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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

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

Project Management Overview™: On-Demand This on-demand program provides learners with an interactive self-paced introduction to the world of project management (PM). Participants will gain fluency in the language and core concepts of PM, regardless of their roles in any project environment. They will also gain experience and perspective with basic yet practical problem-solving on a real-world case study. What You Will Learn You'll learn how to: Speak the language of project management Practice basic skills and tools that support effective project management through a structured process, including: Initiating Planning Executing Monitoring & Controlling Monitoring & Controlling Closing Basic Concepts People in Projects Projects in Organizations A Process Approach Process Groups in Action - Initiating Process Groups in Action - Planning Process Groups in Action - Executing Process Groups in Action - Monitoring & Controlling Process Groups in Action - Closing Summary and Next Steps

Access Introduction generally navigate through Access Database, get data fast, update data records by entering, update data and delete data. Run available report, use available forms, create simple forms and reports via wizards. This style tuition helps to maximise the value that you get from the day.

About Course ASP.NET Core MVC 6: Master the Latest Web Development Framework Become a full-stack web developer with this comprehensive course on ASP.NET Core MVC 6, taught by a lead instructor with 20+ years of experience. This course is designed for beginners with zero or basic programming experience. You will learn everything you need to know to build modern web applications with ASP.NET Core MVC 6, including: HTML5 and CSS3 Bootstrap 4 C# ASP.NET Core MVC 6 Entity Framework Core SQL Server Express You will also learn about important web development concepts such as routing, controllers, views, and models. The course includes HD video tutorials, code challenges, and coding exercises to help you learn and practice the material. You will also build a real-world project to apply your skills. By the end of this course, you will be fluent in ASP.NET Core MVC 6 and ready to build any website you can dream of. Enroll today and start your journey to becoming a full-stack web developer! Benefits of taking this course: Learn from a lead instructor with 20+ years of experience Become a full-stack web developer with just one course Learn the latest tools and technologies used at large companies such as Apple, Facebook, Google, and Netflix Get comprehensive student testing and feedback from students who are working and applying these coding examples Learn by building real-world websites and web apps Get access to HD video tutorials, code challenges, and coding exercises Target audience: Beginners with zero or basic programming experience who want to learn how to build modern web applications with ASP.NET Core MVC 6 What Will You Learn? Learn structure of ASP .NET MVC Core (.NET 6) Project Create websites and webapp for your business needs Get a job as a junior web developer on Microsoft technologies Identify a case study to manage a project development Master front-end development using HTML & CSS back-end development using C# & MS SQL Create fully function dynamic MVC Core web applications using Asp .NET Core Creating Functional Model, View and Controller functionality on Movie Project Learn to Add Entity Framework Packages to Project Using NuGet Package Manager Applying SQL Server Database Connection to your application Running Power Shell Commands for Scaffolding and CRUD function Webforms Identify and applying Database Migrations You will learn fully functional Validations for your project Course Content Getting Started Course Introduction Course Curriculum How to Get Course Requirements Getting Started on Windows, Linux or Mac How to Ask Great Questions FAQ's ASP.NET Basics Section Introduction What You Can Build with ASP.NET Core What is ASP.NET Core How to Get Visual Studio Installing Visual Studio and ASP.NET Creating New Project Summary Prerequisites: HTML, CSS and Bootstrap Section Introduction HTML Overview Paragraph HTML List Items Forms CSS Overview CSS Internal CSS External CSS Forms Bootstrap Overview First Bootstrap Website Bootstrap Grids System Bootstrap Cards Summary ASP.NET MVC: Movie Project Section Introduction Source Code Reference MVC - Model View Controller Create a MVC Project Exploring the MVC Template Creating Controller Add a Controller URL Routing Logic Creating View Add a View Change Views and Layout Pages Passing Data from Controller to View Creating Model Add a Model Add Entity Framework Packages Scaffold Movie Pages-CRUD Database Migrations Initial Migration Generated Database Context Class Dependency Injection Database Connection String Summary Working with Database Section Introduction SQL Server Express Local DB Seed the Database Add the Seed Initializer Summary Add Search to ASP.NET Core MVC App Section Introduction Add Search Method to Controller Add Search to Page Search by Parameter Summary Model Update Section Introduction Add a New Field to Model Add-Migration Update Database Summary Validations Add Validation Rules to Model Required and Minimum Length Regular Expression Range String Length Validation on Error UI Enable JavaScript on Browser Examine the Details and Delete Code Review on Details Method Code Review on Delete Method Course Files and Resources Course Files and Resources A course by Sekhar Metla IT Industry Expert Xpert Learning RequirementsBasic C# programming experience needed(optional). You will learn MVC Core need to knowNo software is required in advance of the course (all software used in the course is free)No pre-knowledge is required on MVC - you will learn from basic Audience Beginner Asp .Net MVC Core C# coding, Microsoft SQL and CSS developers curious about web development Anyone who wants to generate new income streams Anyone who wants to build dynamic web applications Anyone who wants to become financially independent Anyone who wants to start their own business or become freelance Anyone who wants to become a Full stack web developer Anyone who wants to build fully functional asp .net core mvc database applications Audience Beginner Asp .Net MVC Core C# coding, Microsoft SQL and CSS developers curious about web development Anyone who wants to generate new income streams Anyone who wants to build dynamic web applications Anyone who wants to become financially independent Anyone who wants to start their own business or become freelance Anyone who wants to become a Full stack web developer Anyone who wants to build fully functional asp .net core mvc database applications

Project Communication Skills (On-Demand) In this course, participants will actively explore best communication practices from a variety of perspectives: in-person, virtual, electronic, and via formal project documentation. Communication is the single most critical project success factor. When effective, projects get executed on time, within budget, and with objectives being met. But that isn't all. Strong communication also nurtures healthy team relationships. And in today's highly diverse world, where projects are often fast-paced, complex, and virtual, that is more important than ever. Strong communication skills foster cultural awareness, trust, and empathy. Together, they contribute greatly to project success-and ultimately, to future project success. In this course, participants will actively explore best communication practices from a variety of perspectives: in-person, virtual, electronic, and via formal project documentation. In order to be transformative, however, those perspectives will be filtered further through the lens of their formal, personalized assessment. It is a powerful tool which identifies individuals' internal needs and priorities. It translates those into descriptive profiles and reports, gifting users with valuable information about themselves and others. Paired with the course's real-world activities, it will provide uniquely strategic opportunities for communicating effectively and meaningfully-and with less conflict, both personally and professionally. What You Will Learn At the end of this program, you will be able to: Identify basic elements of communication and explain how they affect teams Explore how your assessment style impacts you and how you communicate with people of other styles Infer how your style impacts the way(s) you send and interpret emails and instant messages Analyze real world email and instant messaging practices to determine how they affect communication and relationships Explore best practices for formal project communications and presentations Analyze how your assessment style and global diversity can contribute to both strong team communication and conflict Identify solutions for virtual team work communication challenges Getting Started Foundation Concepts Communication as a foundation skill Elements of communication Communicating across media Targeting your audience How communication impacts team performance The Assessment Framework Overview of the assessment's approach Exploring assessment report Increasing your effectiveness with other assessment styles Email and Instant Messages Preferred communications and assessment styles The email brands we create Assessment styles and email Emotion and email Email guidelines and best practices Anatomy of an email The seven deadly email sins Instant messages and other interfaces Project Communications and Presentations Communicating across the project lifecycle Project templates Structuring a presentation Delivering a presentation Interpersonal and Team Communication Skills Communication styles and techniques Managing conflict in a project environment Styles and conflict Communication and global team leadership Virtual Communication Leading global virtual teams Virtual processes and technology Virtual team leadership Summary and Next Steps

Conflict Resolution Skills (On-Demand) Many organizations have assumed that workplace conflict is always destructive. So, they have often believed that conflict is best dealt with by managers or even via policies and procedures. After all, conflict creates workplace stress and leads to many performance problems, generating very real organizational costs! However, savvy organizations have embraced the fact that when conflict is understood and harnessed, it can be leveraged to add value to teams and even enhance performance. With the right knowledge, skills, training, and practice, conflict can be productive and make organizations better! In this highly interactive course, learners will discover the connection between individual conflict response and team-empowering conflict resolution skills. Participants will explore conflict's visceral dynamics and the nuanced behaviors we individually engage in to communicate and respond to conflict. Learners will apply techniques for transforming unproductive conflict responses into productive ones. Additionally, learners will use a systematic method that prepares them to objectively dissect real-world conflict, while practicing many strategies for resolving it. They will also develop proactive conflict approach plans, which they can transfer back to their own workplaces. At the end of this program, you will be able to: Recognize the organizational costs of conflict Explain our physical and mental responses to conflict Communicate proactively and effectively with different types of people during conflict Replace unproductive conflict responses with productive ones Use the Conflict Resolution Diagram (CRD) process and conflict resolution approaches Relate team stages of development to shifts in conflict Develop a proactive conflict approach for your organization Create a conflict resolution plan for a real-world scenario Getting Started Introductions and social agreements Course goal and objectives Opening activities Conflict Facilitation Readiness Conflict responses and perceptions Conflict basics Conflict and organizations Dynamics of conflict Conflict Styles and Communication A look at the color energies model Conflict through the color energies and DiSC® lens Communication with opposite color energies Individual Response to Conflict The anatomy of conflict Recognizing unproductive conflict responses 4 steps to productive conflict Choosing productive conflict responses Team Performance and Conflict High-performing team relationships Conflict and project team performance Conflict Resolution Diagram (CRD) and process Conflict Facilitation - Preparation Recognizing context and stakeholder needs Using team conflict resolution approaches Preparing for Crucial Conversations® Conflict Facilitation - Clarity Exposing assumptions and biases Defining the conflict and using the CRD Conflict Facilitation - Action Proactive conflict management Conflict facilitation practice Summary and Next Steps Review Personal action plans

Nutrition Training - Advanced Diet & Meal Planning Overview Confused by all the different diets out there? What if you could ditch the fads and create a personalized eating plan that actually works for you? Nutrition Training - Advanced Diet & Meal Planning is your guide to becoming your own nutrition boss. This course breaks down the science of food into easy-to-understand chunks. You'll learn the basics of healthy eating, from the different types of nutrients your body needs to how food choices affect your health. We'll then delve deeper into advanced dieting strategies, so you can create a plan that fits your goals, whether you want to lose weight or build muscle. The course also covers popular diets, explaining how they work and if they're the right choice for you. Plus, you'll learn how to use food to help prevent illness. By the end, you'll be able to design custom meal plans that give your body exactly what it needs to thrive. Nutrition Training - Advanced Diet & Meal Planning is your key to unlocking a healthier, happier you through the power of food! Learning Outcomes Grasp the core principles of nutrition and healthy eating. Explore advanced dieting theories to craft a personalized plan. Design targeted meal plans for effective fat loss. Develop strategies to support muscle growth through diet. Evaluate popular diets and make informed choices about your nutrition. Why You Should Choose Nutrition Training - Advanced Diet & Meal Planning Lifetime access to the course No hidden fees or exam charges CPD Accredited certification on successful completion Full Tutor support on weekdays (Monday - Friday) Efficient exam system, assessment and instant results Download Printable PDF certificate immediately after completion Obtain the original print copy of your certificate, dispatch the next working day for as little as £9. Improve your chance of gaining professional skills and better earning potential. Who is this Course for? Nutrition Training - Advanced Diet & Meal Planning is CPD certified and IAO accredited. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic backgrounds. Requirements Our Nutrition Training - Advanced Diet & Meal Planning is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path You will be ready to enter the relevant job market after completing this course. You will be able to gain necessary knowledge and skills required to succeed in this sector. All our Diplomas' are CPD and IAO accredited so you will be able to stand out in the crowd by adding our qualifications to your CV and Resume. Nutrition Training - Advanced Diet & Meal Planning Section 01: Introduction Course overview 00:04:00 Get to know your instructor 00:02:00 Section 02: The Nutrition Fundamentals Recap intro 00:01:00 Nutrition priorities 00:04:00 Calories Summary 00:04:00 Macronutrient summary 00:20:00 Meal timing summary 00:09:00 Food Quality & Composition summary 00:05:00 Supplements Summary 00:06:00 Meal planning recap 00:09:00 Section 03: Advanced Dieting Theory Advanced Nutrition Theory Introduction 00:02:00 The Factors That Influence Energy Expenditure 00:09:00 Protein 00:03:00 Amino Acids 00:04:00 Protein & Energy (De Novo Glucogenesis) 00:02:00 Carbohydrates 00:03:00 Glucose & Glycogen 00:03:00 Carbs & Energy (Glycolysis) 00:03:00 Fat 00:03:00 Essential Fatty Acids (Omega 3 & Omega 6) 00:07:00 Fat & Energy (Lipolysis) 00:02:00 The 4th Macronutrient: Alcohol 00:05:00 Section 04: Advanced Dieting For Fat Loss Advanced Fat Loss Introduction 00:01:00 Should I build muscle or lose fat first? 00:06:00 The Different Phases Of A Fat Loss Diet 00:08:00 The Settling Point Theory Explained 00:06:00 How To Reverse Diet 00:05:00 The Best Strategies And Supplements To Reduce Hunger 00:08:00 The Different Stages Of Fitness Transformations 00:07:00 PSMF: The Science-Based Crash Diet That Works 00:07:00 Can You Break Your Metabolism? 00:03:00 Section 05: Advanced Dieting For Muscle Grow Advanced Dieting For Muscle Growth Introduction 00:01:00 The Muscle Growth Priorities 00:05:00 The Different Types Of Bulks 00:02:00 Step By Step Dirty Bulk 00:08:00 Step By Step Regular Bulk 00:07:00 Step By Step Lean Bulk 00:03:00 The Difference Between Fitness Diets & Health Diets 00:04:00 Intra Workout Carbs 00:04:00 Section 06: Popular Diets Explained The 'One True Diet' Fallacy 00:03:00 The Naturalistic Fallacy 00:03:00 The Perfect Nutrient Fallacy 00:02:00 Pros & Cons Of High Carb Diets 00:03:00 Pros & Cons Of Low Carb Diets 00:04:00 Pros & Cons Of Moderate Carb, Moderate Fat Diets 00:02:00 The Blood Type Diet 00:04:00 Carb Cycling 00:04:00 Section 07: Dieting & Disease Prevention Dieting & Diseases Introduction 00:01:00 The Right Diet To Avoid Acid Reflux 00:05:00 The Right Diet For Constipation 00:04:00 The Right Diet To Avoid Diabetes 00:08:00 Leaky Gut Syndrome 00:05:00 Section 08: FAQ Diet vs Exercise: Which Is More Important 00:03:00 HCG diet 00:03:00 Is Fructose Bad For You? 00:04:00 Should You Separate Carbs And Protein? 00:04:00

Duration 3 Days 18 CPD hours This course is intended for Individuals involved in IT development, IT operations or IT service management; Those whose role is touched by DevOps and continuous delivery, such as the following IT roles: DevOps engineers, Product owners Integration specialists, Operations managers, Incident & change managers, System administrators, Network administrators, Business managers, Automation architects, Enterprise architects, Testers Overview Know the emergence of DevOps Know the core concepts and principles of DevOps Know what DevOps means for you as professional and for your organization Know the essence of a DevOps culture Understand the key elements of a DevOps culture Know the important aspects when creating a DevOps culture Know the Operational models of DevOps Understand the need for autonomous teams Understand the impact of DevOps on Architecture with respect to deployment Understand governance within DevOps teams Understand Agile, Scrum and Kanban and how these practices relate to one another Understand how ITSM processes relate to practices in a DevOps culture Understand how lean is used to optimise processes Know how to provide a Value Stream Map for a given process Understand the way to harvest new and innovative ideas Know the impact of automation on Software Delivery processes Understand the benefits and core principles of Continuous Delivery Describe the key cloud principles for DevOps organisations Know the relevance of monitoring and logging DevOps This course is designed to provide the core education necessary to build your DevOps vocabulary and to understand its principles and practices. With the help of key DevOps concepts and terminology, real-life case studies, examples and interactive group discussions and extensive exercises in each module you will acquire a fundamental understanding of DevOps. Introduction Let?s Get to Know Each Other Overview Course Objectives Mapping of the Competence Model with the Course Modules Course Agenda Type of Activities Exam Course Book Technical Glossary Group Activity Module Summary DevOps Introduction Module Objectives Module Topics Emergence of DevOps Core Concepts of DevOps DevOps Agile Skills Association (DASA) Module Summary Module End Questions Culture Module Objectives Module Topics Essence of a DevOps Culture Key Elements of DevOps Implementation of a DevOps Culture Module Summary Module End Questions Organization Module Objectives Module Topics Organizational Model Autonomous Teams Architecting for DevOps Governance Module Summary Module End Questions Processes Module Objectives Module Topics Process Basics DevOps in Relation to ITSM Agile and Scrum 12 Principles of the Agile Manifesto Optimizing Processes Using Lean Business Value Optimization and Business Analysis Using Story Mapping Module Summary Module End Questions Automation Module Objectives 6A Automation Concepts Automation for Delivery of Software Continuous Delivery Core Concepts Continuous Delivery Automation Concepts Continuous Delivery Automation Focus Topics 6B Data Center Automation Emergence of Cloud Technology and Principles Cloud Services Concepts in a DevOps Organization Automated Provisioning Concepts Platform Product Characteristics and Application Maturity Module Summary Module End Questions Measure and Improvement Module Objectives Module Topics Importance of Measurement Choosing the Right Metrics Monitoring and Logging Module Summary Module End Questions

This exclusive Language Therapy Course provides learners with a comprehensive overview of the role of a Speech and Language Therapist, equipping you with the essential skills to advance your career. It includes speech science, speech anatomy, and the characteristics of speech in detail. This Language Therapy course will teach you how Speech and Language Therapists help children and adults with speech and language disorders, including swallowing, eating, and drinking issues. It covers the fundamentals of the speech chain model and walks you through the key stages of literacy and language development. This Language Therapy course includes case studies and practical exercises that will teach you how to assess your clients' needs, set long-term goals, and support them every step of the way to recovery using a variety of communication techniques. In addition, you will gain in-demand professional skills that will help you start your career successfully. Learning Objectives After completing this Language Therapy course, the learner will be able to: Understand the fundamentals of Speech & Language Therapy. Understand the study of communication. Explain components of normal speech, language & voice and communication disorders. Understand eating, drinking and swallowing disorders. Understand the speech & language therapy process. Why Choose Language Therapy Course from Us Self-paced course, access available from anywhere. Easy to understand, high-quality study materials. Language Therapy Course developed by industry experts. MCQ quiz after each module to assess your learning. Automated and instant assessment results. Free PDF certificate as soon as completing the Language Therapy course. 24/7 support via live chat, phone call or email. [ Note: Free PDF certificate as soon as completing the Language Therapy course] Course curriculum Module 1: Language Therapy The Role of the Language Therapist The History of Language Therapy Practice The Scope of Practice The Language Therapy process The Role of Speech therapy Assistant in Current Healthcare Practice Summary Module 2: Study of Communication The Role of Interpersonal Communication The Components of Communication - Physical, Sensory, Cognitive, Perceptual, Interpersonal and Intrapersonal Communication Impairment or Disorder on the Individual How An Individual Interacts with Their Environment? Recognise Enablers and Barriers to Interpersonal Communication Summary Module 3: Components of Normal Speech, Language & Voice and Communication Disorders Key Components of Speech, Language and Voice The Process of Normal Speech and Language Acquisition Effective Conversational Skills The Different Types of Impairments/Disorders of Normal Speech, Language and Voice Acquired Brain Injuries and Cerebral Palsy Summary Module 4: Eating, Drinking and Swallowing Disorders Key Components of Eating, Drinking and Swallowing The Process of Normal Eating, Drinking and Swallowing Acquisition The Different Types of Difficulties of Eating, Drinking and Swallowing What May Eating, Drinking and Swallowing Intervention Involve? Give Examples of Communication profiles associated with disorders of eating, drinking and swallowing Summary Assessment Method After completing each module of the Language Therapy Course, you will find automated MCQ quizzes. To unlock the next module, you need to complete the quiz task and get at least 60% marks. Certification After completing the MCQ/Assignment assessment for this Language Therapy course, you will be entitled to a Certificate of Completion from Training Tale. The certificate is in PDF format, which is completely free to download. A printed version is also available upon request. It will also be sent to you through a courier for £13.99. Who is this course for? This Language Therapy course is for anyone who wants to: Gain the skills needed to work in the teaching and child care profession. Improve their speech therapy and language therapy skills. Make a career change and explore new career opportunities. Gain a formal, accredited qualification to improve their career opportunities. Requirements Students who intend to enrol in this Language Therapy course must meet the following requirements: Good command of the English language Must be vivacious and self-driven Basic computer knowledge A minimum of 16 years of age is required Career path Compete High provides the most expedient path to learning about Language Therapy, as well as the opportunity to practice your skills in a corporate setting. Certificates Certificate of completion Digital certificate - Included