ADVANCED 8 CPD POINTS 1 DAY INTENSIVE COURSE ONLINE or IN-CLINIC NOTE! After booking we will contact you for scheduling the exact course date! Courses dates are subject to change due to mentors availability. We will inform you via email if a date becomes available! This course theory will help you to understand: We will cover all you need to know in order for you to treat your patients confidently and safely. The Theory will cover; Anatomy and physiology Ageing Characteristic of the ideal skin booster Product Introduction Treatment Method Contraindication Complication management Pre & Post-treatment advices Using Products like Toskani, Skinecos, Jalupro etc. Using Products , PROFHILO, recommended for midd and low part of the face as well as other delicate areas of skin such as the neck, décolletage, hands or knees. Practice will enable you to learn in 1-day ONE-TO-ONE Training We will cover pertinent information including mechanism of action, safety and efficacy issues, management and treatment of complications, dilution guidelines, and more. A certification of hands-on training will be provided upon completion of the course. You will perform this procedure on live models injecting superficially and administrating the product (skinbooster) into the subcutaneous layer. This will happen under the supervision and guidance of highly experienced aesthetic practitioners. You will practice injectables with needle on; Face, Neck, Decolatege & Hands You need to be medically qualified as a doctor, dentist, nurse, pharmacist or paramedic with full governing body registration and have completed a Foundation Filler Course and to have administered a number of cases. Additional information ATTENDANCE ONLINE (Theory), IN CLINIC (Practice) COURSE LEVEL INTERMEDIATE | Advanced Course
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Level 3 Certificate in Understanding Autism will provide further learning in autism for those that have already completed the level 2 qualification.
If you work with adults and young people and wish to gain a knowledge of the principles and practice of assessment as well as the practical aspects of carrying out assessment, then Level 3 Certificate in Assessing Vocational Achievement is for you.
This course is aimed at those who would like to teach in the further education sector in a college or private training provider. Level 3 Award in Education & Training provides you with knowledge and understanding of the role of a teacher and how to meet individual learner needs.
This Level 3 anatomy & physiology (or A & P as it is commonly known) is a perfect course for those who are looking to build upon their existing knowledge of skincare, but is also open to complete beginners. Please confirm dates and availability with us prior to purchasing Who Is This Course Suitable For? Pre-requisites None required. Course Content You will cover: Skin, nails and hair The skeletal system The muscular system The nervous system The endocrine system The respiratory system The cardiovascular system The lymphatic system The digestive system You will have 1 Assignment and 1 Exam Course Duration & Cost No date required, please go ahead and BOOK, we will email across all relevant home studying information directly to your email address You have a minimum of 6 weeks to study for the exam and a maximum of one year This course is ALL home studying You will need inform us when you feel you are ready to sit your exam, we can take a look at a few assessment dates for you at our Leicester centre. Remote (Webcam) Exams If you cannot attend our assessment Centre we can arrange for you to take your final assessment remotely via webcam. Dates for remote exams are flexible and can be booked in with our team when you have completed your online coursework. £330 Categories: ofqual
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Duration 2 Days 12 CPD hours This course is intended for Business Analysts, Technical Managers, and Programmers Overview This intensive training course helps students learn the practical aspects of the R programming language. The course is supplemented by many hands-on labs which allow attendees to immediately apply their theoretical knowledge in practice. Over the past few years, R has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data as well as supervised and unsupervised machine learning. What is R ? What is R? ? Positioning of R in the Data Science Space ? The Legal Aspects ? Microsoft R Open ? R Integrated Development Environments ? Running R ? Running RStudio ? Getting Help ? General Notes on R Commands and Statements ? Assignment Operators ? R Core Data Structures ? Assignment Example ? R Objects and Workspace ? Printing Objects ? Arithmetic Operators ? Logical Operators ? System Date and Time ? Operations ? User-defined Functions ? Control Statements ? Conditional Execution ? Repetitive Execution ? Repetitive execution ? Built-in Functions ? Summary Introduction to Functional Programming with R ? What is Functional Programming (FP)? ? Terminology: Higher-Order Functions ? A Short List of Languages that Support FP ? Functional Programming in R ? Vector and Matrix Arithmetic ? Vector Arithmetic Example ? More Examples of FP in R ? Summary Managing Your Environment ? Getting and Setting the Working Directory ? Getting the List of Files in a Directory ? The R Home Directory ? Executing External R commands ? Loading External Scripts in RStudio ? Listing Objects in Workspace ? Removing Objects in Workspace ? Saving Your Workspace in R ? Saving Your Workspace in RStudio ? Saving Your Workspace in R GUI ? Loading Your Workspace ? Diverting Output to a File ? Batch (Unattended) Processing ? Controlling Global Options ? Summary R Type System and Structures ? The R Data Types ? System Date and Time ? Formatting Date and Time ? Using the mode() Function ? R Data Structures ? What is the Type of My Data Structure? ? Creating Vectors ? Logical Vectors ? Character Vectors ? Factorization ? Multi-Mode Vectors ? The Length of the Vector ? Getting Vector Elements ? Lists ? A List with Element Names ? Extracting List Elements ? Adding to a List ? Matrix Data Structure ? Creating Matrices ? Creating Matrices with cbind() and rbind() ? Working with Data Frames ? Matrices vs Data Frames ? A Data Frame Sample ? Creating a Data Frame ? Accessing Data Cells ? Getting Info About a Data Frame ? Selecting Columns in Data Frames ? Selecting Rows in Data Frames ? Getting a Subset of a Data Frame ? Sorting (ordering) Data in Data Frames by Attribute(s) ? Editing Data Frames ? The str() Function ? Type Conversion (Coercion) ? The summary() Function ? Checking an Object's Type ? Summary Extending R ? The Base R Packages ? Loading Packages ? What is the Difference between Package and Library? ? Extending R ? The CRAN Web Site ? Extending R in R GUI ? Extending R in RStudio ? Installing and Removing Packages from Command-Line ? Summary Read-Write and Import-Export Operations in R ? Reading Data from a File into a Vector ? Example of Reading Data from a File into A Vector ? Writing Data to a File ? Example of Writing Data to a File ? Reading Data into A Data Frame ? Writing CSV Files ? Importing Data into R ? Exporting Data from R ? Summary Statistical Computing Features in R ? Statistical Computing Features ? Descriptive Statistics ? Basic Statistical Functions ? Examples of Using Basic Statistical Functions ? Non-uniformity of a Probability Distribution ? Writing Your Own skew and kurtosis Functions ? Generating Normally Distributed Random Numbers ? Generating Uniformly Distributed Random Numbers ? Using the summary() Function ? Math Functions Used in Data Analysis ? Examples of Using Math Functions ? Correlations ? Correlation Example ? Testing Correlation Coefficient for Significance ? The cor.test() Function ? The cor.test() Example ? Regression Analysis ? Types of Regression ? Simple Linear Regression Model ? Least-Squares Method (LSM) ? LSM Assumptions ? Fitting Linear Regression Models in R ? Example of Using lm() ? Confidence Intervals for Model Parameters ? Example of Using lm() with a Data Frame ? Regression Models in Excel ? Multiple Regression Analysis ? Summary Data Manipulation and Transformation in R ? Applying Functions to Matrices and Data Frames ? The apply() Function ? Using apply() ? Using apply() with a User-Defined Function ? apply() Variants ? Using tapply() ? Adding a Column to a Data Frame ? Dropping A Column in a Data Frame ? The attach() and detach() Functions ? Sampling ? Using sample() for Generating Labels ? Set Operations ? Example of Using Set Operations ? The dplyr Package ? Object Masking (Shadowing) Considerations ? Getting More Information on dplyr in RStudio ? The search() or searchpaths() Functions ? Handling Large Data Sets in R with the data.table Package ? The fread() and fwrite() functions from the data.table Package ? Using the Data Table Structure ? Summary Data Visualization in R ? Data Visualization ? Data Visualization in R ? The ggplot2 Data Visualization Package ? Creating Bar Plots in R ? Creating Horizontal Bar Plots ? Using barplot() with Matrices ? Using barplot() with Matrices Example ? Customizing Plots ? Histograms in R ? Building Histograms with hist() ? Example of using hist() ? Pie Charts in R ? Examples of using pie() ? Generic X-Y Plotting ? Examples of the plot() function ? Dot Plots in R ? Saving Your Work ? Supported Export Options ? Plots in RStudio ? Saving a Plot as an Image ? Summary Using R Efficiently ? Object Memory Allocation Considerations ? Garbage Collection ? Finding Out About Loaded Packages ? Using the conflicts() Function ? Getting Information About the Object Source Package with the pryr Package ? Using the where() Function from the pryr Package ? Timing Your Code ? Timing Your Code with system.time() ? Timing Your Code with System.time() ? Sleeping a Program ? Handling Large Data Sets in R with the data.table Package ? Passing System-Level Parameters to R ? Summary Lab Exercises Lab 1 - Getting Started with R Lab 2 - Learning the R Type System and Structures Lab 3 - Read and Write Operations in R Lab 4 - Data Import and Export in R Lab 5 - k-Nearest Neighbors Algorithm Lab 6 - Creating Your Own Statistical Functions Lab 7 - Simple Linear Regression Lab 8 - Monte-Carlo Simulation (Method) Lab 9 - Data Processing with R Lab 10 - Using R Graphics Package Lab 11 - Using R Efficiently
Do you want a rewarding career working directly with people, making a difference to their everyday lives? If you are warm, open and empathetic and can bring a patient, tolerant, non-judgemental attitude then a career in counselling could be for you.