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Acrylic nail: Acrylic nails Course Online Introducing the ultimate course: Acrylic nail: Acrylic nails Course The Acrylic nail: Acrylic nails Course will teach you how to apply acrylic nails while also providing you with vital beauty industry skills. The Acrylic nail: Acrylic nails Course covers a wide range of topics, such as: nail tools and equipment and Anatomy and products. You will learn about the usage of these products, tools and equipment. Through this Acrylic nail: Acrylic nails Course you will gain a detailed understanding of Chemical terminology as well as practical procedure of Acrylic nail: Acrylic nails Course. By the completion of the Acrylic nail: Acrylic nails Course, you will have a thorough understanding of the traits of a successful leader as well as how to apply the methods gained in this Acrylic nail: Acrylic nails Course to advance your career. Don't miss out on this opportunity to take your career to the next level. Enrol in our Acrylic nail: Acrylic nails Course today and start your journey towards becoming a confident and successful nail technician. Main Course: Acrylic nails Course Free Courses included with Acrylic nail: Acrylic nails Course: Along with Acrylic nails Course you will get free Nail Technician Along with Acrylic nails Course you will get free Brow Lamination course Along with Acrylic nails Course you will get free Body Massage Therapy Along with Acrylic nails Course you will get free Level 5 Fashion & Beauty Special Offers of this Acrylic nail: Acrylic nails Course; This Acrylic nail: Acrylic nails Course includes a FREE PDF Certificate Lifetime access to this Acrylic nail: Acrylic nails Course Instant access to this Acrylic nail: Acrylic nails Course 24/7 Support Available to this Acrylic nail: Acrylic nails Course Description Acrylic nail: Acrylic nails Course Online Whether you are just starting your career or seeking professional development, this Acrylic nail: Acrylic nails Course is perfect for you. Developed by industry experts and ensures you acquire the skills necessary to provide exceptional Acrylic nail services. With our Acrylic nail: Acrylic nails Course, you will have the flexibility to learn at your own pace, whenever and wherever suits you best. You can access the Acrylic nail: Acrylic nails Course material 24/7 and revisit the content whenever you need a refresher. You will receive a recognized qualification that will enhance your career prospects and open up new opportunities in the sector. Who is this course for? Acrylic nail: Acrylic nails Course Online This Acrylic nail: Acrylic nails Course is open to everyone. Requirements Acrylic nail: Acrylic nails Course Online To enroll in this Acrylic nail: Acrylic nails Course, students must fulfill the following requirements: Acrylic nail: Good Command over English language is mandatory to enrol in our Acrylic nails Course. Acrylic nail: Be energetic and self-motivated to complete our Acrylic nails Course. Acrylic nail: Basic computer Skill is required to complete our Acrylic nails Course. Acrylic nail: If you want to enrol in our Acrylic nails Course you must be at least 15 years old. Career path Acrylic nail: Acrylic nails Course Online This Acrylic nail: Acrylic nails Course training will assist you in enhancing your CV while researching the following career opportunities: Beauty Advisor Beauty Therapist Nail Technician

Motivation: Motivational Interviewing Would you like to master motivational interviewing principles to make positive changes? We have created a special motivational interviewing course to spread positive word training all over. Through the motivational interviewing course, you will learn empathetic dialogue and active listening. Also, in the motivational interviewing course, attendees learn to navigate ambivalence, enhance intrinsic motivation, and guide individuals towards their goals. The motivational interviewing course’s key components include open-ended questioning, reflective listening, and eliciting change talk. Moreover, this motivational interviewing course's practical exercises and case studies provide opportunities to apply techniques in diverse contexts, fostering skill development. Participate in our motivational interviewing course to learn effective communication strategies to inspire behavioural change. Special Offers of this Motivation: Motivational Interviewing Course This Motivation: Motivational Interviewing Course includes a FREE PDF Certificate. Lifetime access to this Motivation: Motivational Interviewing Course Instant access to this Motivation: Motivational Interviewing Course Get FREE Tutor Support to this Motivation: Motivational Interviewing Course Motivation: Motivational Interviewing Unlock the power of empathetic communication with our Motivation: Motivation Interviewing Course. Through this comprehensive Motivation: Motivation course, you'll master the art of empathetic dialogue and active listening, essential for guiding individuals towards their goals. Our Motivation: Motivation training will teach you how to navigate ambivalence and enhance intrinsic motivation, making it easier to inspire change. The Motivation: Motivation course covers key techniques like open-ended questioning, reflective listening, and eliciting change talk. Plus, with practical exercises and case studies, our Motivation: Motivation course ensures you can apply these skills in real-world scenarios. Elevate your professional impact with our Motivation: Motivation Interviewing Course. Who is this course for? Motivation: Motivational Interviewing This motivational interviewing course is ideal for those looking to advance their career in relevant fields. Requirements Motivation: Motivational Interviewing To enrol in this Motivation: Motivational Interviewing Course, students must fulfil the following requirements. To join in our Motivation: Motivational Interviewing Control Course, you must have a strong command of the English language. To successfully complete our Motivation: Motivational Interviewing Course, you must be vivacious and self driven. To complete our Motivation: Motivational Interviewing Course, you must have a basic understanding of computers. A minimum age limit of 15 is required to enrol in this Motivation: Motivational Interviewing Course. Career path Motivation: Motivational Interviewing You can pursue a profession as a motivational interviewer, social worker, counsellor, or in many other fields with the use of this motivational interviewing course.

Level 2 Certificate in Understanding Domestic Abuse Course Online According to the annual Crime Survey, almost 2.5 Million adults experience domestic abuse: domestic abuse each year. Furthermore, one in every five children witnesses or is a victim of domestic abuse: domestic abuse as a child. Although domestic abuse: domestic abuse is often an unreported crime, most cases are kept hidden. This Level 2 Certificate in Understanding Domestic Abuse Course aims to increase learners' awareness and understanding of domestic abuse: domestic abuse and its impacts. Domestic abuse: domestic abuse and its impacts must be understood by those working in various fields, including healthcare, social care, childcare, education, and housing. Why choose this Level 2 Certificate in Understanding Domestic Abuse Course from the School of Health Care? Self-paced course, access available from anywhere in the world. High-quality study materials that are easy to understand. Level 2 Certificate in Understanding Domestic Abuse Course developed by industry experts. After each module, there will be an MCQ quiz to assess your learning. Assessment results are generated automatically and instantly. 24/7 support is available via live chat, phone call, or email. Free PDF certificate after completing the Level 2 Certificate in Understanding Domestic Abuse: Domestic Abuse Course. Main Course: Level 2 Certificate in Understanding Domestic Abuse Course Free Courses included with Level 2 Certificate in Understanding Domestic Abuse Course Course 01: Equality and Diversity Course 02: Healthcare Management Training Course 03: Level 5 Mental Health First Aid Certification Course 04: Mental Health Support Worker Special Offers of this Level 2 Certificate in Understanding Domestic Abuse: Domestic Abuse Course: This Level 2 Certificate in Understanding Domestic Abuse: Domestic Abuse Course includes a FREE PDF Certificate. Lifetime access to this Level 2 Certificate in Understanding Domestic Abuse: Domestic Abuse Course Instant access to this Level 2 Certificate in Understanding Domestic Abuse: Domestic Abuse Course 24/7 Support Available to this Level 2 Certificate in Understanding Domestic Abuse: Domestic Abuse Course [ Note: Free PDF certificate as soon as completing the Level 2 Certificate in Understanding Domestic Abuse: Domestic Abuse Course] Level 2 Certificate in Understanding Domestic Abuse Course Online This Level 2 Certificate in Understanding Domestic Abuse: Domestic Abuse Course consists of 04 modules. Course Curriculum of Level 2 Certificate in Understanding Domestic Abuse Course Module 01: Understand Domestic Abuse Module 02: Understand the Signs and Risk Factors Associated with Domestic Abuse Module 03: Understand the Impact of Domestic Abuse Module 04: Understand Policy, Response and Intervention in Relation to Domestic Abuse Assessment Method of Level 2 Certificate in Understanding Domestic Abuse Course After completing Working in Level 2 Certificate in Understanding Domestic Abuse: Domestic Abuse Course, you will get quizzes to assess your learning. You will do the later modules upon getting 60% marks on the quiz test. Apart from this, you do not need to sit for any other assessments. Certification of Level 2 Certificate in Understanding Domestic Abuse Course After completing the Working in Level 2 Certificate in Understanding Domestic Abuse: Domestic Abuse course, you can instantly download your certificate for FREE. The hard copy of the certification will also be delivered to your doorstep via post, which will cost £13.99. Who is this course for? Level 2 Certificate in Understanding Domestic Abuse Course Online This Level 2 Certificate in Understanding Domestic Abuse: Domestic Abuse course is ideal for anyone who has a responsibility to support those experiencing domestic abuse: domestic abuse. Special Note: Our Level 2 Certificate in Understanding Domestic Abuse: Domestic Abuse Course is not a regulated course. If you prefer to get qualified, you can look at the following options: NCFE CACHE Level 2 Certificate in Understanding Domestic Abuse: Domestic Abuse Requirements Level 2 Certificate in Understanding Domestic Abuse Course Online To enrol in this Understanding Domestic Abuse: Domestic Abuse Course, students must fulfil the following requirements: Good Command over English language is mandatory to enrol in our Understanding Domestic Abuse: Domestic Abuse Course. Be energetic and self-motivated to complete our Understanding Domestic Abuse: Domestic Abuse Course. Basic computer Skill is required to complete our Understanding Domestic Abuse: Domestic Abuse Course. If you want to enrol in our Understanding Domestic Abuse: Domestic Abuse Course, you must be at least 15 years old. Career path Level 2 Certificate in Understanding Domestic Abuse Course Online Upon completing this Level 2 Certificate in Understanding Domestic Abuse: Domestic Abuse course, you can become familiarised with the response and support of those domestically abused.

Higher Level Teaching Assistant Level 4 (HLTA), SEN, Early Years, Teaching and Childcare If you want to learn about Higher Level Teaching Assistant Level 4 (HLTA), SEN, Early Years, Teaching and Childcare course and become an expert in the field, you have arrived at the right place. Teaching is in high demand right now and becoming a Higher-Level Teaching Assistant (HLTA) is an excellent way to get started. This HLTA: Higher Level Teaching Assistant (HLTA) course will teach you everything you need to know to become a Teaching Assistant, allowing you to take the first step toward a rewarding teaching career! Through this Higher Level Teaching Assistant Level 4 (HLTA), SEN, Early Years, Teaching and Childcare course, you will gain a better understanding of the role and responsibilities of a HLTA: Higher Level Teaching Assistant (HLTA) course, as well as schools as organizations, the UK school system, and the National Curriculum. You will learn a variety of skills, including child safety and first aid, as well as how to build relationships and manage a classroom. Main Course: Higher Level Teaching Assistant (HLTA) Free Courses: - Course 01: Diploma in Special Education Needs (SEN) Course 02: Primary Teaching Diploma Course 03: EYFS Teaching Diploma Course 04: Autism Diploma Course 05: Special Educational Needs Coordination Course 06: Level 4 Early Years Course 07: Train the Trainer Course Course 08: Executive Secretary & PA Training Course 09: ADHD Awareness [ Note: Free PDF certificate as soon as completing Higher Level Teaching Assistant Level 4 (HLTA), SEN, Early Years, Teaching and Childcare course] Higher Level Teaching Assistant Level 4 (HLTA), SEN, Early Years, Teaching and Childcare Industry Specialists developed this HLTA: Higher Level Teaching Assistant (HLTA) course into 08 user-friendly modules/ lectures. Course Curriculum of HLTA: Higher Level Teaching Assistant (HLTA) course Course Curriculum of Higher-Level Teaching Assistant (HLTA) Module 01: Understand the Higher Level Teaching Assistant role Module 02: Child Development and Welfare Module 03: Awareness of Special Educational Needs Module 04: Promoting children and young people’s positive behaviour Module 05: Providing support for individual learners and small groups Module 06: Developing skills to promote positive working relationships Module 07: Curriculum planning, delivery and assessment Assessment Method of HLTA: Higher Level Teaching Assistant (HLTA) course After completing Working in Higher Level Teaching Assistant (HLTA), SEN, Early Years, Teaching and Childcare with Child psychology course, you will get quizzes to assess your learning. You will do the later modules upon getting 60% marks on the quiz test. Certification of HLTA: Higher Level Teaching Assistant (HLTA) course After completing the Working in Higher Level Teaching Assistant (HLTA), SEN, Early Years, Teaching and Childcare with Child psychology course, you can instantly download your certificate for FREE. Who is this course for? Higher Level Teaching Assistant Level 4 (HLTA), SEN, Early Years, Teaching and Childcare This HLTA: Higher Level Teaching Assistant (HLTA) course is open to everyone. Special Note: Our Higher Level Teaching Assistant Level 4 (HLTA), SEN, Early Years, Teaching and Childcare Course is not a regulated course. If You want to get qualified, you can consider following options: HND Child Care EDI Child Psychology Teaching and child care RQF Early Learning & Childcare NCFE Early Learning and Childcare Teaching Assistant: Teaching and Childcare Online Level 3 Award in Childcare & Education Level 3 Award in Childcare and Education (VRQ) Level 3 Diploma for Residential Childcare (England) (RQF) Level 3 Award in Preparing to Work in Home-Based Childcare Level 5 Diploma in Leadership and Management for Residential Child care (England) (RQF) Level 2 Award in Food Safety in Health and Social Care and Early Years and Child care Settings (RQF) Requirements Higher Level Teaching Assistant Level 4 (HLTA), SEN, Early Years, Teaching and Childcare Online To enrol in this HLTA: Higher Level Teaching Assistant (HLTA) Course, students must fulfil the following requirements: Good Command over English language is mandatory to enrol in our HLTA: Higher Level Teaching Assistant (HLTA) Course. Be energetic and self-motivated to complete our HLTA: Higher Level Teaching Assistant (HLTA) Course. Basic computer Skill is required to complete our HLTA: Higher Level Teaching Assistant (HLTA) Course. If you want to enrol in our HLTA Course, you must be at least 15 years old. Career path Higher Level Teaching Assistant Level 4 (HLTA), SEN, Early Years, Teaching and Childcare

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

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

Duration 3 Days 18 CPD hours This course is intended for Programmers Application DevelopersSystem Architects Network ArchitectsNetwork Security Architects IT Professionals w/programming experience Overview Those who attend the Ethereum Development course and pass the exam certification will have a demonstrated knowledge of:An excellent overall understanding of the Ethereum architecture and Solidity language.All functional components (including smart contracts) required to develop an Ethereum Blockchain.The understanding of how to instantiate an Ethereum application on the network.An in-depth understanding of how transactions are created and implemented on an Ethereum network. This 3 day instructor-led course is designed for programmers and developers who want to take a comprehensive deep dive in writing smart contracts and building applications that interact with them. This course provides detailed overviews of Ethereum, smart contracts, and the development language, Solidity. The student will be exposed to Ethereum?s adaptable feature set which allows the developer to design decentralized applications for countless applications. Students will also participate in hands-on programming lab sessions to learn, develop, and advance their skills in Ethereum development. The Ethereum Development Training Course is designed for those seeking an in-depth understanding and development experience of the Ethereum Blockchain platform. Students will participate in approximately 50% programming lab time providing practical experience, enhancing their knowledge and existing skill set. What is Blockchain and Smart Contracts? What is Blockchain and how does it work? Bitcoin vs Ethereum Smart Contract How you can use Smart Contracts? Advantages of Smart Contracts Solidity LAB TASK Types of Variables in Solidity Public and Private Code Public Variables and Functions Private Variables and Functions Internal Functions External Functions Smart Contract Constructors Constant Variables Setting Variables LAB CHALLENGE Smart Contracts With WEB3.JS LAB Installing & Running the Ethereum TestRPC Installing Web3.js Changing the Environment in Remix Creating the UI Using Web3.js to Connect & Interact with the Smart Contract SOLUTION LAB CHALLENGE Smart Contract Events With WEB3.JS AIM LAB The Current Contract Defining the Smart Contract Event Updating the UI LAB CHALLENGE Functions, Mappings and Structs THEORY Functions Mappings Structs LAB The Smart Contract Creating a Modifier Using the Modifier Web3 UI?s Modifier Handling LAB Creating a Struct Creating the Mapping Map Addition Get from the Mapping The Full Contract Count from Map LAB CHALLENGE Inheritance and Deployment THEORY Object-oriented programming Inheritance LAB Current Contract Creating a Base Contract Changing from Strings to bytes Continuing the Project Installing MetaMask Deploy Contract to the Ropsten Test Network LAB Update the HTML Form Update the JavaScript Using the App LAB CHALLENGE Embark Framework and It's Deployment Blockchain (Ethereum) Decentralized Storage (IPFS) Decentralized Communication Web Technologies LAB Installing Embark Framework Hello World with Embark Framework First Contract Deployment with Embark Framework Solidity Smart Contracts Testing THEORY What is Software Testing? LAB LAB CHALLENGE Contracts Management With Factories THEORY Factory LAB LAB CHALLENGE IPFS Files Hosting THEORY IPFS FILES HOSTING LAB 1. Get your hosting server 2. Install IPFS on the Server LAB CHALLENGE End to End Development of DAPP AIM LAB Setup the Project Program the Smart Contract Create the Front-end of the application Deploy the App with IPFS LAB CHALLENGE

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

Overview This comprehensive course on Electric Circuits for Electrical Engineering  will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Electric Circuits for Electrical Engineering comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Electric Circuits for Electrical Engineering. It is available to all students, of all academic backgrounds. Requirements Our Electric Circuits for Electrical Engineering is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 7 sections • 135 lectures • 10:29:00 total length •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: 00:09:00 •Module 6- Example 2: 00:02:00 •Module 7- Example 3: 00:13:00 •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: 00:02:00 •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 7: 00:04:00 •Module 18- Application 2 Electricity Bills: 00:02:00 •Module 19- Example 8: 00:03:00 •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: 00:01:00 •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 •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: 00:02:00 •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 •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: 00:04:00 •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 •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: 00:04:00 •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: 00:02:00 •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 •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: 00:02:00 •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 - Reporting and Data: 00:00:00

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