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1208 Courses in Liverpool delivered Online

Medical Transcription Training - CPD Certified

By Wise Campus

Medical Transcription: Medical Transcription Training Course Online Do you want a course on Medical Transcription to keep you better prepared for your Medical Transcription profession? our course will help you on that case. On the very first module of the Medical Transcription course, you can get ideas of medical transcription from this introduction to Medical Transcription. Then the Medical Transcription course will teach all the WH questions of the Medical Transcription subject. This Medical Transcription also explains medical languages boot camp with other documentation preparation. Moreover, the Medical Transcription course will explain the communicate style and data protection tecniques as a medical transcription expert. Take the initial steps toward a successful long-term career by studying the Medical Transcription course. Special Offers of this Medical Transcription: Medical Transcription Training Course This Medical Transcription: Medical Transcription Training Course includes a FREE PDF Certificate. Lifetime access to this Medical Transcription: Medical Transcription Training Course Instant access to this Medical Transcription: Medical Transcription Training Course Get FREE Tutor Support to this Medical Transcription: Medical Transcription Training Course Medical Transcription: Medical Transcription Training Course Online An engaging introduction to medical transcription can be found in the Medical Transcription: Medical Transcription Course. You can learn how to create medical reports and the purpose of medical transcription from the Medical Transcription course. Along with other documentation preparation skills, this medical transcription program teaches medical languages. In addition, the Medical Transcription course will cover data protection and communication protocols for medical clients. Who is this course for? Medical Transcription: Medical Transcription Training Course Online Anyone may benefit from this Medical Transcription: Medical Transcription Training Course, including new grads, job seekers, and students. Requirements Medical Transcription: Medical Transcription Training Course Online To enrol in this Medical Transcription: Medical Transcription Training Course, students must fulfil the following requirements. To join in our Medical Transcription Training Course, you must have a strong command of the English language. To successfully complete our Medical Transcription Training Course, you must be vivacious and self driven. To complete our Medical Transcription: Medical Transcription Training Course, you must have a basic understanding of computers. A minimum age limit of 15 is required to enrol in this Medical Transcription Course. Career path Medical Transcription: Medical Transcription Training Course Online You may work as a medical transcriptionist, audio typist, medical office manager, and many other positions after finishing this course on Medical Transcription: Medical Transcription Training Course!

Medical Transcription Training - CPD Certified
Delivered Online On Demand1 hour 18 minutes
£12

Medical Secretary Diploma

5.0(1)

By Course Gate

Earn your"Medical Secretary Diploma and master the skills needed for a successful career in medical administration. Learn scheduling, medical records management, confidentiality, and more. Ideal for aspiring medical secretaries and healthcare professionals looking to enhance their administrative expertise. Enrol today!

Medical Secretary Diploma
Delivered Online On Demand3 hours 33 minutes
£11.99

Data Science & Machine Learning with Python

By IOMH - Institute of Mental Health

Overview of Data Science & Machine Learning with Python Join our Data Science & Machine Learning with Python course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Data Science & Machine Learning with Python course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Data Science & Machine Learning with Python course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now! This Data Science & Machine Learning with Python Course will help you to learn: Learn strategies to boost your workplace efficiency. Hone your skills to help you advance your career. Acquire a comprehensive understanding of various topics and tips. Learn in-demand skills that are in high demand among UK employers This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this Data Science & Machine Learning with Python. Enrol today and complete the course to achieve a certificate that can change your career forever. Details Perks of Learning with IOMH One-To-One Support from a Dedicated Tutor Throughout Your Course. Study Online - Whenever and Wherever You Want. Instant Digital/ PDF Certificate. 100% Money Back Guarantee. 12 Months Access. Process of Evaluation After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion - Digital / PDF Certificate After completing the Data Science & Machine Learning with Python course, you can order your CPD Accredited Digital / PDF Certificate for £5.99.  Certificate of Completion - Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. Shipping Charges: Inside the UK: £3.99 International: £10.99 Who Is This Course for? This Data Science & Machine Learning with Python is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand.  On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements You don't need any educational qualification or experience to enrol in the Data Science & Machine Learning with Python course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career Path The certification and skills you get from this Data Science & Machine Learning with Python Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors. 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 00:04:00 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 Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using NumPy 00:04:00 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 00:06:00 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 - Data Science & Machine Learning with Python 00:00:00

Data Science & Machine Learning with Python
Delivered Online On Demand10 hours 19 minutes
£10.99

Javascript with Data Visualisation

5.0(1)

By LearnDrive UK

Dive into JavaScript with a focus on data visualization. Master JavaScript fundamentals, control flow, error handling, and client-side validations. Create engaging visual representations using Google Chart. Perfect for anyone looking to combine coding skills with visual analytics.

Javascript with Data Visualisation
Delivered Online On Demand1 hour
£5

Python Programming Tutorials For Beginners

By simplivlearning

Want to learn everything about Python, from installing to coding, with a liberal does of fun sprinkled into the learning? Then, this Python Programming Tutorials For Beginners is what you need.

Python Programming Tutorials For Beginners
Delivered OnlineFlexible Dates
£3.57

AS Level Computer Science

By Spark Generation

Embark on a journey into the world of technology with Spark Generation! Learn the fundamentals of computer science, coding languages, and algorithmic thinking. Discover the logic behind programs and explore the creative potential of digital innovation.

AS Level Computer Science
Delivered Online On Demand48 hours
£4.50

IGCSE Computer Science

By Spark Generation

Embark on a journey into the world of technology with Spark Generation! Learn the fundamentals of computer science, coding languages, and algorithmic thinking. Discover the logic behind programs and explore the creative potential of digital innovation.

IGCSE Computer Science
Delivered Online On Demand48 hours
£4.50

A2 Level Computer Science

By Spark Generation

Embark on a journey into the world of technology with Spark Generation and our Cambridge self-paced courses! Learn the fundamentals of computer science, coding languages, and algorithmic thinking. Discover the logic behind programs and explore the creative potential of digital innovation.

A2 Level Computer Science
Delivered Online On Demand48 hours
£4.50

Educators matching " Coding"

Show all 8
Fun 2 Code

fun 2 code

Ellesmere Port

Fun 2 Learn Code offers coding classes and day camps for children and teens in the Austin area to learn the fundamentals of computer programming and video game development. working on a Scratch project We provide two types of learning opportunities for students: group classes and labs. After-school, homeschool and weekend options are available. No prior programming experience is needed for any of our labs and most of our classes. We also host monthly Coding Nights and periodic workshops. Classes Our group classes are instructor-led and cover a specific program or platform for a certain number of weeks. Classes are designed for beginner and intermediate level students. Options include Introduction to Coding, Minecraft Mods, Video Game Development, Python, Virtual Reality, Keyboarding and others. Labs In our coding labs, students are encouraged to explore technologies that interest them and to work at a pace that they enjoy. We offer ongoing year-round enrollment for our labs, so students can join at any time. Options include Scratch, Python, Java, video game development, Minecraft Mods, Unity, mobile app development, Javascript, web development, 2D/3D graphic design and animation, and more! No previous programming experience is required since the curriculum is geared to each one’s level and pace. Our classes and labs are held at our studio in Round Rock, located at 416 Chisholm Valley Drive. We also host workshops at other locations in the Austin area, including libraries and schools.

Calderstones School

calderstones school

Liverpool

I am exceptionally proud to lead and work in such a richly diverse school community in which students with different languages, cultures and religions learn together in harmony. The school's comprehensive nature is something that we value immensely. Our students are encouraged to explore, discover and question through a range of exciting learning opportunities both within and outside the classroom. The staff endeavour to provide a calm and stimulating environment where good behaviour and mutual respect is modelled by everyone and where everyone is valued. We work closely with parents/carers and the wider community to ensure the success of our students. We believe that children deserve the best possible chances in life and that they learn best when there are strong links between home and school. Over the last few years we have spoken constantly about raised expectations and we will continue to push this throughout this academic year, particularly as we look to re-set and recalibrate on the back on the impact of the pandemic. In every aspect of school life, we will raise the bar for students and staff with the view that 'nobody rises to low expectations'. In terms our curriculum delivery, student achievement and progress, their involvement in school and community life, the ways in which students wear the uniform and present their work with pride, the ways in which they speak to each other and the behaviours that they demonstrate within the school and the community in which it resides ... in all of these ways, our expectations will be more ambitious and explicit than ever before. To this end, we have developed a ‘Manifesto for Change’ which sets out the ways in which we aim to continue our journey to excellence and identifies the long-term priorities for the school. One of our main priorities this year will be to ensure, as far as we can, that no child is left behind and that every child is challenged by the curriculum that we have in place. Students should find things difficult, although not impossible, at times. They should struggle at times and be expected to think deeply about the work that they do. They shouldn’t be getting everything right all of the time; if they are, the work is too easy and they’re not being challenged. None of this means that they shouldn’t be enjoying their learning; being challenged can be enjoyable. The curriculum is the bread and butter of our educational offer and should be inspiring a real thirst for learning; we can only do this through supporting and challenging. I hope you enjoy finding out more about our school by browsing our website. Visits are encouraged and welcomed; we would be delighted to show you around our wonderful school.

Liverpool Hope University

liverpool hope university

Liverpool

Liverpool Hope University pursues a path of excellence in scholarship and collegial life without reservation or hesitation. The University’s distinctive philosophy is to ‘educate in the round’ – mind, body and spirit – in the quest for Truth, Beauty and Goodness. Liverpool Hope University is distinctive in that it is the only university foundation in Europe (and the USA) where Catholic and Anglican colleges have come together to form an integrated, ecumenical, Christian foundation. It has happened in Liverpool and nowhere else in Europe largely because of the presence in the 1980s of two remarkable church leaders: Bishop David Sheppard, the Bishop of the Anglican Diocese, and Archbishop Derek Worlock, the Archbishop of the Catholic Archdiocese that extends from Liverpool across the north of England. They confessed their faith to each other and took their congregations to visit each other’s cathedrals, a symbolic act of Christians working together in the context of northern Irish religious sectarianism. When the three colleges (St Katharine’s 1844, Notre Dame College 1856 and Christ’s College 1964) came together the name ‘Hope’ was adopted came from Hope Street that links both cathedrals - a living parable of what can happen when Christians unite and work together for the common good. This year we celebrate 175 years since the founding of our first college in 1844; in that year there were only six universities in England (two of them medieval) but all of them did not admit women, Catholics or Jews. The founding colleges of Liverpool Hope University were among the first few institutions to begin opening up higher education to the vast majority of England’s population. The Anglican Bishops of Liverpool, going back to the founding Bishop, Bishop Ryle, were all evangelicals. The friendship of the Anglican Bishop and the Catholic Archbishop was largely based on both their sharing of a mutual faith and their commitment to the poor. This adherence to historic Christian faith remains the university’s own commitment as it seeks to live out that faith in its life and work in a secularised British academy. At the beginning of each academic term we hold a Foundation Service to restate our foundational mission and values. Our Graduation ceremonies are held in alternating years in both the Anglican and Catholic Cathedrals in Liverpool.The new name of Liverpool Hope University was chosen to represent the ecumenical mission of the Institution. Liverpool Hope University was born in July 2005, when the Privy Council bestowed the right to use the University title. Research Degree Awarding Powers were granted by the Privy Council in 2009.