The Mechanics of Mediumship. A beginners guide to everything you need to know. How to become a professional psychic medium. Able to give short, accurate, evidential messages. This course runs over 5 weeks and during our time together we will explore five easy to follow parts. 1: What mediumship is and the different types, including your role as a professional medium and the differences between working in the psychic modality and when you are connected to spirit. 2: Activating and building your power within, and the difference between meditation, and attunement both to the spirit world and using your psychic modality. 3: The six different senses available to you, which are your strongest and whether you are perceiving them objectively or subjectively. 4: What is and what is not evidence in mediumship, understanding the different types of evidence available and defining practical and emotional evidence. 5: Surrendering to spirit, building confidence to receive specific unique information, and understanding the reasons why you receive a no response. Guidance on making positive, strong, statements filling your sitter with confidence, building a truly extraordinary professional reading.
Attend our world class Kanban University accredited Certified Kanban System Design training course and learn to implement Kanban in your company
Attend our world class Kanban University accredited Certified Kanban System Design training course and learn to implement Kanban in your company
Attend our world class Kanban University accredited Certified Kanban System Design training course and learn to implement Kanban in your company
Attend our world class Kanban University accredited Certified Kanban System Design training course and learn to implement Kanban in your company
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Join Patrick Garton for a pair of connected session about effective classroom behaviour. This is for all teachers who want to refresh and deepen their skills and understanding in this vital area.
weave together the enchantment of tarot cards with the magic of altars, candles, and incantations, creating a tapestry of transformation
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
Build your confidence, fluency & accuracy with an individual ESL Book Club in English using a simplified, shortened and adapted novel. Highlights Join this individual ESL book club course to quickly improve your English confidence, fluency & accuracy 3 hours of live 1:1 English classes to help you develop your confidence in speaking in English Read a section of the book at home and then discuss what you have read Learn English 1:1 & be corrected by your private English teacher to remove errors and mistakes Build your confidence, skills and accuracy in this individual ESL book club in English course. Choose one of the books from the selection below. These books are shortened, simplified and adapted for learners of English as a foreign language. There are also language learning exercises and a short glossary of new words. Each week you read about 20-30 pages, write a summary of what you have read, and then discuss what you have read with your teacher Geoff. Personalised feedback improves your grammar, vocabulary and pronunciation. The Book Club book Individual ESL Book Clubs are flexible and can be taken on the following simplified and shortened "graded reader" books. Contact Geoff to agree a day and time, then enrol on the course. Intermediate (B1) Austen, Jane - Emma (Oxford Bookworms) Austen, Jane - Persuasion (Oxford Bookworms) Austen, Jane - Sense and Sensibility (Penguin Readers) Brontë, Emily - Wuthering Heights (Penguin Readers) Christie, Agatha - Death on the Nile (Collins English Readers) Christie, Agatha - The Body in the Library (Collins English Readers) Conan Doyle, Arthur - Sherlock Holmes: The Hound of the Baskervilles (Oxford Bookworms) Dickens, Charles - A Tale of Two Cities (Penguin Readers) Dickens, Charles - David Copperfield (Penguin Readers) Dickens, Charles - Great Expectations (Penguin Readers) Dickens, Charles - Oliver Twist (Penguin Readers) Hardy, Thomas - Far From The Madding Crowd (Penguin Readers) Hardy, Thomas - Tess of the D'Urbervilles (Penguin Readers) Hawkins, Paula - The Girl On The Train (Penguin Readers) Highsmith, Patricia - The Talented Mr Ripley (Penguin Readers) Joyce, James - Dubliners (Penguin Readers) Joyce, Rachel - The Unlikely Pilgrimage of Harold Fry (Penguin Readers) Le Carré, John - The Spy Who Came In From The Cold (Penguin Readers) Shelley, Mary - Frankenstein (Penguin Readers) Tóibín, Colm - Brooklyn (Penguin Readers) Upper-Intermediate (B2) Austen, Jane - Sense and Sensibility (Oxford Bookworms) Asimov, Isaac - I, Robot (Oxford Bookworms) Brontë, Emily - Wuthering Heights (Oxford Bookworms) Christie, Agatha - The ABC Murders (Collins English Readers) Christie, Agatha - Evil Under The Sun (Collins English Readers) Collins, Wilkie - The Woman in White (Penguin Readers) Dick, Philip K - Do Androids Dream of Electric Sheep? (Oxford Bookworms) Evaristo, Bernardine - Girl, Woman, Other (Penguin Readers) Fitzgerald, F. Scott - The Great Gatsby (Oxford Bookworms) Gyasi, Yaa - Homegoing (Penguin Readers) Hardy, Thomas - Far From The Madding Crowd (Oxford Bookworms) Kerouac, Jack - On the Road (Pearson English Readers) Mansfield, Katherine - The Garden Party (Oxford Bookworms) McEwan, Ian - The Children Act (Penguin Readers) Melville, Herman - Moby Dick (Penguin Readers) Orwell, George - 1984 (Penguin Readers) Puso, Mario - The Godfather (Penguin Readers) Smith, Zadie - White Teeth (Penguin Readers) Stevenson, RL - The Strange Case of Dr Jekyll and Mr Hyde (Pearson English Readers) Wharton, Edith - The Age of Innocence (Oxford Bookworms) Woolf, Virginia - Mrs Dalloway (Penguin Readers) Upper-Intermediate + (B2+) Austen, Jane - Pride and Prejudice (Oxford Bookworms) Brontë, Charlotte - Jane Eyre (Oxford Bookworms) Conan Doyle, Arthur - Sherlock Holmes: The Sign of Four (Oxford Bookworms) Flaubert, Gustave - Madame Bovary (Pearson English Readers) Gaskell, Elizabeth - North and South (Pearson English Readers) Garland, Alex- The Beach (Pearson English Readers) Hardy, Thomas - Tess of the D'Urbervilles (Oxford Bookworms) Tan, Amy - The Joy Luck Club (Oxford Bookworms) Geoff says: "This is a great way to start reading more in English, to build your confidence, to focus on your needs and language, and to make fast progress."