902 Library courses in Edinburgh delivered Online

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

Premium Bundle of all Time | Ofqual Regulation + ATHE Awards + QLS Endorsement | Assessment & Tutor Support Included

Premium Bundle of all Time | Ofqual Regulation + ATHE Awards + CPD Accreditation | Assessment & Tutor Support Included

Premium Bundle of all Time | Ofqual Regulation + ATHE Awards + QLS Endorsement | Assessment & Tutor Support Included

Duration 4.875 Days 29.25 CPD hours This course is intended for VMware vSphere: Install, Configure, Manage features intensive hands-on training that focuses on installing, configuring, and managing VMware vSphere. This course prepares you to administer a vSphere infrastructure for an organization of any size and forms the foundation for most otherVMware technologies in the software-defined data center. Overview Describe the software-defined data center (SDDC) Explain the vSphere components and their function in the infrastructure Describe the benefits and capabilities of VMware Skyline Install and configure ESXi hosts Deploy and configure VMware vCenter Server Appliance™ Use VMware vSphere Client™ to manage the vCenter Server inventory and the vCenter Server configuration Manage, monitor, back up, and protect vCenter Server Appliance Create virtual networks with vSphere standard switches Describe the storage technologies supported by vSphere Configure virtual storage using iSCSI and NFS storage Create and manage VMware vSphere VMFS datastores Use the vSphere Client to create virtual machines, templates, clones, and snapshots Create a content library and deploy virtual machines from templates in the library Manage virtual machine resource use Migrate virtual machines with VMware vSphere vMotion and VMware vSphere Storage vMotion Create and manage a vSphere cluster that is enabled with VMware vSphere High Availability and VMware vSphere Distributed Resource Scheduler ™ Discuss solutions for managing the vSphere life cycle Use VMware vSphere Lifecycle Manager™ to perform upgrades to ESXi hosts and virtual machines This is an official VMware IT Academy course with official courseware and labs. Course introduction Introductions and course logistics Course objectives Introduction to vSphere and the Software-Defined Data Center Explain basic virtualization concepts Describe how vSphere fits into the software-defined data center and the cloud infrastructure Explain how vSphere interacts with CPUs, memory, networks, and storage Recognize the user interfaces for accessing the vCenter Server system and ESXi hosts Describe the ESXi host architecture Navigate the Direct Console User Interface (DCUI) to configure an ESXi host Recognize ESXi host user account best practices Install an ESXi host Use VMware Host Client? to configure ESXi host settings Describe how to proactively manage your vSphere environment using VMware Skyline Virtual Machines Create and provision a virtual machine Explain the importance of VMware Tools? Install VMware Tools Identify the files that make up a VM Recognize the components of a VM Recognize virtual devices supported by a VM Describe the benefits and use cases for containers Identify the parts of a container system vCenter Server Describe the vCenter Server architecture Discuss how ESXi hosts communicate with vCenter Server Deploy and configure vCenter Server Appliance Use vSphere Client to manage the vCenter Server inventory Add data center, organizational objects, and hosts to vCenter Server Use roles and permissions to enable users to access objects in the vCenter Server inventory Back up vCenter Server Appliance Monitor vCenter Server tasks, events, and appliance health Use VMware vCenter Server© High Availability to protect a vCenter Server Appliance Configuring and Managing Virtual Networks Create and manage standard switches Describe the virtual switch connection types Configure virtual switch security, traffic-shaping, and load-balancing policies Compare vSphere distributed switches and standard switches Configuring and Managing Virtual Storage Identify storage protocols and storage device types Discuss ESXi hosts using iSCSI, NFS, and Fibre Channel storage Create and manage VMFS and NFS datastores Explain how multipathing works with iSCSI, NFS, and Fibre Channel storage Recognize the components of a VMware vSAN? configuration Virtual Machine Management Use templates and cloning to deploy new virtual machines Modify and manage virtual machines Create a content library and deploy virtual machines from templates in the library Use customization specification files to customize a new virtual machine Perform vSphere vMotion and vSphere Storage vMotion migrations Describe the Enhanced vMotion Compatibility feature Create and manage virtual machine snapshots Examine the features and functions of VMware vSphere© Replication? Describe the benefits of VMware vSphere© Storage APIs ? Data Protection Resource Management and Monitoring Discuss CPU and memory concepts in a virtualized environment Describe what overcommitment of a resource means Describe methods for optimizing CPU and memory usage Use various tools to monitor resource use Create and use alarms to report certain conditions or events vSphere Clusters Describe the functions of a vSphere DRS cluster Create a vSphere DRS cluster Monitor a vSphere cluster configuration Describe options for making a vSphere environment highly available Explain the vSphere HA architecture Configure and manage a vSphere HA cluster Examine the features and functions of VMware vSphere© Fault Tolerance Describe the function of the vSphere© Cluster Service vSphere Lifecycle Management Recognize the importance of vCenter Server Update Planner Describe how VMware vSphere© Lifecycle Manager? works Describe how to update ESXi hosts using baselines Validate ESXi host compliance using a cluster image Describe how to upgrade VMware Tools and VM hardware Describe VMware vSphere© Lifecycle Manager? and VMware vSAN? integration

Expanded Talks webinar about design in with VR on 13/10 at 19h CET. Live demo with studio Lavamachine Design in VR with Multibrush and other VR tools.

Premium Bundle of all Time | Ofqual Regulation + ATHE Awards + CPD Accreditation | Assessment & Tutor Support Included

Machine learning isn’t just for self-driving cars and game-playing robots—it’s also helping identify whether someone’s wearing a mask or not. This course takes you through the full project lifecycle of building a Covid Mask Detector, using one of the most relevant applications of computer vision in recent years. Whether you're a data enthusiast or a coding hobbyist, you’ll enjoy diving into this machine learning challenge with a purpose that’s easy to relate to and timely. With clear, structured guidance, you'll explore how to prepare image data, train a neural network, and apply detection techniques—all from the comfort of your own screen. The content is delivered with clarity and a dash of wit, making the learning journey not just informative, but surprisingly enjoyable. You’ll walk away with confidence in building a full machine learning project, specifically tailored for image classification, and yes—taught in plain, human English (no jargon jungle here). Whether you're brushing up your Python skills or simply curious how AI spots face masks, this course offers an insightful experience in smart automation, delivered with a professional tone and just enough character to keep you grinning as you code. Learning Outcomes: Develop a Covid mask detector using machine learning. Master OpenCV, a popular computer vision library. Build models with TensorFlow. Design and build the app, upload files, and deploy it on AWS. Gain valuable experience in machine learning app development. The Hands-on Machine Learning Project - Covid Mask Detector course is designed to provide you with the skills and knowledge needed to develop a mask detector using deep learning. In this course, you'll learn how to master OpenCV, an open-source computer vision library used for image processing and face detection. You'll also learn how to build and train a deep learning model using Tensorflow, a popular machine learning framework. The course is perfect for aspiring data scientists, machine learning engineers, and developers who want to make a positive impact on society by contributing to public health and safety efforts. By the end of this course, you'll have a deep understanding of how to develop a mask detector app that can be used to detect whether individuals are wearing masks in public spaces. You'll be able to master OpenCV and use it to preprocess and detect faces in images. You'll also learn how to build and train a deep learning model using TensorFlow and how to deploy your mask detector app on AWS. This course provides a unique opportunity for individuals to gain real-world experience in developing cutting-edge technology that can make a positive impact on society. Hands on Machine Learning Project - Covid Mask Detector Course Curriculum Section 01: Introduction Introduction to Course Section 02: Mastering OpenCV Getting System Ready Read and Write Images Resize and Crop Working with Shapes Working with Text Section 03: Pre-Requisite for Face Detection Pre-Requisite for Face Detection Detect the Face Section 04: Deep Learning with Tensorflow Introduction to Deep Learning with Tensorflow Model Building Training the Mask Detector Saving the Best Model Basic Front End Design of App File Upload Interface for App App Prep App Build and Testing AWS Deployment AWS Deployment Continued How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Aspiring data scientists. Machine learning engineers. Developers interested in machine learning app development. Anyone interested in developing technology to fight the pandemic. Professionals looking to upskill in the latest technology. Career path Data Scientist: £40,000 to £80,000 per year. Machine Learning Engineer: £55,000 to £90,000 per year. Artificial Intelligence Developer: £40,000 to £80,000 per year. Computer Vision Engineer: £40,000 to £80,000 per year. Deep Learning Engineer: £55,000 to £90,000 per year. Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9.

Premium Bundle of all Time | Ofqual Regulation + ATHE Awards + QLS Endorsement | Assessment & Tutor Support Included

Begin your journey in compliance management with practical knowledge of the laws and legislations that make up the regulatory field in the United Kingdom. Do you know that FCA sets an annual CPD requirement both for senior managers and employees of financial service firms? As per TC 2.1.15 & 2.1.16, the requirement is 35 hours in each 12 months, including 21 hours of structured CPD activities. Furthermore, TC 2.1.20G27/05/2022 defines structures CPD activities as follows: “Examples of structured continuing professional development activities include participating in courses, seminars, lectures, conferences, workshops, web-based seminars or e-learning.” Our FCA Compliance Essentials Bundle, fulfilling and even exceeding the FCA requirement in terms of CPD hours, is ideal for any professional within Financial Services. Study method Online, self-paced Course format Video with subtitles Duration 40 hours Qualification No formal qualification CPD 40 CPD hours / points Certificates Certificate of Completion - Free Description LGCA's FCA Compliance Essentials eLearning library currently includes the following courses (new courses are added on a regular basis): AML Risk Assessment AML Suspicious Activity Reports and Suspicious Transaction Reports (SAR/STRs) Anti-Bribery and Corruption Anti-Money Laundering and Counter Terrorist Finance Approved Persons Regime Assessing and Managing AML Risks Building an AML Risk-based Approach CASS Introduction Complaints Handling Compliance Introduction Compliance Monitoring and Testing Conduct Rules for All Staff Conflict of Interest (COI) Consumer Duty Establishing and Maintaining a Strong CDD Programme Ethics, Integrity and Fairness in Financial Services FCA: the Role and Approach Financial Promotions Regulation Fraud Detection and Prevention GDPR Awareness Introduction to Cybersecurity Introduction to Know Your Client (KYC) and Customer Due Diligence (CDD) Market Abuse (MAR) Operational Resilience Senior Managers and Certification Regime SM&CR – The Conduct Rules Suspicious Transactions/Activity Reporting The Value of Customer Due Diligence (CDD) Treating Customers Fairly Vulnerable Customer Management Whistleblowing Creating a Compliance Culture in Financial Services Who is this course for? Financial Services Providers Accounting Offices Financial Institutions Brokers Wealth & Fund Managers Investment Firms Insurance Companies Law Firms Compliance Consultants Payment Solutions Providers FinTech & RegTech Companies Fiduciary Services Firms