CPD Accredited. This online course covers how to interpret basic 12 lead ECG rhythms, ranging from Sinus Rhythm to ST elevation infarcts. It is suitable for beginners upwards as it covers an in depth 6 stage approach on how to interpret each rhythm individually and accurately. This course acts as an ideal course for those who are new to interpreting 12 lead ECGs and for those who require a refresher in order to boost their confidence and knowledge in this specialist area. The course will cover basic anatomy and physiology of the heart, along with the cardiac cycle and conductivity of the heart in order to give the background knowledge to move on to rhythm strips. The course will lead you through a visual pathway of an array of rhythms with self-test points throughout to enable you to complete the course with new found knowledge and confidence. ECG’s General Terms and Conditions, can be viewed here: https://ecgtraining.co.uk/about-us/policies/
Want to learn how to use Maven and SonarQube effectively for code building and code quality analysis as a DevOps engineer? Then you are in the right place. This learner-centered hands-on course will help you gain confidence in using important DevOps tools such as SVN, Maven, Jenkins, Chef, Puppet, Nagios, Splunk, Selenium, and more. Some basic knowledge of Linux, Git, and AWS EC2 will help you get the most out of this course.
Welcome to the Blender to Unreal Engine 3D Props Medieval Gallows course. In this course, we will be creating a set of medieval gallows with aged wooden planks and rope. These medieval gallows game assets also incorporate animated elements such as a collapsible platform that was used to run the executions in the medieval age.
Dive deep into the vast realm of Python data science with our meticulously crafted course: 'Python Data Science with Numpy, Pandas and Matplotlib'. Explore the intricate details of Python, setting the stage with Pandas and Numpy, before delving into the power of Python data structures. With topics ranging from Python Strings to Matplotlib Histograms, you'll gain a holistic insight, ensuring that every dataset you touch unveils its story compellingly. So, if you're keen on transmuting raw data into visual masterpieces or insights, this journey is tailor-made for you. Learning Outcomes Grasp foundational knowledge of Python and its data structures like strings, lists, and dictionaries. Understand the potential of NumPy, from basic array operations to handling multi-dimensional arrays. Master the versatility of Pandas, encompassing everything from dataframe conversions to intricate operations like aggregation and binning. Efficiently manage, manipulate, and transform data using Pandas' diverse functionalities. Create visually striking and informative graphs using the power of Matplotlib. Why buy this Python Data Science with Numpy, Pandas and Matplotlib course? 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 Python Data Science with Numpy, Pandas and Matplotlib 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 Python Data Science with Numpy, Pandas and Matplotlib course for? Beginners eager to jumpstart their journey in Python data science. Analysts looking to enhance their data manipulation skills using Python. Statisticians keen on expanding their toolset with Python-based libraries. Data enthusiasts desiring a deep dive into Python's data libraries and structures. Professionals aiming to upgrade their data visualisation techniques. Prerequisites This Python Data Science with Numpy, Pandas and Matplotlib does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Python Data Science with Numpy, Pandas and Matplotlib 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 Data Scientist: £40,000 - £80,000 Python Developer: £35,000 - £70,000 Data Analyst: £30,000 - £55,000 Business Intelligence Analyst: £32,000 - £60,000 Research Analyst: £28,000 - £52,000 Data Visualization Engineer: £33,000 - £65,000 Course Curriculum Course Introduction and Table of Contents Course Introduction and Table of Contents 00:09:00 Introduction to Python, Pandas and Numpy Introduction to Python, Pandas and Numpy 00:07:00 System and Environment Setup System and Environment Setup 00:08:00 Python Strings Python Strings - Part 1 00:11:00 Python Strings - Part 2 00:09:00 Python Numbers and Operators Python Numbers and Operators - Part 1 00:06:00 Python Numbers and Operators - Part 2 00:07:00 Python Lists Python Lists - Part 1 00:05:00 Python Lists - Part 2 00:06:00 Python Lists - Part 3 00:05:00 Python Lists - Part 4 00:07:00 Python Lists - Part 5 00:07:00 Tuples in Python Tuples in Python 00:06:00 Sets in Python Sets in Python - Part 1 00:05:00 Sets in Python - Part 2 00:04:00 Python Dictionary Python Dictionary - Part 1 00:07:00 Python Dictionary - Part 2 00:07:00 NumPy Library - Introduction NumPy Library Intro - Part 1 00:05:00 NumPy Library Intro - Part 2 00:05:00 NumPy Library Intro - Part 3 00:06:00 NumPy Array Operations and Indexing NumPy Array Operations and Indexing - Part 1 00:04:00 NumPy Array Operations and Indexing - Part 2 00:06:00 NumPy Multi-Dimensional Arrays NumPy Multi-Dimensional Arrays - Part 1 00:07:00 NumPy Multi-Dimensional Arrays - Part 2 00:06:00 NumPy Multi-Dimensional Arrays - Part 3 00:05:00 Introduction to Pandas Series Introduction to Pandas Series 00:08:00 Introduction to Pandas Dataframes Introduction to Pandas Dataframes 00:07:00 Pandas Dataframe conversion and drop Pandas Dataframe conversion and drop - Part 1 00:06:00 Pandas Dataframe conversion and drop - Part 2 00:06:00 Pandas Dataframe conversion and drop - Part 3 00:07:00 Pandas Dataframe summary and selection Pandas Dataframe summary and selection - Part 1 00:06:00 Pandas Dataframe summary and selection - Part 2 00:06:00 Pandas Dataframe summary and selection - Part 3 00:07:00 Pandas Missing Data Management and Sorting Pandas Missing Data Management and Sorting - Part 1 00:07:00 Pandas Missing Data Management and Sorting - Part 2 00:07:00 Pandas Hierarchical-Multi Indexing Pandas Hierarchical-Multi Indexing 00:06:00 Pandas CSV File Read Write Pandas CSV File Read Write - Part 1 00:05:00 Pandas CSV File Read Write - Part 2 00:07:00 Pandas JSON File Read Write Pandas JSON File Read Write Operations 00:07:00 Pandas Concatenation Merging and Joining Pandas Concatenation Merging and Joining - Part 1 00:05:00 Pandas Concatenation Merging and Joining - Part 2 00:04:00 Pandas Concatenation Merging and Joining - Part 3 00:04:00 Pandas Stacking and Pivoting Pandas Stacking and Pivoting - Part 1 00:06:00 Pandas Stacking and Pivoting - Part 2 00:05:00 Pandas Duplicate Data Management Pandas Duplicate Data Management 00:07:00 Pandas Mapping Pandas Mapping 00:04:00 Pandas Grouping Pandas Groupby 00:06:00 Pandas Aggregation Pandas Aggregation 00:09:00 Pandas Binning or Bucketing Pandas Binning or Bucketing 00:08:00 Pandas Re-index and Rename Pandas Re-index and Rename - Part 1 00:04:00 Pandas Re-index and Rename - Part 2 00:05:00 Pandas Replace Values Pandas Replace Values 00:05:00 Pandas Dataframe Metrics Pandas Dataframe Metrics 00:07:00 Pandas Random Permutation Pandas Random Permutation 00:08:00 Pandas Excel sheet Import Pandas Excel sheet Import 00:07:00 Pandas Condition Selection and Lambda Function Pandas Condition Selection and Lambda Function - Part 1 00:05:00 Pandas Condition Selection and Lambda Function - Part 2 00:05:00 Pandas Ranks Min Max Pandas Ranks Min Max 00:06:00 Pandas Cross Tabulation Pandas Cross Tabulation 00:07:00 Matplotlib Graphs and plots Graphs and plots using Matplotlib - Part 1 00:06:00 Graphs and plots using Matplotlib - Part 2 00:02:00 Matplotlib Histograms Matplotlib Histograms 00:03:00 Resource File Resource File - Python Data Science with Numpy, Pandas and Matplotlib 00:00:00
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jQuery is a very powerful framework used by all the big companies like Microsoft, Apple, Google etc. It is cross-platform.
Learn to efficiently use Midjourney, an AI image-generation tool sweeping the globe. Generate images with artificial intelligence (AI) in a revolutionary way using text prompts or simple drawing tools. So, join this course and let's get your first idea on the screen!
Course Overview: This Personal Productivity Course is designed to equip learners with the essential skills and techniques to enhance their productivity, both personally and professionally. Covering key principles of time management, goal setting, and focus, the course provides valuable strategies to help individuals manage their tasks more efficiently, reduce distractions, and achieve their goals effectively. Learners will gain a deeper understanding of how to prioritise, manage workloads, and stay motivated, all while cultivating a mindset for continuous improvement. Upon completion, learners will be able to apply these skills to increase productivity and performance in various aspects of life and work. Course Description: The Personal Productivity Course delves into essential topics such as setting achievable goals, mastering prioritisation, eliminating distractions, and fostering self-motivation. Learners will explore strategies to optimise their time management, cultivate focus, and develop a systematic approach to tackling tasks. With practical insights, the course will guide individuals in overcoming procrastination, managing stress, and ensuring long-term success. The course is suitable for beginners and professionals alike, providing the foundation for enhanced productivity and a more balanced, goal-oriented life. By the end of the course, learners will have the skills to effectively plan, execute, and measure their productivity in both personal and professional settings. Course Modules: • Module 01: Introduction • Module 02: Core Principles of Focus & Productivity (See full curriculum) Who is this course for? Individuals seeking to improve their personal productivity. Professionals aiming to enhance career development through better time management. Beginners with an interest in learning productivity techniques for professional or personal growth. Anyone looking to optimise their focus, organisation, and performance. Career Path: Personal Assistant Project Manager Executive Assistant Operations Manager Team Leader Entrepreneur Administrative Coordinator Freelance Consultant