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Course Curriculum Cyber Security Basics Introduction 00:30:00 Child Safety Online 01:00:00 Secure Payment Sites 01:00:00 Online Banking 00:30:00 How To Keep Your Password Safe 00:30:00 Common Scams 01:00:00 How I Got Pharmed 01:00:00 Virus Protection 01:00:00 Self Maintenance 00:30:00 Personal Information Online 01:00:00 Is The Internet Safe? 00:30:00 Importance of Cyber Security 00:30:00 Internet Security Management Internet Security- The Truth About Identify Theft 01:00:00 Internet Security for Teens- What You Need to Do 01:00:00 Internet Security-Downloading Email Attachments 00:15:00 Internet Security- 5 Tips for Using Facebook 00:30:00 Internet Security- 8 Tips to Protect Yourself When Dating Online 00:30:00 Internet Security for Teens and Tweens- 10 Tips to Keep You Protected 00:15:00 Internet Security- Parental Control Software 00:30:00 Internet Security- Online Safety for Your Children 00:30:00 Cyber Bullying- Another Aspect of Breaking Internet Security 00:30:00 Tips to Ensure Internet Security 00:30:00 Internet Security- Downloading Music off the Internet 01:00:00 Internet Security- Protect Your Wireless Connection 00:30:00 Internet Security- How to Deal with Spyware 00:15:00 Internet Security- Protecting Yourself When You Shop Online 00:15:00 Internet Security- Make Sure Your Passwords Protect You 00:15:00 Make Sure Your Emails Are Safe: Tips for Internet Security 01:00:00 Internet Security- Why Should You Use a Firewall? 01:00:00 Internet security-Signs That Your Child's Safety Might Be Compromised 01:00:00 Internet Security- Safety When Using Public Computers 01:00:00 Internet Security- Storing Your Password on Your Computer 01:00:00 Internet Security-Using Social Utility Sites 00:30:00 IT Security Spyware Can Destroy 00:30:00 How Does Spyware Spread? 01:00:00 How To Remove Spyware 01:00:00 Anti Spyware Program 01:00:00 The Anti Anti-Spyware Programs 00:30:00 Research And Learn More 00:30:00 Choosing The Best Anti Spyware Tool 01:00:00 Computer Security And Spyware 01:00:00 The Programs To Avoid 00:15:00 Is It Legal? 00:30:00 Checklist Of Protection 00:15:00 Recommended Reading Recommended Reading : Cyber Security Advanced Diploma 00:00:00 Mock Exam Mock Exam - Cyber Security Advanced Diploma 00:30:00 Final Exam Final Exam - Cyber Security Advanced Diploma 00:30:00
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
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