00:02:00 Module 7-Example 1 00:01:00 Module 8-Example 2 00:01:00 Module 9-Example 3 00:05:00 Module 10-Equivalent Capacitance of Parallel Capacitors 00:02:00 Module 11-Equivalent Capacitance of Series Capacitors 00:03:00 Module 12-Example 4 00:02:00 Module 13-Definition of Inductors 00:06:00 Module 14-Definition of Inductance 00:03:00 Module 15-Voltage-Current Relation in Inductor 00:03:00 Module 16-Power and Energy Stored in Inductor 00:02:00 Module 17-DC Source and Inductor 00:04:00 Module 18-Example 5 00:02:00 Module 19-Series Inductors 00:03:00 Module 20-Parallel Inductors 00:04:00 Module 21-Example 6 00:01:00 Module 22-Small Summary to 3 Basic Elements 00:02:00 Module 23-Example 7 00:05:00 Module 24-Application Integrator 00:05:00 Module 25-Example 8 00:03:00 Module 26-Application Differentiator 00:02:00 Module 27-Example 9 00:06:00 Module 28-Summary 00:05:00 Assignment Assignment - Electrical Circuits Laws and Methods 00:00:00

Delve into the world of data analysis with 'R Programming for Data Science,' a course designed to guide learners through the intricacies of R, a premier programming language in the data science domain. The course opens with a broad perspective on data science, illuminating the pivotal role of R in this field. Learners are then introduced to R and RStudio, equipping them with the foundational tools and interfaces essential for R programming. The curriculum progresses with an introduction to the basics of R, ensuring learners grasp the core principles that underpin more complex operations. A highlight of this course is its in-depth exploration of R's versatile data structures, including vectors, matrices, factors, and data frames. Each unit is crafted to provide learners with a comprehensive understanding of these structures, pivotal for effective data handling and manipulation. The course also emphasizes the importance of relational and logical operators in R, key elements for executing data operations. As the course advances, learners will engage with the nuances of conditional statements and loops, essential for writing efficient and dynamic R scripts. Moving into more advanced territories, the course delves into the creation and usage of functions, an integral part of R programming, and the exploration of various R packages that extend the language's capabilities. Learners will also gain expertise in the 'apply' family of functions, crucial for streamlined data processing. Further units cover regular expressions and effective strategies for managing dates and times in data sets. The course concludes with practical applications in data acquisition, cleaning, visualization, and manipulation, ensuring learners are well-prepared to tackle real-world data science challenges using R. Learning Outcomes Develop a foundational understanding of R's role in data science and proficiency in RStudio. Gain fluency in R programming basics, enabling the handling of complex data tasks. Acquire skills in managing various R data structures for efficient data analysis. Master relational and logical operations for advanced data manipulation in R. Learn to create functions and utilize R packages for expanded analytical capabilities. Why choose this R Programming for Data Science 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 R Programming for Data Science course for? Beginners in data science eager to learn R programming. Data analysts and scientists looking to enhance their skills in R. Researchers in various fields requiring advanced data analysis tools. Statisticians seeking to adopt R for more sophisticated data manipulations. Professionals in finance, healthcare, and other sectors needing data-driven insights. Career path Data Scientist (R Expertise): £30,000 - £70,000 Data Analyst (R Programming Skills): £27,000 - £55,000 Bioinformatics Scientist (R Proficiency): £35,000 - £60,000 Quantitative Analyst (R Knowledge): £40,000 - £80,000 Research Analyst (R Usage): £25,000 - £50,000 Business Intelligence Developer (R Familiarity): £32,000 - £65,000 Prerequisites This R Programming for Data Science does not require you to have any prior qualifications or experience. You can just enrol and start learning.This R Programming for Data Science 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 Unit 01: Data Science Overview Introduction to Data Science 00:01:00 Data Science: Career of the Future 00:04:00 What is Data Science? 00:02:00 Data Science as a Process 00:02:00 Data Science Toolbox 00:03:00 Data Science Process Explained 00:05:00 What's next? 00:02:00 Unit 02: R and RStudio Engine and coding environment 00:03:00 Installing R and RStudio 00:04:00 RStudio: A quick tour 00:04:00 Unit 03: Introduction to Basics Arithmetic with R 00:03:00 Variable assignment 00:04:00 Basic data types in R 00:03:00 Unit 04: Vectors Creating a vector 00:05:00 Naming a vector 00:04:00 Arithmetic calculations on vectors 00:07:00 Vector selection 00:06:00 Selection by comparison 00:04:00 Unit 05: Matrices What's a Matrix? 00:02:00 Analyzing Matrices 00:03:00 Naming a Matrix 00:05:00 Adding columns and rows to a matrix 00:06:00 Selection of matrix elements 00:03:00 Arithmetic with matrices 00:07:00 Additional Materials 00:00:00 Unit 06: Factors What's a Factor? 00:02:00 Categorical Variables and Factor Levels 00:04:00 Summarizing a Factor 00:01:00 Ordered Factors 00:05:00 Unit 07: Data Frames What's a Data Frame? 00:03:00 Creating Data Frames 00:20:00 Selection of Data Frame elements 00:03:00 Conditional selection 00:03:00 Sorting a Data Frame 00:03:00 Additional Materials 00:00:00 Unit 08: Lists Why would you need lists? 00:01:00 Creating a List 00:06:00 Selecting elements from a list 00:03:00 Adding more data to the list 00:02:00 Additional Materials 00:00:00 Unit 09: Relational Operators Equality 00:03:00 Greater and Less Than 00:03:00 Compare Vectors 00:03:00 Compare Matrices 00:02:00 Additional Materials 00:00:00 Unit 10: Logical Operators AND, OR, NOT Operators 00:04:00 Logical operators with vectors and matrices 00:04:00 Reverse the result: (!) 00:01:00 Relational and Logical Operators together 00:06:00 Additional Materials 00:00:00 Unit 11: Conditional Statements The IF statement 00:04:00 IFELSE 00:03:00 The ELSEIF statement 00:05:00 Full Exercise 00:03:00 Additional Materials 00:00:00 Unit 12: Loops Write a While loop 00:04:00 Looping with more conditions 00:04:00 Break: stop the While Loop 00:04:00 What's a For loop? 00:02:00 Loop over a vector 00:02:00 Loop over a list 00:03:00 Loop over a matrix 00:04:00 For loop with conditionals 00:01:00 Using Next and Break with For loop 00:03:00 Additional Materials 00:00:00 Unit 13: Functions What is a Function? 00:02:00 Arguments matching 00:03:00 Required and Optional Arguments 00:03:00 Nested functions 00:02:00 Writing own functions 00:03:00 Functions with no arguments 00:02:00 Defining default arguments in functions 00:04:00 Function scoping 00:02:00 Control flow in functions 00:03:00 Additional Materials 00:00:00 Unit 14: R Packages Installing R Packages 00:01:00 Loading R Packages 00:04:00 Different ways to load a package 00:02:00 Additional Materials 00:00:00 Unit 15: The Apply Family - lapply What is lapply and when is used? 00:04:00 Use lapply with user-defined functions 00:03:00 lapply and anonymous functions 00:01:00 Use lapply with additional arguments 00:04:00 Additional Materials 00:00:00 Unit 16: The apply Family - sapply & vapply What is sapply? 00:02:00 How to use sapply 00:02:00 sapply with your own function 00:02:00 sapply with a function returning a vector 00:02:00 When can't sapply simplify? 00:02:00 What is vapply and why is it used? 00:04:00 Additional Materials 00:00:00 Unit 17: Useful Functions Mathematical functions 00:05:00 Data Utilities 00:08:00 Additional Materials 00:00:00 Unit 18: Regular Expressions grepl & grep 00:04:00 Metacharacters 00:05:00 sub & gsub 00:02:00 More metacharacters 00:04:00 Additional Materials 00:00:00 Unit 19: Dates and Times Today and Now 00:02:00 Create and format dates 00:06:00 Create and format times 00:03:00 Calculations with Dates 00:03:00 Calculations with Times 00:07:00 Additional Materials 00:00:00 Unit 20: Getting and Cleaning Data Get and set current directory 00:04:00 Get data from the web 00:04:00 Loading flat files 00:03:00 Loading Excel files 00:05:00 Additional Materials 00:00:00 Unit 21: Plotting Data in R Base plotting system 00:03:00 Base plots: Histograms 00:03:00 Base plots: Scatterplots 00:05:00 Base plots: Regression Line 00:03:00 Base plots: Boxplot 00:03:00 Unit 22: Data Manipulation with dplyr Introduction to dplyr package 00:04:00 Using the pipe operator (%>%) 00:02:00 Columns component: select() 00:05:00 Columns component: rename() and rename_with() 00:02:00 Columns component: mutate() 00:02:00 Columns component: relocate() 00:02:00 Rows component: filter() 00:01:00 Rows component: slice() 00:04:00 Rows component: arrange() 00:01:00 Rows component: rowwise() 00:02:00 Grouping of rows: summarise() 00:03:00 Grouping of rows: across() 00:02:00 COVID-19 Analysis Task 00:08:00 Additional Materials 00:00:00 Assignment Assignment - R Programming for Data Science 00:00:00

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

Take on a journey through the dynamic realm of aviation infrastructure with our comprehensive course. Unveil the intricate tapestry that weaves together the core concepts of airport management, a tapestry that extends far beyond the runway. Imagine immersing yourself in a world where each module serves as a gateway to understanding the pulse of passenger terminal operations, ensuring seamless journeys for those who traverse the skies. Key Features: This Aviation Infrastructure Administration and Management Course Includes: CPD Certified Developed by Specialist Lifetime Access You'll be equipped with the expertise to master optimal timing and scheduling practices, orchestrating a harmonious symphony of arrivals and departures that dance to the beat of precision. As you delve deeper, unravel the secrets of efficient freight management, where the tiniest delay can have a domino effect across the aviation landscape. Tackle challenges head-on, from the buzz of aviation noise to the intricate dance with climate influences and weather management. Picture yourself at the forefront of sustainable practices, implementing strategies that echo through the corridors of airport operations. Elevate your understanding of security measures to new heights, ensuring the safety of the skies. Navigate the expansive horizons of aviation expansion, where each decision shapes the future of this ever-evolving industry. Join us on a transformative journey, where knowledge takes flight, and your expertise becomes the guiding force behind the seamless operations of the aviation world. Course Curriculum Aviation Infrastructure Administration and Management Module 01: Exploring Airport Management Concepts Module 02: Effective Customer Service Strategies Module 03: Oversight of Passenger Terminal Operations Module 04: Elements of Airport Infrastructure Module 05: Optimal Timing and Scheduling Practices Module 06: Efficient Freight Management Module 07: Addressing Aviation Noise Challenges Module 08: Climate Influence and Weather Management Module 09: Sustainable Practices in Airport Operations Module 10: Enhancing Security Measures Module 11: Navigating Aviation Expansion Learning Outcomes: Aviation Infrastructure Administration and Management Analyse key concepts in airport management for effective administration strategies. Apply customer service techniques to enhance the passenger experience at airports. Demonstrate oversight skills in managing passenger terminal operations efficiently. Identify and evaluate elements crucial to the functioning of airport infrastructure. Implement optimal timing and scheduling practices in aviation operations. Address aviation noise challenges and mitigate their impact on airport operations. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Aviation Infrastructure Administration and Management Airport managers seeking advanced insights into aviation infrastructure administration. Aviation professionals aiming to enhance customer service and operational efficiency skills. Individuals involved in passenger terminal operations and oversight roles. Freight management personnel interested in optimising air cargo logistics. Environmental enthusiasts keen on sustainable airport practices and climate management. Career path Aviation Infrastructure Administration and Management Airport Operations Manager Customer Service Manager in Aviation Passenger Terminal Operations Supervisor Airport Infrastructure Analyst Aviation Environmental Compliance Specialist Security Measures Coordinator in Aviation Certificates Digital certificate Digital certificate - Included Will be downloadable when all lectures have been completed.

Take on a journey through the dynamic realm of aviation infrastructure with our comprehensive course. Unveil the intricate tapestry that weaves together the core concepts of airport management, a tapestry that extends far beyond the runway. Imagine immersing yourself in a world where each module serves as a gateway to understanding the pulse of passenger terminal operations, ensuring seamless journeys for those who traverse the skies. Key Features: This Aviation Infrastructure Administration and Management Course Includes: CPD Certified Developed by Specialist Lifetime Access You'll be equipped with the expertise to master optimal timing and scheduling practices, orchestrating a harmonious symphony of arrivals and departures that dance to the beat of precision. As you delve deeper, unravel the secrets of efficient freight management, where the tiniest delay can have a domino effect across the aviation landscape. Tackle challenges head-on, from the buzz of aviation noise to the intricate dance with climate influences and weather management. Picture yourself at the forefront of sustainable practices, implementing strategies that echo through the corridors of airport operations. Elevate your understanding of security measures to new heights, ensuring the safety of the skies. Navigate the expansive horizons of aviation expansion, where each decision shapes the future of this ever-evolving industry. Join us on a transformative journey, where knowledge takes flight, and your expertise becomes the guiding force behind the seamless operations of the aviation world. Course Curriculum Aviation Infrastructure Administration and Management Module 01: Exploring Airport Management Concepts Module 02: Effective Customer Service Strategies Module 03: Oversight of Passenger Terminal Operations Module 04: Elements of Airport Infrastructure Module 05: Optimal Timing and Scheduling Practices Module 06: Efficient Freight Management Module 07: Addressing Aviation Noise Challenges Module 08: Climate Influence and Weather Management Module 09: Sustainable Practices in Airport Operations Module 10: Enhancing Security Measures Module 11: Navigating Aviation Expansion Learning Outcomes: Aviation Infrastructure Administration and Management Analyse key concepts in airport management for effective administration strategies. Apply customer service techniques to enhance the passenger experience at airports. Demonstrate oversight skills in managing passenger terminal operations efficiently. Identify and evaluate elements crucial to the functioning of airport infrastructure. Implement optimal timing and scheduling practices in aviation operations. Address aviation noise challenges and mitigate their impact on airport operations. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Aviation Infrastructure Administration and Management Airport managers seeking advanced insights into aviation infrastructure administration. Aviation professionals aiming to enhance customer service and operational efficiency skills. Individuals involved in passenger terminal operations and oversight roles. Freight management personnel interested in optimising air cargo logistics. Environmental enthusiasts keen on sustainable airport practices and climate management. Career path Aviation Infrastructure Administration and Management Airport Operations Manager Customer Service Manager in Aviation Passenger Terminal Operations Supervisor Airport Infrastructure Analyst Aviation Environmental Compliance Specialist Security Measures Coordinator in Aviation Certificates Digital certificate Digital certificate - Included Will be downloadable when all lectures have been completed.

Empower yourself with essential knowledge to ensure passenger safety and uphold community trust. Our comprehensive course equips you with the necessary skills to navigate safeguarding responsibilities effectively. Key Features: CPD Certified Free Certificate Developed by Specialist Lifetime Access In the "Safeguarding for Taxi Drivers" course, learners will gain essential knowledge and skills to ensure passenger safety and well-being. They will understand their responsibilities in safeguarding passengers, including vulnerable groups. Learners will grasp key principles of safeguarding, learning how to recognize signs of abuse and respond appropriately to safeguarding concerns. They will also explore current issues affecting safeguarding in the context of taxi services. By the end of the course, learners will be equipped with practical insights and strategies to create a safe and secure environment for passengers, enhancing their professionalism and ensuring compliance with safeguarding regulations. Course Curriculum Module 01: Introduction to Safeguarding for Taxi Drivers Module 02: Understanding Your Safeguarding Responsibilities Module 03: Understanding Key Safeguarding Principles Module 04: Understanding Abuse Module 05: Current Issues in Safeguarding Learning Outcomes: Understand safeguarding principles to ensure passenger safety and well-being. Recognize signs of abuse and how to respond appropriately. Demonstrate awareness of current issues affecting taxi driver safeguarding. Explain the responsibilities involved in safeguarding as a taxi driver. Apply key safeguarding principles in real-life driving scenarios. Evaluate personal understanding of safeguarding through practical assessments. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Taxi drivers seeking to enhance passenger safety awareness. Individuals aspiring to become licensed taxi drivers in the UK. Taxi company operators managing driver training and compliance. Local authorities and regulators overseeing taxi driver standards. Anyone interested in safeguarding practices within the transportation sector. Career path Taxi Driver Private Hire Driver Taxi Company Operator Local Authority Licensing Officer Safeguarding Trainer Transport Compliance Officer Certificates Digital certificate Digital certificate - Included Certificate of Completion Digital certificate - Included Will be downloadable when all lectures have been completed.

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Cyber security is of paramount importance in the digital age, serving as a vital shield against ever-evolving Cyber security threats. In the UK, its significance is underscored by a burgeoning demand fueled by a surge in Cyber security attacks and digital vulnerabilities. With a projected increase of 25% in cyber incidents annually, the need for skilled cyber security professionals is escalating rapidly. This demand translates into abundant job opportunities across various sectors, ranging from government agencies to private enterprises. Moreover, cyber security roles offer competitive salaries, with entry-level positions starting at around £30,000 per year and experienced professionals commanding salaries well over £60,000 annually. Embracing a career in cyber security not only presents a chance to contribute to safeguarding digital infrastructure but also offers the prospect of a lucrative and rewarding profession in a field that is continually expanding and evolving. Key Features This Level 2 Diploma in Cyber Security Course Includes: This Level 2 Diploma in Cyber Security Course is CPD Certified Free Certificate Level 2 Diploma Developed by Specialist Lifetime Access From our Cyber security course, you will learn about cyber security, cyber attacks types, cybercrimes overview & password management . So, stand out in the job market by completing the Cyber Security course. Get an certificate and add it to your resume to impress your employers. Course Curriculum Level 2 Diploma in Cyber Security Course: Module 01: Fundamentals of Cyber Security Module 02: Types of Cyber Attacks Module 03: Cybercrimes Overview Module 04: Cyber Security and Data Breach Incidents Module 05: Best Practices in Password Management Learning Outcomes Diploma in Cyber Security Level 2 & 3 Course : Understanding Cyber Threats: Recognize various cyber threats and their implications on Cyber security. Cybercrime Awareness: Grasp the concepts and types of cybercrimes prevalent today. Data Breach Management: Acquire skills to respond to and prevent data breaches. Effective Password Practices: Implement secure password management techniques proficiently. Safe Internet Navigation: Demonstrate safe internet browsing practices for personal and professional use. Security in Remote Work: Apply Cyber security measures for office and remote work environments effectively. Certification After completing this Diploma in Cyber Security Level 2 & 3course, you will get a free certificate. 10 CPD hours / points Accredited by The CPD Quality Standards (CPD QS) Who is this course for? Level 2 Diploma in Cyber Security Course Individuals aspiring to enter the cyber security field. Employees seeking to enhance their cyber security awareness. IT professionals aiming to specialise in cyber security. Students pursuing a career in information technology or cyber security. Anyone concerned about personal and professional cyber security. NB: This Course doesn't provide any professional qualifications. For professional qualifications, you may like to choose: Level 2 Diploma in Business Beginners in Cyber Security Level 4 Diploma in Cyber Security Level 5 Diploma in Cyber Security NCFE Level 2 Certificate in the Principles of Cyber Security Level 3 Diploma in Cyber Security Management and Operations Career path Level 2 Diploma in Cyber Security Course Cyber Security Analyst IT Security Consultant Network Security Engineer Incident Response Specialist Data Security Administrator Security Compliance Officer Certificates Certificate of Completion Digital certificate - Included Will be downloadable when all lectures have been completed.