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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

Overview This Nutrition : Build Your Diet Plan course will unlock your full potential and will show you how to excel in a career in Nutrition : Build Your Diet Plan. So upskill now and reach your full potential. Everything you need to get started in Nutrition : Build Your Diet Plan is available in this course. Learning and progressing are the hallmarks of personal development. This Nutrition : Build Your Diet Plan will quickly teach you the must-have skills needed to start in the relevant industry. In This Nutrition : Build Your Diet Plan Course, You Will: Learn strategies to boost your workplace efficiency. Hone your Nutrition : Build Your Diet Plan skills to help you advance your career. Acquire a comprehensive understanding of various Nutrition : Build Your Diet Plan topics and tips from industry experts. Learn in-demand Nutrition : Build Your Diet Plan skills that are in high demand among UK employers, which will help you to kickstart your career. This Nutrition : Build Your Diet Plan course covers everything you must know to stand against the tough competition in the Nutrition : Build Your Diet Plan field.  The future is truly yours to seize with this Nutrition : Build Your Diet Plan. Enrol today and complete the course to achieve a Nutrition : Build Your Diet Plan certificate that can change your professional career forever. Additional Perks of Buying a Course From Institute of Mental Health Study online - whenever and wherever you want. One-to-one support from a dedicated tutor throughout your course. Certificate immediately upon course completion 100% Money back guarantee Exclusive discounts on your next course purchase from Institute of Mental Health Enrolling in the Nutrition : Build Your Diet Plan course can assist you in getting into your desired career quicker than you ever imagined. So without further ado, start now. Process of Evaluation After studying the Nutrition : Build Your Diet Plan course, your skills and knowledge will be tested with a MCQ exam or assignment. You must get a score of 60% to pass the test and get your certificate.  Certificate of Achievement Upon successfully completing the Nutrition : Build Your Diet Plan course, you will get your CPD accredited digital certificate immediately. And you can also claim the hardcopy certificate completely free of charge. All you have to do is pay a shipping charge of just £3.99. Who Is This Course for? This Nutrition : Build Your Diet Plan is suitable for anyone aspiring to start a career in Nutrition : Build Your Diet Plan; even if you are new to this and have no prior knowledge on Nutrition : Build Your Diet Plan, this course is going to be very easy for you to understand.  And if you are already working in the Nutrition : Build Your Diet Plan field, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  Taking this Nutrition : Build Your Diet Plan course is a win-win for you in all aspects.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements This Nutrition : Build Your Diet Plan course has no prerequisite.  You don't need any educational qualification or experience to enrol in the Nutrition : Build Your Diet Plan course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online Nutrition : Build Your Diet Plan course. Moreover, this course allows you to learn at your own pace while developing transferable and marketable skills. Course Curriculum Introduction Welcome To The Course & What You Will Learn FREE 00:04:00 Get to Know Your Instructor 00:03:00 Meal Planning Basics Meal Planning Explained 00:04:00 Calories Explained 00:04:00 Micronutrients Introduction 00:01:00 Protein Explained 00:02:00 How much protein do you need to consume per day 00:04:00 Fats explained 00:03:00 How Much Fat Should You Eat Per Day 00:04:00 Carbohydrate Explained 00:03:00 Macronutrients Explained 00:01:00 The Different Types of carbs 00:05:00 How Much Carbs should you eat per day 00:03:00 Meal Timing Intro 2 copy 00:01:00 Protein Timing 00:04:00 Carbohydrate Timing 00:02:00 Fat Timing 00:01:00 Pre-Workout Meal 00:04:00 Post Workout Meal 00:02:00 What About the Anabolic Window 00:01:00 Food Composition Introduction 2 copy 00:02:00 Protein Composition 00:02:00 Carbohydrate Composition 00:03:00 Fat Composition 00:01:00 Supplements Top 3 Beginner Supplements 00:04:00 How to Use Protein Powder When, How Much & With What 00:06:00 How to Use Creatine When,How Much & With What 00:04:00 Other Supplements to consider 00:05:00 Setting Up Your Diet How To Determin Your Optimal Calorie Intake 2 00:03:00 How to Track Calories 00:05:00 Determining Protein Intake 00:01:00 Determining Fat Intake 00:01:00 What About the Ramaining Calories 00:02:00 Determining Meal Structure 00:03:00 Quality Protein Sources 00:01:00 Quality Carbs Sources 00:01:00 Quality Sources Of Fat 00:01:00 Adjusting Your Diet For Weigh Loss & Muscle Gains Adjusting You Diet For Weight Gain 00:04:00 Adjusting Your Diet For Weight Loss 00:05:00 Cheat Days and Cheat Meals 00:05:00 Post Workout Shake 00:02:00 Healthy Dieting Healthy Dieting Intro copy 00:01:00 Dieting myth #1 Carbs are bad for you 00:02:00 Dieting Myth #2 Fat is bad for you 00:02:00 Dieting Myth #3 Protein is bad for you 00:04:00 Dieting Myth #5 Avoid Salt At All Cost 00:01:00 Dieting Myth #6 Eat several small meals throughout the day to lose weight 00:01:00 Dieting Myth #7 Diet Foods Will Lead To Weight Loss 00:01:00 Red Meat Always Causes Cancer 00:03:00 Common Dieting Trends Explained Common Diets Intro Copy 00:01:00 Gluten Free Diet Explained 00:03:00 Paleo Diet Explained 00:04:00 Low Carb Diet Explained 00:03:00 Intermittend Fasting Explained 00:03:00 Vegan Diet Explained 00:05:00 Micronutrients Micronutrients Introduction 00:01:00 Vitamin A 00:02:00 Vitamin B 00:01:00 Vitamin C 00:01:00 Vitamin D 00:02:00 Vitmain E 00:01:00 Vitamin K 00:01:00 Calcium 00:02:00 Magnesium 00:01:00 Phosphorus 00:01:00 Potassium 00:01:00 Sodium 00:01:00 Copper 00:01:00 Iron 00:01:00 Zinc 00:02:00 Water 00:04:00 More Dieting Tips & Strategies Intro Specific dieting tips and strategies 00:01:00 5 Best Supplements to Boost Your Immune System 00:04:00 How to Read a Nutrition Label 00:03:00 How to Do You Own Research 00:04:00

Overview This Healthy Nutrition Masterclass course will unlock your full potential and will show you how to excel in a career in Healthy Nutrition Masterclass. So upskill now and reach your full potential. Everything you need to get started in Healthy Nutrition Masterclass is available in this course. Learning and progressing are the hallmarks of personal development. This Healthy Nutrition Masterclass will quickly teach you the must-have skills needed to start in the relevant industry. In This Healthy Nutrition Masterclass Course, You Will: Learn strategies to boost your workplace efficiency. Hone your Healthy Nutrition Masterclass skills to help you advance your career. Acquire a comprehensive understanding of various Healthy Nutrition Masterclass topics and tips from industry experts. Learn in-demand Healthy Nutrition Masterclass skills that are in high demand among UK employers, which will help you to kickstart your career. This Healthy Nutrition Masterclass course covers everything you must know to stand against the tough competition in the Healthy Nutrition Masterclass field.  The future is truly yours to seize with this Healthy Nutrition Masterclass. Enrol today and complete the course to achieve a Healthy Nutrition Masterclass certificate that can change your professional career forever. Additional Perks of Buying a Course From Institute of Mental Health Study online - whenever and wherever you want. One-to-one support from a dedicated tutor throughout your course. Certificate immediately upon course completion 100% Money back guarantee Exclusive discounts on your next course purchase from Institute of Mental Health Enrolling in the Healthy Nutrition Masterclass course can assist you in getting into your desired career quicker than you ever imagined. So without further ado, start now. Process of Evaluation After studying the Healthy Nutrition Masterclass course, your skills and knowledge will be tested with a MCQ exam or assignment. You must get a score of 60% to pass the test and get your certificate.  Certificate of Achievement Upon successfully completing the Healthy Nutrition Masterclass course, you will get your CPD accredited digital certificate immediately. And you can also claim the hardcopy certificate completely free of charge. All you have to do is pay a shipping charge of just £3.99. Who Is This Course for? This Healthy Nutrition Masterclass is suitable for anyone aspiring to start a career in Healthy Nutrition Masterclass; even if you are new to this and have no prior knowledge on Healthy Nutrition Masterclass, this course is going to be very easy for you to understand.  And if you are already working in the Healthy Nutrition Masterclass field, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  Taking this Healthy Nutrition Masterclass course is a win-win for you in all aspects.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements This Healthy Nutrition Masterclass course has no prerequisite.  You don't need any educational qualification or experience to enrol in the Healthy Nutrition Masterclass course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online Healthy Nutrition Masterclass course. Moreover, this course allows you to learn at your own pace while developing transferable and marketable skills. Course Curriculum Introduction Course Promo 00:02:00 Introduciton & What you will learn in the course 00:04:00 who this course is for 00:02:00 what is nutrition 00:01:00 The principles of healthy dieting 00:04:00 the true dieting pyramid 00:04:00 Calorie Balance Calories Explained 00:04:00 bodyweight and health 00:05:00 Calories & bodyweight in a healthy diet 00:02:00 the twinkie diet 00:02:00 weight loss and health 00:03:00 How many calories do you need daily 00:02:00 How To Determin Your Optimal Calorie Intake 00:03:00 healthy weight ranges 00:02:00 How to lose weight if you are close to the optimal range 00:03:00 How to lose weight when you start from a higher weight 00:02:00 Diet breaks 00:05:00 How to track calories 00:05:00 How to lose weight without tracking calories 00:04:00 Food Composition food composition intro 00:03:00 Protein Composition copy 00:02:00 Carbohydrate Composition copy 00:03:00 Fat Composition copy 00:01:00 Overview food composition 00:03:00 Macronutrients Macros intro 00:01:00 Protein Explained 00:02:00 protein needs for overall health 00:02:00 How Much Carbs should you eat per day copy 00:01:00 How Much Fat Should You Eat Per Day copy 00:04:00 Overview Macronutrients 00:03:00 Nutrient Timing Nutrient Timing Intro 00:02:00 Nutrient Timing Facts 00:04:00 Nutrient Timing Recommendations 00:02:00 Supplements Supplements intro 00:04:00 Why Mulitvitamins arent a good idea 00:02:00 supplements for vegans and vegetarians 00:02:00 supplements for joint health 00:02:00 supplements for improved sleep 00:02:00 supplements for better memory and focus 00:02:00 Supplements Overview 00:01:00 How to naturally increase testosterone 00:07:00 Healthy Eating Fundamentals basics of healthy dieting 00:02:00 making changs towards a healthier diet 00:04:00 How to read a nutrition label copy 00:03:00 Health Myths, Diet Fads & More diet myths into 00:01:00 Dieting myth #1 Carbs are bad for you copy 00:02:00 Dieting Myth #2 Fat is bad for you copy 00:02:00 Dieting Myth #3 Protein is bad for you copy 00:04:00 Dieting Myth #4 Eating Eggs Raises Cllesterol copy 00:01:00 Dieting Myth #5 Avoid Salt At All Cost copy 00:01:00 Dieting Myth #6 Eat several small meals throughout the day to lose weight copy 00:01:00 Dieting Myth #7 Diet Foods Will Lead To Weight Loss copy 00:01:00 Red meat always causes cancer copy 00:03:00 Common Diet Trends Explained Common Diets Intro 2 copy 00:01:00 Gluten Free Diet Explained copy 00:03:00 Paleo Diet Explained copy 00:04:00 Low Carb Diet Explained copy 00:03:00 Intermittend Fasting Explained copy 00:03:00 Vegan Diet Explained copy 00:05:00 Micronutrients (Vitamins & Minerals) Micronutrients Introduction 2 copy 00:01:00 Vitamin A copy 00:02:00 Vitamin B copy 00:01:00 Vitamin C copy 00:01:00 Vitamin D copy 00:02:00 Vitmain E copy 00:01:00 Vitamin K copy 00:01:00 Calcium copy 00:02:00 Magnesium copy 00:01:00 Phosphorus copy 00:01:00 Potassium copy 00:01:00 Sodium copy 00:01:00 Copper copy 00:01:00 Iron copy 00:01:00 Zinc copy** 00:02:00 water copy 00:04:00

Overview Uplift Your Career & Skill Up to Your Dream Job - Learning Simplified From Home! Kickstart your career & boost your employability by helping you discover your skills, talents and interests with our special Microsoft Power BI Masterclass 2021 Course. You'll create a pathway to your ideal job as this course is designed to uplift your career in the relevant industry. It provides professional training that employers are looking for in today's workplaces. The Microsoft Power BI Masterclass 2021 Course is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This Microsoft Power BI Masterclass 2021 Course has been designed by industry experts to provide our learners with the best learning experience possible to increase their understanding of their chosen field. This Microsoft Power BI Masterclass 2021 Course, like every one of Study Hub's courses, is meticulously developed and well researched. Every one of the topics is divided into elementary modules, allowing our students to grasp each lesson quickly. At StudyHub, we don't just offer courses; we also provide a valuable teaching process. When you buy a course from StudyHub, you get unlimited Lifetime access with 24/7 dedicated tutor support. Why buy this Microsoft Power BI Masterclass 2021? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Microsoft Power BI Masterclass 2021 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? This Microsoft Power BI Masterclass 2021 course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill.   Prerequisites This Microsoft Power BI Masterclass 2021 does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Microsoft Power BI Masterclass 2021 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 As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Microsoft Power BI Masterclass 2021 is a great way for you to gain multiple skills from the comfort of your home. 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 00:02:00 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 - Microsoft Power BI Masterclass 2021 00:00:00 Assignment Assignment - Microsoft Power BI 00:00:00

Teaching Assistants Level 1, 2 & 3 Do you aspire to be a capable teaching assistant who can meet the needs of your students? The Teaching Assistants Level 2,3 & 4 Course will help you to Discover a revolutionary curriculum to provide you with the skills and information necessary to succeed in a variety of educational environments. You will learn about the Roles and Responsibilities of the Teaching Assistant as well as various teaching environments during this Teaching Assistants Course course. You will learn how to defend supportive actions, healthy behaviours, and safety concerns in this Teaching Assistants Course. Additionally, this Teaching Assistants Course will help you strengthen your mentoring, organising, and understanding of children's growth. You may encourage equality, diversity, and inclusion in work with the aid of this Teaching Assistants Course. Enrol in the Teaching Assistants Course to develop your ability to work with a range of students! Special Offers of this Teaching Assistants Level 1, 2 & 3 Course This Teaching Assistants Course includes a FREE PDF Certificate. Lifetime Access to this Teaching Assistants Course Instant Access to this Teaching Assistants Course Get FREE Tutor Support to this Teaching Assistants Course Teaching Assistants Level 1, 2 & 3 You will also learn about a variety of Teaching Assistants Level 1, 2 & 3 concepts and approaches that have impacted contemporary primary teaching support practices in this Teaching Assistants Level 1,2 & 3 course. So, start your journey to a fulfilling career in education by enrolling in our Teaching Assistants Level 1, 2 & 3 course right now! [ Special Note: This Teaching Assistants Level 1, 2 & 3 Courses are CPD Accredited knowledge based Course & we don't offer any formal Qualification ] Who is this course for? Teaching Assistants Level 1, 2 & 3 For those who desire to work as teaching assistants and obtain a recognised qualification in this profession, this Teaching Assistants Level 1, 2 & 3 course has been created. This Teaching Assistants Level 1, 2 & 3 course will help you to go advance level in the field of Teaching Assistant. You can enrol on higher level Teaching Assistant courses, such as: Level 2 Award in Teaching Assistant Practice Level 2 Certificate in Teaching Assistant Practice Level 3 Certificate in Teaching Assistant Studies Level 3 Diploma in Teaching Assistant Studies Level 4 Certificate in Teaching Assistant Leadership Level 4 Diploma in Teaching Assistant Leadership Level 5 Diploma in Teaching Assistant Management Level 6 Diploma in Teaching Assistant Research Level 4 Certificate in Higher Level Teaching Assistant (HLTA) Level 5 Higher Level Teaching Assistant (HLTA) Requirements Teaching Assistants Level 1, 2 & 3 To enrol in this Teaching Assistants Level 1, 2 & 3 Course, students must fulfil the following requirements. To join in our Teaching Assistant Course, you must have a strong command of the English language. To successfully complete our Teaching Assistant Course, you must be vivacious and self driven. To complete our Teaching Assistant Course, you must have a basic understanding of computers. Career path Teaching Assistants Level 1, 2 & 3 This credential in Teaching Assistants Level 1, 2 & 3 courses will open up several paths including: Higher Level Teaching Assistant Primary Teaching Assistant Montessori Educator

Dive into the enthralling world of numbers and equations with 'High School Math (Pure Mathematics 1),' a course designed to unravel the mysteries of mathematics. Your journey begins with an Introduction that lays the foundation, not just in terms of concepts but igniting a passion for the beauty of math. As you progress, Functions become more than just equations; they turn into a language that describes the universe. Imagine the elegance of Quadratic Equations unfolding before your eyes, revealing patterns and solutions that were once hidden. Embark on an adventure through Co-ordinate Geometry, where every point and line tells a story of space and dimensions. Sequence and Series will no longer be just about numbers; they will be about the rhythm and flow of mathematical logic. The course takes a deeper dive with the Binomial Theorem, Differentiation, Tangents and Normals, each module building on the last, turning complexity into simplicity. Stationary Points & Curve Sketching, and the Second Derivative Test open new vistas in understanding the nature of graphs. As you master Simultaneous Linear Equations, you're not just solving problems; you're unlocking a new perspective on mathematical relationships. The Essential Revision at the end is your bridge to excellence, consolidating your knowledge and skills. Learning Outcomes Develop a foundational understanding of key mathematical concepts and functions. Master the intricacies of quadratic equations and co-ordinate geometry. Explore and apply the principles of sequences, series, and the binomial theorem. Gain proficiency in differentiation and its practical applications in tangents and normals. Understand and implement techniques in curve sketching, stationary points, and optimisation. Why choose this High School Math (Pure Mathematics 1) 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 High School Math (Pure Mathematics 1) course for? High school students seeking to excel in mathematics. Individuals preparing for college-level math courses. Math enthusiasts looking to deepen their understanding of pure mathematics. Students requiring a comprehensive revision of key mathematical concepts. Anyone aspiring to pursue a career involving advanced mathematics. Career path Mathematician: £30,000 - £60,000 Data Analyst: £25,000 - £50,000 Actuarial Analyst: £28,000 - £55,000 Research Scientist (Mathematics): £32,000 - £60,000 Engineering Consultant: £27,000 - £55,000 Academic Tutor (Mathematics): £24,000 - £40,000 Prerequisites This High School Math (Pure Mathematics 1) does not require you to have any prior qualifications or experience. You can just enrol and start learning.This High School Math (Pure Mathematics 1) 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 Introduction Introduction 00:03:00 Functions What is Function? 00:07:00 Vertical Line Test 00:04:00 Value of a Function Graphically 00:08:00 Domain Range of a function Algebraically 00:13:00 Domain Range of a function Graphically 00:06:00 Even & Odd Functions 00:07:00 One to one Function 00:05:00 Composite Functions 00:09:00 How to draw Rational Functions- 1 00:04:00 How to draw Rational Functions- 2 00:10:00 Inverse of a function Algebraically 00:05:00 Inverse of a function Graphically 00:09:00 Practice Problems 00:15:00 Practice Problems 00:11:00 Resources Downloads 00:40:00 Quadratic Equations Introduction to Quadratic Equations 00:04:00 Solving Quadratic Equations by Factorization method 00:10:00 Writing in completed square form 00:08:00 Solving by completed square method 00:08:00 Sketching of Quadratic Graphs 00:11:00 Quadratic graphs using Transformations 00:06:00 Quadratic inequalities 00:11:00 Deriving Quadratic formula 00:05:00 Solving problems using Quadratic Formula 00:06:00 Equations reducible to Quadratic 00:07:00 Nature of Roots of Quadratic Equations 00:04:00 Nature of roots continues 00:12:00 Quadratic Equations (Resources) 00:50:00 Co-ordinate Geometry Distance formula 00:15:00 Mid point formula 00:05:00 Gradient of a line 00:10:00 Graphing using gradient and y intercept 00:02:00 Some standard lines 00:04:00 Slope intercept form y = m x +c 00:05:00 Point slope form and two point form 00:10:00 Intersection of line and parabola 00:09:00 Practice Problems from past papers (part 3) 00:12:00 Sequence and series Sequence and series ( video) 00:08:00 Arithmetic Sequence 00:10:00 General term of an A.P. 00:07:00 Finding given term is which term? 00:05:00 Writing sequence when two terms are known 00:08:00 Condition for three terms to be in A.P. 00:05:00 Sum to n terms of A.P. 00:06:00 Practice Problems 1 (A.P.) 00:08:00 Practice problems 3 (A.P.) 00:07:00 Practice problems 4 (A.P.) 00:10:00 Geometric Progressions 00:11:00 Sum to n terms in G.P. 00:14:00 Sum to infinite Terms in G.P. 00:13:00 Practice Problems 1 (GP) 00:13:00 Practice Problems 2 (GP) 00:06:00 Practice Problems based on AP and GP both 00:15:00 Sequence and series Text 1 00:40:00 Sequence and series Text 2 00:55:00 Binomial Theorem What is Factorial? 00:06:00 n-choose -r problems 00:06:00 Properties of n - choose -r 00:05:00 Expanding using Binomial Theorem 00:11:00 Finding the indicated term in the Binomial expansion 00:10:00 Finding the indicated term from end 00:09:00 Finding the coefficient for given exponent (index) of the variable 00:08:00 Finding the term independent of variable 00:05:00 Expanding in increasing and decreasing powers of x 00:09:00 Practice problems 1 00:12:00 Practice Problems 2 00:09:00 Practice problems 3 00:10:00 Past papers problems 1 00:15:00 Past Paper problems 2 00:13:00 Past Paper problems 3 00:09:00 Resources in this section 00:50:00 Differentiation What is Derivative? 00:07:00 Derivation of formula for Derivative 00:06:00 Differentiation by definition or First Principle 00:06:00 Power Rule 00:20:00 Practice Problems on Power Rule 1 00:07:00 Practice Problems on Power Rule 2 00:07:00 Practice Problems on Power Rule 3 00:05:00 Practice Problems on Power Rule 4 00:11:00 Practice Problems on Power Rule 5 00:07:00 Tangents and Normals Tangents and Normals- Basics 00:12:00 Practice- Tangents and Normals Part 1 00:16:00 Practice- Tangents and Normals Part 2 00:13:00 Practice- Tangents and Normals Part 3 00:11:00 Practice- Tangents and Normals Part 4 00:14:00 Stationary Points & Curve Sketching Stationary Points - Basics 00:13:00 Practice- Increasing Decreasing & Maxima Minima part 1 00:11:00 Practice- Increasing Decreasing & Maxima Minima part 2 00:12:00 Practice- Increasing Decreasing & Maxima Minima part 3 00:10:00 Second Derivative Test (Maximum & Minimum Points) Concavity-Basics 00:02:00 Concavity & Second Derivative 00:08:00 Second Derivative Test 00:09:00 Practice Problems on second derivative 00:04:00 Practice Problem of Maxima Minima using second derivative test Part 1 00:17:00 Practice Problem of Maxima Minima using second derivative test Part 2 00:10:00 Practice Problem of Maxima Minima using second derivative test Part 3 00:07:00 Practice Problem of Maxima Minima using second derivative test Part 4 00:07:00 Applications of Maxima and Minima Part 1 00:09:00 Applications of Maxima and Minima Part 2 00:07:00 Applications of Maxima and Minima Part 3 00:10:00 Applications of Maxima and Minima Part 4 00:09:00 Applications of Maxima and Minima Part 5 00:10:00 Applications of Maxima and Minima Part 6 00:08:00 Past Paper Problems on applications of maxima and minima Part 1 00:09:00 Past Paper Problems on applications of maxima and minima Part 2 00:09:00 Past Paper Problems on applications of maxima and minima Part 3 00:08:00 Past Paper Problems on applications of maxima and minima Part 4 00:07:00 Chain Rule 00:12:00 Rate of change part 1 00:05:00 Rate of change part 2 00:10:00 Rate of change part 3 00:07:00 Past Paper Problems using chain rule -1 00:06:00 Past Paper Problems using chain rule - 2 00:07:00 Past Paper Problems using chain rule 3 00:07:00 Past Paper Problems using chain rule -4 00:04:00 Simultaneous Linear equations Graphical Method of solving pair of linear equations 00:10:00 Video lecture on Graphical method 00:05:00 Method of elimination by substitution 00:10:00 Video lecture on substitution method 00:06:00 Method of elimination by equating the coefficients 00:10:00 Video lecture on equating coefficients method 00:09:00 Practice Problems on Linear equation 00:20:00 Essential Revision How to take up this course? 00:10:00 Background of Algebra 00:10:00 Language of Alg ebra 00:10:00 Finding Values of algebraic expressions 00:14:00 Fractional Indices 00:10:00 Higher Indices 00:07:00 Rules of Brackets 00:04:00 Simplification by removing brackets (BODMAS) 00:11:00 Simplifications of Algebraic Fractions 00:07:00 Solving complex Linear Equations in one variable 00:10:00 Factorization by taking out common factor 00:10:00 Factorization by grouping the terms 00:09:00 Factorize using identity a ² - b ² 00:07:00 Factorization by middle term split 00:12:00

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

The 'Complete Python Machine Learning & Data Science Fundamentals' course covers the foundational concepts of machine learning, data science, and Python programming. It includes hands-on exercises, data visualization, algorithm evaluation techniques, feature selection, and performance improvement using ensembles and parameter tuning. Learning Outcomes: Understand the fundamental concepts and types of machine learning, data science, and Python programming. Learn to prepare the system and environment for data analysis and machine learning tasks. Master the basics of Python, NumPy, Matplotlib, and Pandas for data manipulation and visualization. Gain insights into dataset summary statistics, data visualization techniques, and data preprocessing. Explore feature selection methods and evaluation metrics for classification and regression algorithms. Compare and select the best machine learning model using pipelines and ensembles. Learn to export, save, load machine learning models, and finalize the chosen models for real-time predictions. Why buy this Complete Python Machine Learning & Data Science Fundamentals? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Complete Python Machine Learning & Data Science Fundamentals 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? This Complete Python Machine Learning & Data Science Fundamentals course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Complete Python Machine Learning & Data Science Fundamentals does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Complete Python Machine Learning & Data Science Fundamentals 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 As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Complete Python Machine Learning & Data Science Fundamentals is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:08:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Understanding the CSV data file 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:07:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Python Machine Learning & Data Science Fundamentals 00:00:00

Embark on a transformative journey through the intricate landscape of networking with the CompTIA Network+ Certification (N10-007). This course isn't just about mastering the intricacies of network models or delving into the depths of cabling and topology; it's about empowering yourself with the skills and knowledge to navigate the digital highways of the modern era confidently. Picture yourself as the architect, laying down the foundations of robust networks, securing them against digital threats, and troubleshooting with finesse. With CompTIA Network+ +, you're not just learning; you're shaping your future in information technology. In this comprehensive course, you'll traverse through 22 meticulously crafted sections, each unlocking a new facet of comptia networking. From understanding the fundamentals of TCP/IP to exploring the nuances of wireless networking and delving into virtualization and cloud computing, every lesson is a stepping stone towards network mastery. Through immersive learning experiences and hands-on comptia network+ practice tests, you'll absorb theoretical knowledge and hone your practical skills, preparing you for real-world challenges. Learning Outcomes: Master network models and topologies, laying a strong foundation for network architecture. Demonstrate proficiency in TCP/IP fundamentals and routing protocols for effective data transmission. Develop expertise in securing networks against cyber threats, ensuring data integrity and confidentiality. Acquire skills in network troubleshooting and monitoring, enabling swift resolution of issues. Apply wireless networking and cloud computing knowledge to design and implement scalable network solutions. Why buy this CompTIA Network+ Certification (N10-007)? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the CompTIA Network+ Certification (N10-007) 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 CompTIA Network+ Certification (N10-007) for? Aspiring IT professionals seeking to kickstart their careers in networking. Students aiming to enhance their employability with industry-recognized certifications. Career changers looking to transition into the dynamic field of information technology. IT professionals seeking to validate their skills and advance their careers. Anyone passionate about mastering the intricacies of comptia network and carving a niche in the digital landscape. Prerequisites This CompTIA Network+ Certification (N10-007) does not require you to have any prior qualifications or experience. You can just enrol and start learning.This CompTIA Network+ Certification (N10-007) 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 Network Administrator: £20,000 - £45,000 Per Annum Network Engineer: £25,000 - £55,000 Per Annum Systems Administrator: £22,000 - £50,000 Per Annum IT Support Technician: £18,000 - £35,000 Per Annum Cyber Security Analyst: £25,000 - £60,000 Per Annum Cloud Solutions Architect: £30,000 - £80,000 Per Annum Course Curriculum Section 01: Introduction Introduction 00:03:00 Section 02: Network Models What is a Model? 00:02:00 OSI vs. TCP/IP Model 00:07:00 Walking Through OSI and TCP/IP 00:12:00 Meet the Frame 00:06:00 The MAC Address 00:07:00 Broadcast vs. Unicast 00:04:00 Introduction to IP Addressing 00:08:00 Packets and Ports 00:05:00 Section 03: Cabling and Topology Network Topologies 00:10:00 Coaxial Cabling 00:05:00 Twisted Pair Cabling 00:06:00 Cat Ratings 00:06:00 Fiber Optic Cabling 00:09:00 Fire Ratings 00:05:00 Legacy Network Connections 00:07:00 Section 04: Ethernet Basics What is Ethernet? 00:07:00 Ethernet Frames 00:07:00 Early Ethernet 00:08:00 The Daddy of Ethernet, 10BaseT 00:03:00 Terminating Twisted Pair 00:14:00 Hubs vs. Switches 00:13:00 Section 05: Modern Ethernet 100BaseT 00:05:00 Connecting Switches 00:05:00 Gigabit Ethernet and 10-Gigabit Ethernet 00:05:00 Transceivers 00:07:00 Connecting Ethernet Scenarios 00:14:00 Section 06: Installing a Physical Network Introduction to Structured Cabling 00:04:00 Terminating Structured Cabling 00:08:00 Equipment Room 00:07:00 Alternative Distribution Panels 00:04:00 Testing Cable 00:09:00 Troubleshooting Structured Cabling, Part 1 00:05:00 Troubleshooting Structured Cabling, Part 2 00:05:00 Using a Toner and Probe 00:03:00 Wired Connection Scenarios 00:11:00 Section 07: TCP/IP Basics Introduction to IP Addressing and Binary 00:13:00 Introduction to ARP 00:04:00 Classful Addressing 00:10:00 Subnet Masks 00:12:00 Subnetting with CIDR 00:10:00 More CIDR Subnetting Practice 00:10:00 Dynamic and Static IP Addressing 00:18:00 Rogue DHCP Servers 00:07:00 Special IP Addresses 00:07:00 IP Addressing Scenarios 00:15:00 Section 08: Routing Introducing Routers 00:15:00 Understanding Ports 00:05:00 Network Address Translation 00:06:00 Implementing NAT 00:03:00 Forwarding Ports 00:18:00 Tour of a SOHO Router 00:12:00 SOHO vs. Enterprise 00:09:00 Static Routes 00:13:00 Dynamic Routing 00:11:00 RIP 00:04:00 OSPF 00:04:00 BGP 00:06:00 Section 09: TCP/IP Applications TCP and UDP 00:07:00 ICMP and IGMP 00:06:00 Handy Tools 00:07:00 Introduction to Wireshark 00:11:00 Introduction to netstat 00:09:00 Web Servers 00:12:00 FTP 00:12:00 E-mail Servers and Clients 00:09:00 Securing E-mail 00:06:00 Telnet and SSH 00:09:00 Network Time Protocol 00:02:00 Network Service Scenarios 00:10:00 Section 10: Network Naming Understanding DNS 00:12:00 Applying DNS 00:19:00 The Hosts File 00:04:00 Net Command 00:08:00 Windows Name Resolution 00:11:00 Dynamic DNS 00:05:00 DNS Troubleshooting 00:13:00 Section 11: Securing TCP/IP Making TCP/IP Secure 00:04:00 Symmetric Encryption 00:06:00 Asymmetric Encryption 00:03:00 Cryptographic Hashes 00:05:00 Identification 00:12:00 Access Control 00:04:00 AAA 00:05:00 Kerberos/EAP 00:08:00 Single Sign-On 00:10:00 Certificates and Trust 00:14:00 Certificate Error Scenarios 00:08:00 Section 12: Advanced Networking Devices Understanding IP Tunneling 00:06:00 Virtual Private Networks 00:13:00 Introduction to VLANs 00:12:00 InterVLAN Routing 00:03:00 Interfacing with Managed Switches 00:11:00 Switch Port Protection 00:07:00 Port Bonding 00:07:00 Port Mirroring 00:04:00 Quality of Service 00:05:00 IDS vs. IPS 00:04:00 Proxy Servers 00:13:00 Load Balancing 00:09:00 Device Placement Scenarios 00:13:00 Section 13: IPv6 Introduction to IPv6 00:13:00 IPv6 Addressing 00:15:00 IPv6 in Action 00:13:00 IPv4 and IPv6 Tunneling 00:05:00 Section 14: Remote Connectivity Telephony Technologies 00:09:00 Optical Carriers 00:03:00 Packet Switching 00:05:00 Connecting with Dial-up 00:05:00 Digital Subscriber Line (DSL) 00:05:00 Connecting with Cable Modems 00:04:00 Connecting with Satellites 00:03:00 ISDN and BPL 00:04:00 Remote Desktop Connectivity 00:05:00 Advanced Remote Control Systems 00:09:00 Section 15: Wireless Networking Introduction to 802.11 00:12:00 802.11 Standards 00:12:00 Power over Ethernet (PoE) 00:04:00 Antennas 00:09:00 Wireless Security Standards 00:16:00 Implementing Wireless Security 00:07:00 Threats to Your Wireless Network 00:07:00 Retro Threats 00:05:00 Wi-Fi Protected Setup (WPS) 00:05:00 Enterprise Wireless 00:06:00 Installing a Wireless Network 00:15:00 Wireless Scenarios 00:07:00 More Wireless Scenarios 00:09:00 Section 16: Virtualization and Cloud Computing Virtualization Basics 00:07:00 Cloud Ownership 00:03:00 Cloud Implementation 00:12:00 Your First Virtual Machine 00:09:00 NAS and SAN 00:16:00 Platform as a Service (PaaS) 00:09:00 Software as a Service (SaaS) 00:03:00 Infrastructure as a Service (IaaS) 00:10:00 Section 17: Mobile Networking Cellular Technologies 00:05:00 Mobile Connectivity 00:07:00 Deploying Mobile Devices 00:05:00 Mobile Access Control 00:06:00 Section 18: Building a Real-World Network Network Types 00:04:00 Network Design 00:10:00 Power Management 00:06:00 Unified Communications 00:11:00 Network Documentation 00:07:00 Contingency Planning 00:10:00 Predicting Hardware Failure 00:05:00 Backups 00:08:00 Section 19: Managing Risk What is Risk Management? 00:06:00 Security Policies 00:08:00 Change Management 00:07:00 User Training 00:03:00 Standard Business Documentation 00:05:00 Mitigating Network Threats 00:05:00 High Availability 00:05:00 Section 20: Protecting Your Network Denial of Service 00:09:00 Malware 00:10:00 Social Engineering 00:04:00 Access Control 00:08:00 Man-in-the-Middle 00:22:00 Introduction to Firewalls 00:05:00 Firewalls 00:10:00 DMZ 00:06:00 Hardening Devices 00:14:00 Physical Security Controls 00:09:00 Testing Network Security 00:08:00 Network Protection Scenarios 00:14:00 Section 21: Network Monitoring SNMP 00:15:00 Documenting Logs 00:09:00 System Monitoring 00:08:00 SIEM (Security Information and Event Management) 00:07:00 Section 22: Network Troubleshooting Network Troubleshooting Theory 00:05:00

Overview Construction management is vast, and the global construction market is forecasted to grow by 85% to $15.5 TRILLION worldwide by 2030. The Diploma in Construction Management becomes an essential learning tool for those aspiring to spearhead this growth. This comprehensive course covers all the critical facts of construction management, equipping students with the essential knowledge and in-demand skills to oversee complex Construction projects seamlessly. This Construction diploma covers everything from the project life cycle to the legal aspects of contracting, giving you a complete understanding of construction management. Key Features of the Course: FREE Construction Management CPD-accredited certificate Get a free student ID card with Construction Management training (£10 applicable for international delivery) Lifetime access to the Construction Management course materials The Construction Management program comes with 24/7 tutor support Get instant access to this Construction Management course Learn Construction Management training from anywhere in the world The Construction Management training is affordable and simple to understand The Construction Management training is an entirely online Description This course provides essential knowledge and skills for managing construction projects effectively. Learn about project planning, budgeting, team coordination, and legal requirements to confidently oversee construction projects from start to finish. Course Curriculum: 1 sections • 18 lectures • 06:43:00 hours total •Module 01: Introduction to Construction Management •Module 02: Project Life Cycle and Success •Module 03: Cost Management •Module 04: Preliminary Site Investigation and Site Organization •Module 05: Site Management •Module 06: Planning and Management of Equipment •Module 07: Construction Materials Management •Module 08: Vendor Analysis in Construction Management •Module 09: Construction Procurement •Module 10: Stock Control •Module 11: Supply Chain Management •Module 12: The Main Participators •Module 13: Quality Assurance and Customer Care •Module 14: Legal Aspects of Contracting •Module 15: Human Resources Management •Module 16: Risk and Value Management •Module 17: Communications, Information and Documentation of Construction •Module 18: Health and Safety in Construction Management Career path Having these various qualifications will increase the value of your CV and open you up to multiple sectors such as: Construction Manager Site Manager Project Manager Quantity Surveyor Estimator Site Engineer Building Surveyor Health and Safety Manager Sustainability Manager General Foreman