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Packt

PostgreSQL

Data Science

This complete training program comprising levels 1 and 2 is divided into multi-sequential sections to let you gain comprehensive knowledge and understanding of SQL and data analysis. This two-level course is designed to kickstart your SQL knowledge and perform various data analysis tasks and implement SQL in projects independently and efficiently.

Master SQL for Data Analysis

General Admission

Python

Are you someone wishing to learn the skills to analyze data professionally using Power BI? Do you want to learn to create impressive reports? Then this is the right course for you! Learn the complete workflow in Power BI from A-to-Z and advanced analytics with DAX-calculated columns and measures, forecasting, and advanced analytics.

Microsoft Power BI - The Complete Masterclass [2023 EDITION]

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				<p><span>Embark on a comprehensive journey into the world of MySQL with a focus on its applications in Data Science and Analytics. This course is structured to take you from the fundamentals to advanced topics in MySQL Server. Covering SQL basics, data manipulation and definition, control and analytic functions, and database management, you'll acquire the essential skills for harnessing MySQL's power in data-driven decision-making.</span></p><p><b id="docs-internal-guid-6a582f22-7fff-d807-19e0-b5dad8f04cd9"><br /></b></p><p><span>Learning Outcomes:</span></p><ul><li><p><span>Establish a strong foundation in SQL and MySQL.</span></p></li><li><p><span>Set up and configure SQL Server for efficient data handling.</span></p></li><li><p><span>Master SQL's Data Manipulation, Definition, and Control Language.</span></p></li><li><p><span>Create and optimize SQL queries for data analysis.</span></p></li><li><p><span>Perform advanced data analytics using SQL.</span></p></li><li><p><span>Understand the power of GROUP BY and JOIN statements.</span></p></li><li><p><span>Implement data constraints and views for data integrity and security.</span></p></li><li><p><span>Develop proficiency in stored procedures, data import/export, and database backup/restore.</span></p></li></ul><p><b><br /></b></p><p><span>Why buy this Learn MySQL from Scratch for Data Science and Analytics?</span><span> </span></p><ul><li><p><span>Unlimited access to the course for forever</span></p></li><li><p><span>Digital Certificate, Transcript, student ID all included in the price</span></p></li><li><p><span>Absolutely no hidden fees</span></p></li><li><p><span>Directly receive CPD accredited qualifications after course completion</span></p></li><li><p><span>Receive one to one assistance on every weekday from professionals</span></p></li><li><p><span>Immediately receive the PDF certificate after passing</span></p></li><li><p><span>Receive the original copies of your certificate and transcript on the next working day</span></p></li><li><p><span>Easily learn the skills and knowledge from the comfort of your home</span></p></li></ul><p><b><br /></b></p><p><span>Certification</span></p><p><span>After studying the course materials of the </span><span>Learn MySQL from Scratch for Data Science and Analytics</span><span> you will be able to take the MCQ test that will assess your knowledge. 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.</span></p><p><b><br /></b></p><p><span>Who is this course for?</span></p><p><span>This </span><span>Learn MySQL from Scratch for Data Science and Analytics</span><span> course is ideal for</span></p><ul><li><p><span>Aspiring Data Scientists and Analysts.</span></p></li><li><p><span>Database Administrators and Developers.</span></p></li><li><p><span>Students and professionals seeking to enter the field of Data Science.</span></p></li><li><p><span>Anyone looking to enhance their SQL and MySQL skills for data-related roles.</span></p></li></ul><p><b><br /></b></p><p><span>Prerequisites</span></p><p><span>This </span><span>Learn MySQL from Scratch for Data Science and Analytics</span><span> 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.</span></p><p><b><br /></b></p><p><span>Career path</span></p><p></p><ul><li><p><span>Data Analyst: £25,000 - £50,000 per year.</span></p></li><li><p><span>Database Administrator: £30,000 - £60,000 per year.</span></p></li><li><p><span>SQL Developer: £30,000 - £60,000 per year.</span></p></li><li><p><span>Data Scientist: £40,000 - £80,000 per year.</span></p></li><li><p><span>Business Intelligence Analyst: £35,000 - £65,000 per year.</span></p></li></ul>					</div>
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				<h3>
	<span>Course Curriculum</span>
</h3>

<div>
<table width="100%">				<tbody><tr>
					<td colspan="4">Learn MySQL from Scratch for Data Science and Analytics</td>
				</tr>
								<tr>
					<td colspan="4">Section 01: Getting Started</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>How to get course requirements</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Getting started on Windows, Linux or Mac</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>How to ask great questions</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>FAQ's</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>What is Source Code?</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 02: SQL Server setting up</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Section Introduction</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>MySQL Server Installation</td>
					<td> </td>
					<td><span><i></i> 00:14:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Connect MySQL Server Instance</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>MySQL Workbench overview</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Download and Restore Sample Database</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 03: SQL Database basics</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Section Introduction</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Overview of Databases</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating Database</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>SQL Data Types</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Column Data Types on Workbench</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating Table</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Overview of Primary and Foreign Key</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Primary Key</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Foreign Key</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating Temporary tables</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>EER - Enhanced Entity Relationship Diagrams</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 04: SQL DML (Data Manipulation Language)</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Section Introduction</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Insert statement</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Update statement</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Delete statement</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 05: SQL DDL (Data Definition Language)</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Section Introduction</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>CREATE table statement</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>DROP statement</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>ALTER statement</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>TRUNCATE statement</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>COMMENT in query</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>RENAME table</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 06: SQL DCL (Data Control Language)</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Create Database user</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>GRANT permissions</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>REVOKE permissions</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 07: SQL Statement Basic</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Section Introduction</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>SQL Statement basic</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>SELECT Statement</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>SELECT DISTINCT</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>SELECT with column headings</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Column AS statement</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>DASHBOARD Analytics</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 08: Filtering Data rows</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>SELECT WHERE Clause - theory</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>SELECT WHERE Clause - practical</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 09: Aggregate functions for Data Analysis</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Sum()</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Min()-Max()</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 10: SQL Data Analyticstatements</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Order By statement</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>SELECT TOP 3 records</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>BETWEEN command</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>IN operator</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Search Data usingLIKE cards</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 11: SQL Group by statement</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Section Introduction</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Group by - theory</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Analytics with Group By</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>HAVING statement</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 12: JOINS</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Overview of Joins</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>What are Joins</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Inner join</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Left outer join</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Right outer join</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Union</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>CERTESIAN Product or Cross Join</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Query Exercise</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution for Query Exercise</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 13: SQL Constraints</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Section introduction</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Check constraint</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>NOT NULL constraint</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>UNIQUE constraint</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 14: Views</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating Views</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Analytic Views from multiple tables</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 15: Advanced SQL Functions</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Section Introduction</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Timestamp</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Extract from timestamp</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Mathematical scalar functions</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>String functions3</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Advanced functions</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Sub Queries</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>SELECT with calculations</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 16: SQL Stored procedures</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Create stored procedure</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Stored procedure with parameter</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Drop Procedure</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 17: Import &amp; Export data</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Section Introduction</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Import .csv file</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Export Data to .csv file</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 18: Backup and Restore Database</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Section Introduction</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating Database backup</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Restoring Database backup</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
				</tbody></table></div>

			</div>

Studyhub UK

Learning & Development

Data Engineering

Microsoft SQL

AWS Certified Database

Data Skills

Trainers Course

Learn MySQL from Scratch for Data Science and Analytics

ICDL (International Certification of Digital Literacy)

Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3

Data Visualization

Data Management

Discover Microsoft Fabric's architecture, master Data Engineering with OneLake and Spark, and elevate your skills in data warehousing and real-time processing. Compare SQL and KQL for better insights, and improve storytelling using Power BI. Finally, you will end with practical data science techniques and data management methods.

Microsoft Fabric Complete Guide - The Future of Data with Fabric

<p><strong>Get Hard Copy + PDF Certificates + Transcript + Student ID Card + e-Learning App as a Gift - Enrol Now</strong></p> <p>Healthcare assistants (HCAs) are crucial members of any medical team and are in high demand in the UK. They are always there to help physicians and nurses in their work and to care for the patients. Healthcare assistants can provide treatment in a variety of settings, including clinics, hospitals, hospices, and mental health facilities. Some people can view this as a stepping stone to higher-level careers in the healthcare industry.</p> <p>If you are empathetic, kind, and driven to help others, you already have half the abilities needed. Enrol in our Health Care Assistant bundle course, and you'll be prepared to shine.</p> <p><strong>This Bundle Consists of the following Premium courses: </strong></p> <ul> <li><strong></strong><strong>Course 01: </strong>Healthcare Assistant Training</li><li><strong></strong><strong>Course 02: </strong>Medical Law</li><li><strong></strong><strong>Course 03: </strong>European Medical Device Regulations</li><li><strong></strong><strong>Course 04: </strong>Vaccine Management</li><li><strong></strong><strong>Course 05: </strong>Clinical Observations Skills</li><li><strong></strong><strong>Course 06: </strong>Medication Administration Level 4</li><li><strong></strong><strong>Course 07: </strong>Medical Transcription</li><li><strong></strong><strong>Course 08: </strong>Nurse Prescribing Diploma</li><li><strong></strong><strong>Course 09: </strong>Phlebotomy</li><li><strong></strong><strong>Course 10: </strong>Wound Care Level 2</li><li><strong></strong><strong>Course 11: </strong>Verification of Death Training for Nurses</li><li><strong></strong><strong>Course 12: </strong>Consent in Healthcare</li><li><strong></strong><strong>Course 13: </strong>Diabetes Care Diploma</li><li><strong></strong><strong>Course 14: </strong>Public Health</li></ul> <p><strong>Learning Outcomes</strong></p> <ul> <li>Get an insight into training.</li><li>Explore the medical law based in the UK.</li><li>Learn the European medical device regulations.</li><li>Explore the core concepts of vaccine management and clinical observational skills.</li><li>Recognise the importance of medication administration and medical transcription.</li><li>Gain a better understanding of Phlebotomy and wound care.</li><li>Learn how to care for diabetic patients.</li><li>Get an overview of public health.</li></ul><p><strong>Curriculum</strong></p> <p><strong> Course 01: Healthcare Assistant Training</strong></p> <ul> <li>Module 01: Working in Different Healthcare Settings</li><li>Module 02: Understanding Legal, Professional Standards of Practice and Ethical Aspects of Health Care Part - 1</li><li>Module 03: Understanding Legal, Professional Standards of Practice and Ethical Aspects of Health Care Part - 2</li><li>Module 04: Maintaining Medical Records</li><li>Module 05: Confidentiality in a Medical Environment</li><li>Module 06: Health and Safety Responsibilities</li><li>Module 07: Hygiene in Nursing</li><li>Module 08: Infection Control</li><li>Module 09: Mobility and Immobility Issues of Patients in Nursing</li><li>Module 10: Rights and Responsibilities as a Health and Social Care Worker</li><li>Module 11: Role as A Caregiver and Healthcare Professional</li><li>Module 12: Providing Care or Treatment to People Who Lack Capacity</li><li>Module 13: Managing Service Delivery in Health and Social Care</li><li>Module 14: Medical Jargon and Terminology</li><li>Module 15: Effects of Covid-19 on Human Life</li><li>Module 16: Preventions and Social Measures to Be Taken</li><li>Module 17: Information Technology in Health Care</li><li>Module 18: Artificial Intelligence, Data Science and Technological Solutions against Covid-19</li></ul><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        140 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                             <p>For anyone who is interested to learn.</p> <p><strong>Note: Kindly note that these courses will not make you eligible to work professionally.</strong></p> 
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                             <p><strong>None.</strong></p> 
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                             <p>With the knowledge gained from the bundle course, you will be able to explore different career options such as -</p> <ul> <li>Health Care Assistant</li><li>Medical Social Worker</li><li>Home Care Assistant</li></ul> <p>In the United Kingdom, the average salary of these professions ranges from £22,000 - £32,000 per annum.</p> 
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            Included
        </p>
            <div> <p>You will get the PDF Certificate for the title course (<strong>Healthcare Assistant Training</strong>) absolutely Free!</p> </div>
        <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div> <p>You will get the Hard Copy certificate for the title course (<strong>Healthcare Assistant Training</strong>) absolutely Free! Other Hard Copy certificates are available for £10 each. </p> <p>Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.</p> </div>

                        </div>

Apex Learning

Health Care Assistant

<p>Tired of browsing and searching for the course you are looking for? Can't find the complete package that fulfils all your needs? Then don't worry as you have just found the solution. Take a minute and look through this 14-in-1 extensive bundle that has everything you need to succeed in <strong>Social Care </strong>and other relevant fields!</p><p>After surveying thousands of learners just like you and considering their valuable feedback, this all in one <strong>Social Care </strong>bundle has been designed by industry experts. We prioritised what learners were looking for in a complete package and developed this in-demand course that will enhance your skills and prepare you for the competitive job market.</p><p>Also, our <strong>Social Care </strong>experts are available for answering your queries and help you along your learning journey. Advanced audiovisual learning modules of these courses are broken down into little chunks so that you can learn at your own pace without being overwhelmed by too much material at once.</p><p>Furthermore, to help you showcase your expertise in <strong>Social Care, </strong> we have prepared a special gift of 1 hardcopy certificate and 1 PDF certificate for the title course completely free of cost. These certificates will enhance your credibility and encourage possible employers to pick you over the rest.</p><p><strong>This Bundle Consists of the following Premium courses: </strong></p><ul><li><strong>Course 01: </strong>Level 4 Diploma in Health and Social Care Management</li><li><strong>Course 02: </strong>Work Preparation for Adult Social Care Level 5</li><li><strong>Course 03: </strong>Mental Health Laws and Awareness - Level 2</li><li><strong>Course 04: </strong>Level 3 Residential Childcare Worker</li><li><strong>Course 05: </strong>Safeguarding Children Level 3</li><li><strong>Course 06: </strong>CPR and Paediatric First Aid Course</li><li><strong>Course 07: </strong>Domestic Violence and Abuse Awareness - Level 2</li><li><strong>Course 08: </strong>Family Law 2021</li><li><strong>Course 09: </strong>Family Support Worker Diploma</li><li><strong>Course 10: </strong>Consent in Healthcare</li><li><strong>Course 11: </strong>Diabetes Care Diploma</li><li><strong>Course 12: </strong>Nutrition and Diet Awareness</li><li><strong>Course 13: </strong>Addiction and Mental Health - Dual Diagnosis</li><li><strong>Course 14: </strong>Effective Communication Skills Diploma</li></ul><p><strong>Benefits you'll get choosing Apex Learning for this Social Care:</strong></p><ul><li>Pay once and get lifetime access to 14 CPD courses</li><li>Certificates, student ID for the title course included in a one-time fee</li><li>Free up your time - don't waste time and money travelling for classes</li><li>Accessible, informative modules designed by expert instructors</li><li>Learn at your ease - anytime, from anywhere</li><li>Study the course from your computer, tablet or mobile device</li><li>CPD accredited course - improve the chance of gaining professional skills</li></ul><p><strong>How will I get my Certificate?</strong></p><p>After successfully completing the course you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement.</p><ul><li><strong>PDF Certificate: Free (For The Title Course)</strong></li><li><strong>Hard Copy Certificate: Free (For The Title Course)</strong></li></ul><p><strong>Curriculum of the Bundle </strong></p><p><strong>Course 01: Level 4 Diploma in Health and Social Care Management</strong></p><ul><li>Introduction</li><li>Communication and its Relevance</li><li>Rights and Responsibilities</li><li>Role as A Caregiver and Healthcare Professional</li><li>Promoting Equality, Diversity and Rights</li><li>Important Principles and Policies</li><li>Understanding Legal, Professional Standards of Practice and Ethical Aspects of Health Care Part - 1</li><li>Understanding Legal, Professional Standards of Practice and Ethical Aspects of Health Care Part - 2</li><li>Safeguarding Vulnerable Individuals</li><li>Health and Safety Responsibilities</li><li>The Economics of Healthcare</li><li>Strategic Marketing</li><li>Managing Finance</li><li>Managing Service Delivery</li></ul><p><strong>Course 02: Work Preparation for Adult Social Care Level 5</strong></p><p><strong>Adult Nursing Training</strong></p><ul><li>Introduction to Nursing</li><li>Working in Different Healthcare Settings</li><li>Understanding legal, professional standards of practice and ethical aspects of health care- Part 1 and 2</li><li>Effective Communication in Nursing</li><li>Health and Safety in Nursing</li><li>Hygiene in Nursing</li><li>Infection Control</li><li>Asepsis in Nursing</li><li>Medication Administration in Nursing</li><li>Adult Care in Different Life Stages</li><li>Understanding Immune System in Nursing</li><li>Rest and Sleep Management in Nursing</li><li>Mobility and Immobility Issues of Patients in Nursing</li><li>Pain Management for Nurses</li><li>Nutrition in Nursing</li><li>Fluid and Electrolyte Balance</li><li>Assisting with Elimination</li><li>Oxygenation in Nursing</li></ul><p><strong>Health and Social Care Training</strong></p><ul><li>Introduction</li><li>Communication and its Relevance</li><li>Role as A Caregiver and Healthcare Professional</li><li>Working in Health and Social Care; Promoting Equality, Diversity and Rights</li><li>Important Principles and Policies in Health and Social Care Work</li><li>Safeguarding Vulnerable Individuals</li><li>Health and Safety Responsibilities</li><li>Risk Management</li></ul><p><strong>Course 03: Mental Health Laws and Awareness - Level 2</strong></p><ul><li>The Mental Capacity Act</li><li>Interface with Legislation, Policy and Procedures</li><li>Deprivation of Liberty Safeguards</li><li>The Mental Capacity Act (2005) and Deprivation of Liberty Safeguards During a Pandemic</li><li>Mental Health Legislation and Services</li><li>Liberty Protection Safeguards (LPS)</li></ul><p><strong>Course 04: Level 3 Residential Childcare Worker</strong></p><ul><li>Introduction to Child Psychology</li><li>Impacts of Separation and Loss on Attachment</li><li>Social and Emotional Development</li><li>Mental Health Problems in Young and Adults</li><li>Personality and Intellectual Development of Children</li><li>Language Development in Children</li><li>Cognitive Development</li><li>Autism, ADHD and Dyslexia in Young and Adults</li><li>Dealing With Autism, ADHD and Dyslexia in Young and Adults</li><li>Children with Special Needs</li><li>Child Protection</li></ul><p><strong>Course 05: Safeguarding Children Level 3</strong></p><ul><li>Laws and Guidance</li><li>Social and Emotional Development</li><li>Personality and Intellectual Development of Children</li><li>Child Abuse</li><li>Sexual Abuse</li><li>The Impact of Domestic Violence and Abuse on Children</li><li>Risks and Risk Assessment</li><li>Responding to Disclosure and Reporting</li><li>Things to Do after Referral</li><li>Safeguarding Trafficked Children</li><li>Infant Mental Health and Early Attachment</li><li>Assessing Need and Providing Early Help</li></ul><p><strong>Course 06: CPR and Paediatric First Aid Course</strong></p><ul><li>Introduction to Paediatric First Aid</li><li>Assessment and Assistance</li><li>Loss of Responsiveness and CPR</li><li>Paediatric First Aid for Common Illnesses, Injuries and Incidents</li><li>First Aid for Acute Medical Conditions</li><li>Call for an Emergency</li></ul><p><strong>Course 07: Domestic Violence and Abuse Awareness - Level 2</strong></p><ul><li>Introduction to Domestic Violence &amp; Abuse</li><li>The Components of Domestic Violence</li><li>The Impact of Domestic Violence on Victims</li><li>The Impact of Domestic Violence and Abuse on Children</li><li>Assessing the Risks of Domestic Violence and Abuses on Children</li><li>Supporting the Victim and Reporting Incidents</li><li>Record Keeping</li><li>Domestic Violence and Abuse Legislation in the UK</li></ul><p><strong>Course 08: Family Law 2021</strong></p><ul><li>Introduction to Family Law</li><li>Framing Family Law</li><li>Marriage in Family Law</li><li>Civil Partnership and Cohabitation</li><li>Nullity in Marriage</li><li>Divorce and Family Law</li><li>Child Custody</li><li>Property and Finance on Divorce</li><li>Child Support and Family Law</li><li>Adoption Process</li><li>Domestic Violence</li><li>Gender Equality in Family Law</li><li>Feminist Perspectives on Family Law</li></ul><p><strong>Course 09: Family Support Worker Diploma</strong></p><ul><li>Introduction to Family Support Work</li><li>Legislation, Policy and Guidance</li><li>Solving Family Issues</li><li>Safeguarding - Assessing need and providing help</li><li>Building Relationships</li></ul><p><strong>Course 10: Consent in Healthcare</strong></p><p>Covid-19 Awareness for General People and Healthcare</p><ul><li>Introduction to Covid-19</li><li>Understanding of Covid-19 as a Pandemic and How It Is Related to Zoonotic Diseases Like SARS and MERS</li><li>The Strike of Pandemic Around the World and Great Britain</li><li>Effects of Covid-19 on Human Life</li><li>Diagnoses and Treatments</li><li>Preventions and Social Measures to Be Taken</li><li>Artificial Intelligence, Data Science and Technological Solutions against Covid-19</li></ul><p>Consent Training in Healthcare Course</p><ul><li>An Introduction to Consent</li><li>Information Regarding Consent</li><li>Consent Training in Healthcare Course</li><li>Best Interest Decision Making</li><li>Assessing Capacity</li><li>Providing Care or Treatment to People Who Lack Capacity</li><li>Public Bodies and Services Created by MCA Act 2005</li><li>UK Acts in Relation to Consent</li><li>Handling Complaints Regarding Consent</li></ul><p><strong>Course 11: Diabetes Care Diploma</strong></p><ul><li>What is Diabetes</li><li>The Diabetes Challenge</li><li>The Cost of Diabetes</li><li>Types</li><li>Prediabetes</li><li>Gestational Diabetes</li><li>Other Types of Diabetes</li><li>Hypoglycaemia</li><li>Hyperglycaemia and Hyperosmolar Hyperglycaemic State</li><li>Glossary of Diabetes Terms</li></ul><p><strong>Course 12: Nutrition and Diet Awareness</strong></p><ul><li>Overview</li><li>Nutritional Details</li><li>What to Avoid &amp; Problem Areas</li><li>Beyond Food</li><li>Putting It All Together</li><li>Handouts</li></ul><p><strong>Course 13: Addiction and Mental Health - Dual Diagnosis</strong></p><ul><li>Promotional Video</li><li>SAMHI Dual Diagnosis Intro video</li><li>Module 01 - Drugs and Effects</li><li>Module 02 - Addictions &amp; Mental Health</li><li>Module 03 - Harm Minimisation &amp; Optimal Health</li><li>Module 04 - Brain Works - Neurophysiology</li><li>Module 05 - Trauma Model &amp; Keys to Treatment</li><li>Module 06 - Brief &amp; Early Intervention and Tripod of Support</li></ul><p><strong>Course 14: Effective Communication Skills Diploma</strong></p><ul><li>Module 01: Business Communication</li><li>Module 02: Verbal and Non-verbal Communication</li><li>Module 03: Written Communication</li><li>Module 04: Electronic Communication</li><li>Module 05: Communicating with Graphic</li><li>Module 06: Effectively Working for Your Boss</li></ul><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        150 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>Anyone from any background can enrol in thisbundle<strong>. </strong>Persons with similar professions can also refresh or strengthen their skills by enrolling in this course. Students can take this course to gather professional knowledge besides their study or for the future.</p><p>Please note: This course doesn't entitle you to practice as a professional in this specific field. Rather, this course will assist you in understanding the fundamentals so that you can improve your knowledge in the relevant field.</p>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>Our <strong>Social Care </strong>is fully compatible with PC's, Mac's, laptops, tablets and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so that you can access your course on Wi-Fi, 3G or 4G.</p><p>There is no time limit for completing this course; it can be studied in your own time at your own pace.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Having this various expertise will increase the value of your CV and open you up to multiple job sectors.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div> <p>You will get the Hard Copy certificate for the title course (<strong>Level 4 Diploma in Health and Social Care Management</strong>) absolutely Free! Other Hard Copy certificates are available for £10 each. </p><p>Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.</p> </div>

                        </div>

Level 4 Diploma in Health and Social Care Management - CPD Certified

<p>Picture a world of endless possibilities; a realm where knowledge is power, and data reigns supreme. In today's digital age, the ability to decipher complex data sets and extract valuable insights has become an invaluable skill. With the Data Analysis with Data Science &amp; Machine Learning bundle, you're one step closer to harnessing the full potential of data and unlocking a brighter future.</p><p>The age of data is upon us, and the UK is no exception. As businesses and organisations increasingly rely on data to inform strategic decisions, professionals skilled in data analysis and machine learning are in high demand. By acquiring expertise in these fields, you'll not only enhance your career prospects but also contribute to the growth and success of the nation.</p><p>Don't miss out on this opportunity to take your career to the next level. Enrol in the Data Analysis with Data Science &amp; Machine Learning bundle today and unlock the power of data for your business.</p><p><strong>This Data Analysis with Data Science &amp; Machine Learning Bundle Consists of the following Premium courses: </strong></p><ul><li> Course 01: Introduction to Data Analysis</li><li> Course 02: Data Analytics with Tableau</li><li> Course 03: Complete Google Analytics Course</li><li> Course 04: Python for Data Analysis</li><li> Course 05: Quick Data Science Approach from Scratch</li><li> Course 06: R Programming for Data Science</li><li> Course 07: Learn MySQL from Scratch for Data Science and Analytics</li><li> Course 08: Master JavaScript with Data Visualization</li><li> Course 09: Excel Data Analysis</li><li> Course 10: Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li> Course 11: Root Cause Analysis</li><li> Course 12: Google Data Studio: Data Analytics</li><li> Course 13: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query</li><li> Course 14: Business Intelligence and Data Mining Masterclass</li></ul><p>Learning Outcomes:</p><ul><li>Develop a solid understanding of data analysis techniques.</li><li>Learn how to collect, manage, and manipulate data effectively.</li><li>Gain knowledge in the programming languages commonly used in data analysis, such as Python and R.</li><li>Become proficient in data visualisation and presentation.</li><li>Develop an understanding of machine learning algorithms and their application in data analysis.</li><li>Learn how to use various data analysis software, including Tableau and Google Analytics.</li></ul><p>The Data Analysis with Data Science &amp; Machine Learning bundle includes a variety of courses aimed at providing theoretical knowledge in the field of data analysis. The bundle covers a wide range of topics, starting with the basics of data analysis such as data cleaning, exploration, and visualisation. With courses such as Introduction to Data Analysis, Data Analytics with Tableau, Complete Google Analytics Course, Python for Data Analysis, Quick Data Science Approach from Scratch, R Programming for Data Science, Learn MySQL from Scratch for Data Science and Analytics, and Master JavaScript with Data Visualization, learners can get a comprehensive understanding of data analysis concepts.</p><p>The course material is presented in a theoretical format to help learners gain a deep understanding of the topics. Learners can engage with the material at their own pace. The course content is presented in a way that is easy to understand, making it ideal for those who are new to the field of data analysis.</p><p><strong>Course Curriculum: Data Analysis with Data Science &amp; Machine Learning</strong></p><ul><li>Module 01: Introduction</li><li>Module 02: Agenda and Principles of Process Management</li><li>Module 03: The Voice of the Process</li><li>Module 04: Working as One Team for Improvement</li><li>Module 05: Exercise: The Voice of the Customer</li><li>Module 06: Tools for Data Analysis</li><li>Module 07: The Pareto Chart</li><li>Module 08: The Histogram</li><li>Module 09: The Run Chart</li><li>Module 10: Exercise: Presenting Performance Data</li><li>Module 11: Understanding Variation</li><li>Module 12: The Control Chart</li><li>Module 13: Control Chart Example</li><li>Module 14: Control Chart Special Cases</li><li>Module 15: Interpreting the Control Chart</li><li>Module 16: Control Chart Exercise</li><li>Module 17: Strategies to Deal with Variation</li><li>Module 18: Using Data to Drive Improvement</li><li>Module 19: A Structure for Performance Measurement</li><li>Module 20: Data Analysis Exercise</li><li>Module 21: Course Project</li><li>Module 22: Test your Understanding</li></ul><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        140 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <ul><li>Professionals seeking to upskill and enhance their data analysis knowledge and abilities.</li><li>Individuals interested in pursuing a career in data analysis, data science or machine learning.</li><li>Business owners or entrepreneurs looking to gain insights into their data and make data-driven decisions.</li><li>Students or recent graduates seeking to gain valuable experience and knowledge in data analysis.</li><li>Anyone looking to expand their knowledge and understanding of data analysis and its useful applications.</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>This Data Analysis with Data Science &amp; Machine Learning course has been designed to be fully compatible with tablets and smartphones.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Data Analyst: £24k-£42k per annum.</li><li>Business Intelligence Analyst: £25k-£60k per annum.</li><li>Data Scientist: £27k-£65k per annum.</li><li>Machine Learning Engineer: £28k-£80k per annum.</li><li>Business Analyst: £24k-£52k per annum.</li></ul>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            £10
        </p>
            <div> <p>You will get the Hard Copy certificate for the <strong>Data Analysis with Data Science &amp; Machine Learning</strong> course absolutely Free! Other Hard Copy certificates are available for £10 each.</p><p><strong>Please Note:</strong> The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.</p> </div>

                        </div>

Data Analysis with Data Science & Machine Learning

<p><strong>***Limited Time Exclusive Bundle***</strong></p><p><strong>Life Just Got Better This Summer ! Get Hard Copy + PDF Certificates + Transcript + Student ID Card as a Gift - Enrol Now</strong></p><p>Tired of browsing and searching for the course you are looking for? Can't find the complete package that fulfils all your needs? Then don't worry as you have just found the solution. Take a minute and look through this 14-in-1 extensive bundle that has everything you need to succeed in <strong>Medical Law </strong>and other relevant fields!</p><p>After surveying thousands of learners just like you and considering their valuable feedback, this all in one <strong>Medical Law </strong>bundle has been designed by industry experts. We prioritised what learners were looking for in a complete package and developed this in-demand <strong>Medical Law </strong>course that will enhance your skills and prepare you for the competitive job market.</p><p>Also, our <strong>Medical Law </strong>experts are available for answering your queries and help you along your learning journey. Advanced audiovisual learning modules of these courses are broken down into little chunks so that you can learn at your own pace without being overwhelmed by too much material at once.</p><p>Furthermore, to help you showcase your expertise in <strong>Medical Law, </strong> we have prepared a special gift of 1 hardcopy certificate and 1 PDF certificate for the title course completely free of cost. These certificates will enhance your credibility and encourage possible employers to pick you over the rest.</p><p><strong>This Medical Law Bundle Consists of the following Premium courses: </strong></p><ul><li><strong>Course 01: </strong>Medical Law</li><li><strong>Course 02: </strong>Mental Health Laws and Awareness - Level 2</li><li><strong>Course 03: </strong>Public Health</li><li><strong>Course 04: </strong>GDPR in Healthcare</li><li><strong>Course 05: </strong>Consent in Healthcare</li><li><strong>Course 06: </strong>Verification of Death Training for Nurses</li><li><strong>Course 07: </strong>European Medical Device Regulations</li><li><strong>Course 08: </strong>Medication Administration Level 4</li><li><strong>Course 09: </strong>Medical Transcription</li><li><strong>Course 10: </strong>Vaccine Management</li><li><strong>Course 11: </strong>Epidemiology</li><li><strong>Course 12: </strong>Pandemic Disease Awareness</li><li><strong>Course 13: </strong>Coronavirus (COVID-19) Awareness</li><li><strong>Course 14: </strong>Personal Hygiene</li></ul><p><strong>Benefits you'll get choosing Apex Learning for this Medical Law:</strong></p><ul><li>Pay once and get lifetime access to 14 CPD courses</li><li>Certificates, student ID for the title course included in a one-time fee</li><li>Free up your time - don't waste time and money travelling for classes</li><li>Accessible, informative modules designed by expert instructors</li><li>Learn at your ease - anytime, from anywhere</li><li>Study the course from your computer, tablet or mobile device</li><li>CPD accredited course - improve the chance of gaining professional skills</li></ul><p><strong>How will I get my Certificate?</strong></p><p>After successfully completing the course, you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement.</p><ul><li><strong>PDF Certificate: Free (For The Title Course)</strong></li><li><strong>Hard Copy Certificate: Free (For The Title Course)</strong></li></ul><p><strong>Curriculum of the Bundle</strong></p><p><strong>Course 01: Medical Law</strong></p><ul><li>An Introduction to Medical Law</li><li>Legislation on Access to Health, Medical Report, Treatment</li><li>Legislation on Adult Support</li><li>Legislation on Public Health and Health Service (Part 1)</li><li>Legislation on Public Health and Health Service (Part 2)</li><li>Legislation on Public Health and Health Service (Part 3)</li><li>Legislation on Public Health and Health Service (Part 4)</li><li>Legislation on Coronavirus</li><li>Legislation on Mental Health (Part 1)</li><li>Legislation on Mental Health (Part 2)</li><li>Legislation on Abortion</li><li>Other Legislation (Part 1)</li><li>Other Legislation (Part 2)</li></ul><p><strong>Course 02: Mental Health Laws and Awareness - Level 2</strong></p><ul><li>The Mental Capacity Act</li><li>Interface with Legislation, Policy and Procedures</li><li>Deprivation of Liberty Safeguards</li><li>The Mental Capacity Act (2005) and Deprivation of Liberty Safeguards During a Pandemic</li><li>Mental Health Legislation and Services</li><li>Liberty Protection Safeguards (LPS)</li></ul><p><strong>Course 03: Public Health</strong></p><ul><li>Introduction to Public Health</li><li>Principles of Public Health</li><li>Understanding Epidemiology</li><li>Disease Control</li><li>Understanding Measures of Disease Frequency</li><li>Maternity and Childbirth</li><li>Environment and Public Health</li><li>Health System and Policy</li><li>Public Health and Ethics</li></ul><p><strong>Course 04: GDPR in Healthcare</strong></p><ul><li>Introduction to GDPR</li><li>GDPR and Healthcare Setting</li><li>General Data Protection Regulations Explained</li><li>Lawful Basis for Preparation</li><li>Responsibilities and Obligations</li><li>Electronic Medical Records</li><li>Rights and Breaches</li></ul><p><strong>Course 05: Consent in Healthcare</strong></p><ul><li>Introduction to Covid-19</li><li>Understanding of Covid-19 as a Pandemic and How It Is Related to Zoonotic Diseases Like SARS and MERS</li><li>The Strike of Pandemic Around the World and Great Britain</li><li>Effects of Covid-19 on Human Life</li><li>Diagnoses and Treatments</li><li>Preventions and Social Measures to Be Taken</li><li>Artificial Intelligence, Data Science and Technological Solutions against Covid-19</li><li>Consent Training in Healthcare Course</li><li>An Introduction to Consent</li><li>Information Regarding Consent</li><li>Consent Training in Healthcare Course</li><li>Best Interest Decision Making</li><li>Assessing Capacity</li><li>Providing Care or Treatment to People Who Lack Capacity</li><li>Public Bodies and Services Created by MCA Act 2005</li><li>UK Acts in Relation to Consent</li><li>Handling Complaints Regarding Consent</li></ul><p><strong>Course 06: Verification of Death Training for Nurses</strong></p><ul><li>Introduction to Verification of Death</li><li>Legal Considerations</li><li>Expected Death</li><li>Natural Cause of Death</li><li>Verification of Unexpected Death</li><li>Process for Verifying a Death</li><li>Role of Forensic Nurse</li><li>Clinical &amp; Forensic Examination</li><li>Certification &amp; Documentation</li></ul><p><strong>Course 07: European Medical Device Regulations</strong></p><ul><li>Overview to European Regulations on Medical Devices</li><li>Essential Components of EU MDR</li><li>Reporting Requirements and Identification</li><li>Quality System in Medical Device Regulation</li></ul><p><strong>Course 08: Medication Administration Level 4</strong></p><ul><li>Introduction to Safe Handling of Medicines</li><li>Legislation and guidance of medication management</li><li>Principles of Safe and Appropriate Handling of Medicines</li><li>Medication Risk Assessment Guidance</li><li>Handling Medicines in Social Care Settings</li><li>Consent to Treatment</li><li>Requirements for Specific Services</li><li>Levels of Care and Support</li><li>Procedure for Handling Medication</li><li>The Six Rights of Medication Administration</li><li>Covert Administration of Medication</li><li>Recording Procedures</li><li>Storage of Medication</li><li>Transfer and Disposal of Medication</li><li>Drug Formulation and Ways of Taking It</li></ul><p><strong>Course 09: Medical Transcription</strong></p><ul><li>Introduction to Medical Transcription</li><li>The What, How, Who and Why of Medical Transcription</li><li>Understanding Medical Reports</li><li>Medical Language Boot Camp</li><li>Formatting: The Basics</li><li>Data Protection</li></ul><p><strong>Course 10: Vaccine Management</strong></p><ul><li>Introduction to Vaccine and Vaccination</li><li>Types of Vaccine</li><li>Immunology and Immunisation</li><li>Vaccine Safety</li><li>Communication</li><li>Vaccines in Pandemic</li><li>Paediatric Vaccination</li></ul><p><strong>Course 11: Epidemiology</strong></p><ul><li>Understanding Epidemiology</li><li>Principles of Epidemiology</li><li>Study Design</li><li>Disease Occurrence</li><li>Variation in Disease by Time, Place, and Person</li><li>Epidemics and Outbreaks</li><li>Measures of Risk and Disease Prevention</li><li>Measures of Disease Frequency</li><li>Role of Epidemiology in Public Health</li><li>The Epidemiological Concept of Population</li></ul><p><strong>Course 12: Pandemic Disease Awareness</strong></p><ul><li>Introduction to Pandemics</li><li>Pandemics: Risks, Impacts, and Mitigation</li><li>The SARS - MERS Factors</li><li>The Novel Coronavirus (2019-nCoV) 2020 Version of the SARS</li><li>Zoonotic Diseases</li><li>Pandemic Outbreaks from History(HIV/Aids)</li><li>Pandemic Outbreaks from History (Influenza)</li><li>Pandemic Outbreaks from History (Nipah Virus)</li><li>Pandemic Outbreaks from History (Smallpox)</li><li>Pandemic Outbreaks from History (Viral Meningitis)</li><li>Pandemic Outbreaks from History (Ebola Virus)</li><li>Pandemic Outbreaks from History (Zika Virus)</li><li>Pandemic Outbreaks from History (Plague)</li><li>Mild Threats to Human-Being</li><li>Pandemic Risks and Consequences</li><li>Pandemic Mitigation: Preparedness And Response</li></ul><p><strong>Course 13: Coronavirus (COVID-19) Awareness</strong></p><ul><li>Introduction to COVID-19</li><li>Understanding of Covid-19 as a Pandemic and How It Is Related to Zoonotic Diseases Like SARS and MERS</li><li>The Strike of Pandemic Around the World and Great Britain</li><li>Effects of Covid-19 on Human Life</li><li>Diagnosis and Treatment</li><li>Preventions and Social Measures to Be Taken</li><li>Artificial Intelligence, Data Science and Technological Solutions against Covid-19</li></ul><p><strong>Course 14: Personal Hygiene</strong></p><ul><li>Introduction to Personal Hygiene and a Brief History</li><li>Looking Clean, Smelling Clean</li><li>Improving and Maintaining Oral Health</li><li>Care of the Eyes</li><li>Ear Care Secrets</li><li>Foot &amp; Nail Care in Personal Hygiene</li><li>Hair Care Hygienic Ways</li><li>Hygienic Approach to Skin Care</li><li>Maintain Good Toilet Hygiene</li><li>Potential Hygiene Guidelines</li><li>Personal Hygiene During Coronavirus Pandemic</li></ul><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        140 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>Anyone from any background can enrol in this <strong>Medical Law </strong>bundle<strong>. </strong>Persons with similar professions can also refresh or strengthen their skills by enrolling in this course. Students can take this course to gather professional knowledge besides their study or for the future.</p>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>Our <strong>Medical Law </strong>is fully compatible with PC's, Mac's, laptops, tablets and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so that you can access your course on Wi-Fi, 3G or 4G.</p><p>There is no time limit for completing this course; it can be studied in your own time at your own pace.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Having this various expertise will increase the value of your CV and open you up to multiple job sectors.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            Included
        </p>

                        </div>

Medical Teaching : Medical Law

<p><strong>***Don't Spend More; Spend Smart***</strong></p><p><strong>Life Just Got Better This Summer! Get Hard Copy + PDF Certificates + Transcript + Student ID Card + e-Learning App as a Gift - Enrol Now</strong></p><p>Tired of browsing and searching for the course you are looking for? Can't find the complete package that fulfils all your needs? Then don't worry as you have just found the solution. Take a minute and look through this 14-in-1 extensive bundle that has everything you need to succeed in <strong>Neuroscience </strong>and other relevant fields!</p><p>After surveying thousands of learners just like you and considering their valuable feedback, this all-in<strong>-</strong>one <strong>Neuroscience </strong>bundle has been designed by industry experts. We prioritised what learners were looking for in a complete package and developed this in-demand <strong>Neuroscience </strong>course that will enhance your skills and prepare you for the competitive job market.</p><p>Also, our <strong>Neuroscience </strong>experts are available for answering your queries and help you along your learning journey. Advanced audio-visual learning modules of these courses are broken down into little chunks so that you can learn at your own pace without being overwhelmed by too much material at once.</p><p>Furthermore, to help you showcase your expertise in <strong>Neuroscience, </strong> we have prepared a special gift of 1 hardcopy certificate and 1 PDF certificate for the title course completely free of cost. These certificates will enhance your credibility and encourage possible employers to pick you over the rest.</p><p><strong>This Neuroscience Bundle Consists of the following Premium courses: </strong></p><ul><li><strong>Course 01: </strong>Neurology</li><li><strong>Course 02: </strong>Neuropsychology and Development of Children</li><li><strong>Course 03: </strong>Concussion and Brain Injury Awareness</li><li><strong>Course 04: </strong>Cerebral Palsy Awareness</li><li><strong>Course 05: </strong>Understanding Autism Awareness and Diagnosis Level 2</li><li><strong>Course 06: </strong>Dyslexia Awareness Course</li><li><strong>Course 07: </strong>Level 3 Mental Health and Adolescent Course</li><li><strong>Course 08: </strong>Level 3 Mental Health Awareness Course</li><li><strong>Course 09: </strong>Human Anatomy and Physiology</li><li><strong>Course 10: </strong>Nutrition and Diet Awareness</li><li><strong>Course 11: </strong>Medication Administration Level 4</li><li><strong>Course 12: </strong>GDPR in Healthcare</li><li><strong>Course 13: </strong>Medical Law</li><li><strong>Course 14: </strong>Level 3 - Coronavirus (COVID -19) Awareness Course</li></ul><p><strong>Benefits you'll get choosing Apex Learning for this Neuroscience:</strong></p><ul><li>Pay once and get lifetime access to 14 CPD courses</li><li>Free e-Learning App for engaging reading materials &amp; helpful assistance</li><li>Certificates, student ID for the title course included in a one-time fee</li><li>Free up your time - don't waste time and money travelling for classes</li><li>Accessible, informative modules designed by expert instructors</li><li>Learn at your ease - anytime, from anywhere</li><li>Study the course from your computer, tablet or mobile device</li><li>CPD accredited course - improve the chance of gaining professional skills</li></ul><p><strong>How will I get my Certificate?</strong></p><p>After successfully completing the course you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement.</p><ul><li><strong>PDF Certificate: Free (For The Title Course)</strong></li><li><strong>Hard Copy Certificate: Free (For The Title Course)</strong></li></ul><p>Curriculum of <strong>Neuroscience Bundle </strong></p><p><strong>Course 01: Neurology</strong></p><ul><li>Introduction to Neurology</li><li>Neurological Disorders</li><li>Visual Disorders</li><li>Disorders Of Hearing</li><li>Spinal Cord Disorders</li><li>Peripheral Nervous System Disorders</li><li>Child Neurology</li><li>Neurological Assessments</li><li>Medications</li></ul><p><strong>Course 02: Neuropsychology and Development of Children</strong></p><ul><li>The Theory of Psycho-social Development</li><li>Serve &amp; Return</li><li>Practical Tips For Serve &amp; Return</li><li>Fuzzy Trace Theory - Explains and Predicts Adolescent Risk Taking</li><li>Adolescent Risk Taking and the Prefrontal Cortex</li><li>Operant Conditioning - How Reinforcement Works and How it can help you</li><li>The Danger of Unearned Rewards (Habituation and Expectations)</li><li>Influencing behavior through linguistic cuing</li><li>Does violent media lead to aggressive kids?</li><li>Parenting Styles</li><li>Culture and seeing world</li><li>How childhood experience (i.e. violence) can result in choosing abusive partners</li><li>A Highly Regimented Life is a Very Stressful Life</li><li>Heritable vs. Inherited</li><li>Hormones and Development</li></ul><p><strong>Course 03: Concussion and Brain Injury Awareness</strong></p><ul><li>Introduction To Brain Injury</li><li>Concussion Awareness</li><li>Acquired Brain Injury</li><li>Sports-related Concussion And Brain Injury</li><li>Rehabilitation</li><li>Prevention</li></ul><p><strong>Course 04: Cerebral Palsy Awareness</strong></p><ul><li>Understanding Cerebral Palsy</li><li>Causes and Symptoms of Cerebral Palsy</li><li>Epidemiology of Cerebral Palsy</li><li>Diagnosis of Cerebral Palsy</li><li>Principles of Treatment</li><li>Principles of Rehabilitation: Occupational and Physical Therapy</li><li>Care Planning</li><li>Typical Child vs Child with Cerebral Palsy</li><li>Child, Family and Therapist Working as a Team</li></ul><p><strong>Course 05: Understanding Autism Awareness and Diagnosis Level 2</strong></p><ul><li>Autism Spectrum Disorder (ASD)</li><li>Learning Difficulties Related to Autism</li><li>Autism Diagnosis</li><li>Cognitive Approaches in Autism</li><li>Dealing with Autistic Individuals</li><li>Other Considerations for Dealing with Autistic Individuals</li><li>Engagement in Autism Awareness</li></ul><p><strong>Course 06: Dyslexia Awareness Course</strong></p><ul><li>Introduction to Dyslexia</li><li>Dyslexia and Learning Difficulties</li><li>Dyslexia in the School</li><li>Cognitive Approaches in Dyslexia</li><li>The Legal Rights of Dyslexics</li></ul><p><strong>Course 07: Level 3 Mental Health and Adolescent Course</strong></p><ul><li>Introduction to Mental Health</li><li>Child Psychology</li><li>Attachment and Relationship Building in Childhood</li><li>Impacts of Separation and Loss on Attachment</li><li>Factors that Influence Development</li><li>Mental Health Problems in Young and Adults</li><li>Other Mental Health Problems in Young and Adults</li><li>Autism, ADHD and Dyslexia in Young and Adults</li><li>Dealing With Autism, ADHD and Dyslexia in Young and Adults</li><li>The Self Harming Behaviour</li><li>Mental Health Treatment and Medicine</li><li>Mental Health over Life Span and Society in the UK</li><li>Mental Health Related Legislations in the UK</li></ul><p><strong>Course 08: Level 3 Mental Health Awareness Course</strong></p><ul><li>Introduction to Mental Health</li><li>Childhood And Adolescent Psychiatric Disorders</li><li>Stress and Anxiety Disorders</li><li>Schizophrenia</li><li>Personality Disorders</li><li>Mood Disorders</li><li>Eating and Sleeping Disorders</li><li>Self-Harm and Suicide</li><li>Medication and Therapy in the Treatment of Mental Illness</li><li>Social Attitudes To Mental Illness</li><li>Mental Health Legislation and Services</li><li>Mental Health In The Workplace</li></ul><p><strong>Course 09: Human Anatomy and Physiology</strong></p><ul><li>Human Body Vocabulary with Pictures</li><li>Equipment, Instruments and Lab Tests</li><li>Acronyms and Abbreviation</li><li>Digestive System</li><li>Cardiovascular System</li><li>Blood and Immunity System</li><li>Respiratory System</li><li>Musculoskeletal System</li><li>Central Nervous System</li></ul><p><strong>Course 10: Nutrition and Diet Awareness</strong></p><ul><li>Nutrition and Diet Awareness</li><li>Overview</li><li>Nutritional Details</li><li>What to Avoid &amp; Problem Areas</li><li>Beyond Food</li><li>Putting It All Together</li></ul><p><strong>Course 11: Medication Administration Level 4</strong></p><ul><li>Introduction to Safe Handling of Medicines</li><li>Legislation and guidance of medication management</li><li>Principles of Safe and Appropriate Handling of Medicines</li><li>Medication Risk Assessment Guidance</li><li>Handling Medicines in Social Care Settings</li><li>Consent to Treatment</li><li>Requirements for Specific Services</li><li>Levels of Care and Support</li><li>Procedure for Handling Medication</li><li>The Six Rights of Medication Administration</li><li>Covert Administration of Medication</li><li>Recording Procedures</li><li>Storage of Medication</li><li>Transfer and Disposal of Medication</li><li>Drug Formulation and Ways of Taking It</li></ul><p><strong>Course 12: GDPR in Healthcare</strong></p><ul><li>Introduction to GDPR</li><li>GDPR and Healthcare Setting</li><li>General Data Protection Regulations Explained</li><li>Lawful Basis for Preparation</li><li>Responsibilities and Obligations</li><li>Electronic Medical Records</li><li>Rights and Breaches</li></ul><p><strong>Course 13: Medical Law</strong></p><ul><li>An Introduction to Medical Law</li><li>Legislation on Access to Health, Medical Report, Treatment</li><li>Legislation on Adult Support</li><li>Legislation on Public Health and Health Service (Part 1)</li><li>Legislation on Public Health and Health Service (Part 2)</li><li>Legislation on Public Health and Health Service (Part 3)</li><li>Legislation on Public Health and Health Service (Part 4)</li><li>Legislation on Coronavirus</li><li>Legislation on Mental Health (Part 1)</li><li>Legislation on Mental Health (Part 2)</li><li>Legislation on Abortion</li><li>Other Legislation (Part 1)</li><li>Other Legislation (Part 2)</li></ul><p><strong>Course 14: Level 3 - Coronavirus (COVID -19) Awareness Course</strong></p><ul><li>Introduction to COVID-19</li><li>Understanding of Covid-19 as a Pandemic and How It Is Related to Zoonotic Diseases Like SARS and MERS</li><li>The Strike of Pandemic Around the World and Great Britain</li><li>Effects of Covid-19 on Human Life</li><li>Diagnosis and Treatment</li><li>Preventions and Social Measures to Be Taken</li><li>Artificial Intelligence, Data Science and Technological Solutions against Covid-19</li></ul><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        140 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>Anyone from any background can enrol in this <strong>Neuroscience </strong>bundle<strong>. </strong>Persons with similar professions can also refresh or strengthen their skills by enrolling in this course. Students can take this course to gather professional knowledge besides their study or for the future.</p>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>Our <strong>Neuroscience </strong>is fully compatible with PC's, Mac's, laptops, tablets and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so that you can access your course on Wi-Fi, 3G or 4G.</p><p>There is no time limit for completing this course; it can be studied in your own time at your own pace.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Having this various expertise will increase the value of your CV and open you up to multiple job sectors.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            Included
        </p>
            <div> <p>You will get the PDF Certificate for the title course (<strong>Neurology</strong>) absolutely Free!</p> </div>
        <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div> <p>You will get the Hard Copy certificate for the title course (<strong>Neurology</strong>) absolutely Free! Other Hard Copy certificates are available for £10 each. </p><p>Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.</p> </div>

                        </div>

Neuroscience Courses

<p dir="ltr" id="isPasted" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Python for Data Science and Machine Learning Bootcamp course is a comprehensive and practical online course designed to teach you how to use Python for data science and machine learning.&nbsp;</span></p><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">The course comprises several sections, each covering different topics in data science and machine learning. It includes all the essential concepts and tools required to analyse and manipulate data, build machine learning models, and make predictions or decisions.</span></p><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">It also covers dataset summary statistics and visualisation techniques using libraries like matplotlib and seaborn. You&#39;ll learn about model selection, ensemble approaches, and parameter adjustment. Additionally, you will discover how to export and load machine learning models using libraries such as pickle and joblib.</span></p><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">This course is suitable for anyone interested in learning Python for data science and machine learning. Whether you are an aspiring data scientist or a professional looking to enhance your data analysis skills, this course will help you achieve your goals.</span></p><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Enrol now to gain instant access to the course materials and start your learning journey. Don&#39;t miss out on the opportunity to acquire one of the most in-demand skills in the market today and become a proficient data scientist and machine learning expert.</span></p><h2 dir="ltr" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Learning Outcome of Python for Data Science and Machine Learning Bootcamp &nbsp; &nbsp;</span></h2><ul fr-original-style="" style="box-sizing: border-box;"><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Master fundamental concepts of machine learning and its applications.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Gain proficiency in Python programming for data analysis and manipulation.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Learn to load, read, and manipulate CSV data files using Python libraries.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Understand dataset summary statistics and visualization techniques.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Acquire skills in data preparation and preprocessing.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Explore feature selection techniques and their importance.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Evaluate machine learning algorithms using various techniques and metrics.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Spot check classification and regression algorithms for model selection.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Improve model performance using ensemble methods and parameter tuning.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Learn to export, save, load, and finalize machine learning models for real-time predictions.</li></ul><h2 dir="ltr" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Key Features of the Course</span></h2><ul fr-original-style="" style="box-sizing: border-box;"><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">A CPD certificate that is recognised worldwide.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">A great online learning experience.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Interesting and unique online materials and activities.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Expert guidance and support from the field leaders.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Access to the study resources anytime you want.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Friendly and helpful customer service and admin support by email, phone, and chat from Monday through Friday.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Get a year-long access to the course.</li></ul><h2 dir="ltr" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Who is this course for</span></h2><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); font-size: 16px; box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0); font-size: 16px;">This Python for Data Science and Machine Learning Bootcamp Course is suitable for -</span></p><ul fr-original-style="" style="box-sizing: border-box;"><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Aspiring data scientists and machine learning enthusiasts</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Professionals seeking to enhance their data analysis skills</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Individuals interested in Python programming for data science</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Anyone looking to break into the field of data science and machine learning</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Students pursuing studies in computer science or related fields</li></ul><h2 dir="ltr" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Requirements</span></h2><ul fr-original-style="" style="box-sizing: border-box;"><li id="isPasted" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Basic understanding of programming concepts</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Familiarity with Python programming language is beneficial but not mandatory</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">No prerequisites; suitable for individuals from any academic background.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Accessible course materials from any internet-enabled device.</li></ul><h2 dir="ltr" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">CPD Certificate from Course Gate</span></h2><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">At the successful completion of the course, you can obtain your CPD certificate from us. You can order the PDF certificate for &pound;9 and the hard copy for &pound;15. Also, you can order both PDF and hardcopy certificates for &pound;22.</span></p><h2 dir="ltr" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Career path</span><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0);"><br fr-original-style="" style="box-sizing: border-box;"></span></h2><div style="color: rgb(68, 68, 68); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(68, 68, 68);"><div style="color: rgb(68, 68, 68); box-sizing: border-box;" fr-original-style=" color: rgb(68, 68, 68);"><div data-elementor-type="wp-post" data-elementor-id="357815" data-elementor-post-type="course" fr-original-style="" style="box-sizing: border-box;"><section data-id="5767f71a" data-element_type="section" fr-original-style="" style="box-sizing: border-box;"><div data-id="58784751" data-element_type="column" fr-original-style="" style="box-sizing: border-box;"><div data-id="ce105db" data-element_type="widget" data-widget_type="text-editor.default" style="color: var( --e-global-color-text ); box-sizing: border-box;" fr-original-style=" color: var( --e-global-color-text );"><ul fr-original-style="" style="box-sizing: border-box;"><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Data Scientist</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Data Analyst</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Machine Learning Engineer</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Business Intelligence Analyst</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Data Engineer</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Research Scientist</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Quantitative Analyst</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Artificial Intelligence Specialist</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Data Consultant</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Statistician</li></ul></div></div></section></div></div></div>

Course Gate

Machine Learning (ML)

Python for Data Science and Machine Learning Bootcamp online course is suitable for anyone interested in learning Python for data science and machine learning. It is especially ideal for aspiring data scientists and professionals seeking to enhance their data analysis skills. 

Python for Data Science and Machine Learning Bootcamp

<h2 style="color: var(--text-heading); box-sizing: border-box;" id="isPasted" fr-original-style="color: var(--text-heading);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><span style="font-size: 24px; box-sizing: border-box;" fr-original-style="font-size: 24px;">This course at a glance</span></strong></h2><ul style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0);"><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0);">Accredited by CPDQE</li><li id="isPasted" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Learn how to become a data scientist, data engineer, data analyst or consultant</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Know the different processes of Data Science, such as data cleaning, processing, wrangling, manipulation</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Discover the usage of R to clean, analyse, and visualise data</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">How to write complex R programs for real-life industry situations</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Get data scientist resume tips and land your first job</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Explore the various applications of Machine Learning</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Understand Tidyverse, Operators, Vectors, Lists and their applications</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Uncover data extraction and scraping</span></li></ul><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(38, 99, 82) !important;">Data science and Machine Learning are one of the most popular fields in the world today. Data science is crucial to analysing and developing data-based machine learning models. We will cover programming in R in this course for data science and machine learning.</p><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">R programming is a specialised skill that is in high demand today. We&rsquo;ve designed our&nbsp;<b fr-original-style="" style="box-sizing: border-box;">Data Science and Machine Learning with R</b>&nbsp;course to help you learn fundamentals through advanced R programming. This course teaches you how to effectively use R programming for machine learning or data science. You&rsquo;ll learn how to visualise data by plotting in R, as well as how to clean data.&nbsp;</p><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">You will receive training in machine learning and its many real-world applications while working with R Shiny to create web applications and online interactive dashboards. In other words, you will gain practical, step-by-step knowledge of the R programming language that you may use for business or professional purposes.</p><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">An expert instructor designed this&nbsp;<b fr-original-style="" style="box-sizing: border-box;">&ldquo;Data Science and Machine Learning with R&rdquo;</b>&nbsp;course to provide you with the best learning experience possible. Our goal is for you to learn and apply the lessons from this course to improve your skills.&nbsp;</p><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">To explore the world of R Programming Language, Enrol Now!</p><h3 style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);"><span style="font-size: 24px; box-sizing: border-box;" fr-original-style="font-size: 24px;">Accredited by</span></h3><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);">This course is <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">CPDQE&nbsp;</strong>accredited, which serves as an impactful mechanism for skill enhancement.&nbsp;</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Continuing Professional Development (CPD) stands as a crucial, widely acknowledged method that aids individuals, organisations, and entire industries in staying current with their skills and knowledge.</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">CPD not only facilitates the elevation of global standards and benchmarks, aligning with the growing forces of globalisation and consumer expectations but also transforms learning into a deliberate and proactive process. It motivates professionals to uphold a consistently high level of performance and demonstrates their unwavering commitment to a specific job role or profession.</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><span style="font-size: 24px; box-sizing: border-box;" fr-original-style="font-size: 24px;">Course Curriculum</span></strong></p><ul fr-original-style="" style="box-sizing: border-box;"><li id="isPasted" fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Introduction to Data Science +ML with R from A-Z</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Getting Started with R</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Types and Structures in R</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Intermediate R</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Manipulation in R</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Visualization in R</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Creating Reports with R Markdown</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Building Webapps with R Shiny</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Introduction to Machine Learning</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Preprocessing</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Linear Regression: A Simple Model</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Exploratory Data Analysis</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Linear Regression: A Real Model</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Logistic Regression</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Starting a Career in Data Science</strong></li></ul>

LearnDrive UK

The course covers data science and machine learning with R.



Data Science and Machine Learning with R

<strong>This course starts with the basics of data science and gradually moves towards explaining the concepts of machine learning and various data science algorithms.</strong>
        <p>Machine learning is the key to development in many areas, such as IT, security, marketing, automation, and even medicine. Without machine learning, it is impossible to build intelligent applications and devices, such as Alexa, Siri, and Google Assistant. This course will help to get familiar with data science and machine learning.

The course starts with an introduction to data science, explaining different terms associated with it. You will also become familiar with machine learning and data science modeling and explore the key differences between model parameters and hyperparameters. Next, you will become familiar with the concepts of machine learning models, such as linear regression, decision trees, random forests, neural networks, and clustering techniques. Towards the end, you will learn how to evaluate machine learning models and learn the best practices to succeed in your data scientist role.

By the end of this course, you will have a solid understanding of data science and machine learning fundamentals.</p>
        <h2>What You Will Learn</h2><p>Become familiar with data science and machine learning terms<br>Distinguish between model parameters and hyperparameters<br>Distinguish between supervised and unsupervised learning<br>Discover how decision trees, bagging, and random forest works<br>Understand the importance of the k-nearest neighbors (KNN) algorithm in machine learning<br>Learn about neural networks and clustering techniques<br>Evaluate the performance of machine learning models</p>
        <h2>Audience</h2><p>This course is designed for students and beginners who want to understand the concepts, statistics, and math behind machine learning algorithms and for those who are curious to solve real-world problems using machine learning and data science. Everything is taught from scratch; hence, there are no prerequisites to get started with this course.</p>
        <h2>Approach</h2><p>With the help of simple explanation, avoiding confusing mathematical notation and jargon, this course covers the fundamentals of data science, machine learning, and data mining from scratch.</p>
        <h2>Key Features</h2><p>Learn the fundamentals of data science, machine learning, and data mining * Learn interesting techniques to evaluate a machine learning model * Discover the best practices to solve real-world problems using machine learning</p>
        
        <h2>About the Author</h2><h3>AI Sciences</h3><p>AI Sciences are experts, PhDs, and artificial intelligence practitioners, including computer science, machine learning, and Statistics. Some work in big companies such as Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM.

AI sciences produce a series of courses dedicated to beginners and newcomers on techniques and methods of machine learning, statistics, artificial intelligence, and data science. They aim to help those who wish to understand techniques more easily and start with less theory and less extended reading. Today, they publish more comprehensive courses on specific topics for wider audiences.

Their courses have successfully helped more than 100,000 students master AI and data science.</p>
        <h2>Course Outline</h2><h4>1. Welcome and Introduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Welcome</p><p style='margin: 0'>This video welcomes you to the course.</p></td></tr><tr><td style='padding: 15px;'><p>2. Introduction to Data Science</p><p style='margin: 0'>This video provides an introduction to data science.</p></td></tr></tbody></table><br><h4>2. Preliminary Requirements to Understand Data Science and Machine Learning</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Understanding Data Science Terms</p><p style='margin: 0'>This video provides an overview of the terms used in data science.</p></td></tr><tr><td style='padding: 15px;'><p>2. Understanding Machine Learning</p><p style='margin: 0'>This video presents an overview of machine learning.</p></td></tr><tr><td style='padding: 15px;'><p>3. Types of Learning</p><p style='margin: 0'>This video explains the different types of learning.</p></td></tr><tr><td style='padding: 15px;'><p>4. Understanding Data Science Modeling</p><p style='margin: 0'>This video focuses on data science modeling.</p></td></tr><tr><td style='padding: 15px;'><p>5. Model parameters versus Hyperparameters</p><p style='margin: 0'>This video explains the difference between model parameters and hyperparameters.</p></td></tr></tbody></table><br><h4>3. Machine Learning Models</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. How Linear Regression Works</p><p style='margin: 0'>This video demonstrates how linear regression works.</p></td></tr><tr><td style='padding: 15px;'><p>2. How Decision Trees Work</p><p style='margin: 0'>This video demonstrates how decision trees work.</p></td></tr><tr><td style='padding: 15px;'><p>3. How Bagging and Random Forest Work</p><p style='margin: 0'>This video demonstrates the working of bagging and random forest.</p></td></tr><tr><td style='padding: 15px;'><p>4. How Support Vector Machine Works</p><p style='margin: 0'>This video demonstrates the working of support vector machines.</p></td></tr><tr><td style='padding: 15px;'><p>5. Neural Networks- Part 1</p><p style='margin: 0'>This video is the first part of a two-part video that explains neural networks.</p></td></tr><tr><td style='padding: 15px;'><p>6. Neural Networks- Part 2</p><p style='margin: 0'>This is the second part of the two-part video that explains neural networks.</p></td></tr><tr><td style='padding: 15px;'><p>7. How Logistic Regression Works</p><p style='margin: 0'>This video demonstrates the working of logistic regression.</p></td></tr><tr><td style='padding: 15px;'><p>8. How k-nearest neighbour (KNN) Works</p><p style='margin: 0'>This video focuses on KNN and explains how it works.</p></td></tr><tr><td style='padding: 15px;'><p>9. Clustering Techniques</p><p style='margin: 0'>This video explains the different clustering techniques.</p></td></tr></tbody></table><br><h4>4. Model Performance</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Evaluating Models Performance</p><p style='margin: 0'>This video demonstrates how to evaluate the performance of the models.</p></td></tr></tbody></table><br><h4>5. Best Practices for a Data Scientist</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Best Practices for a Data Scientist</p><p style='margin: 0'>This video explains the best practices used by data scientists.</p></td></tr></tbody></table>

Algorithms

This course starts with the basics of data science and gradually moves towards explaining the concepts of machine learning and various data science algorithms.

Mastering Data Science and Machine Learning Fundamentals

<p>Feeling Stuck in Your Career? The Python for Data Science and Machine Learning-(30 in 1) CPD Accredited Courses! Bundle is Your Skill-Building Solution. This exceptional collection of <strong>30 premium courses</strong> is designed to encourage growth and improve your career opportunities. Suited to meet different interests and goals, the  Python for Data Science and Machine Learning bundle provides an engaging learning experience, helping you learn skills across various disciplines.</p><p>With Python for Data Science and Machine Learning-(30 in 1) CPD Accredited Courses! Bundle, you'll have a personalised journey that aligns with your career goals and interests. This comprehensive package helps you confidently tackle new challenges, whether entering a new field or enhancing your existing knowledge. The  Python for Data Science and Machine Learning bundle is your gateway to expanding your career options, increasing job demand, and enhancing your skill set.</p><p>By enrolling in this bundle, you'll receive complimentary PDF certificates for all courses, adding value to your resume at no extra cost. Develop key skills and achieve important progress in your career and personal development. Start your journey today and experience the transformative impact of the Python for Data Science and Machine Learning-(30 in 1) CPD Accredited Courses! bundle on your job life and career growth!</p><p><strong>This Python for Data Science and Machine Learning-(30 in 1) CPD Accredited Courses! Bundle Comprises the Following CPD Accredited Courses:</strong></p><ul><li><strong>Course 01</strong>: Machine Learning Basics</li><li><strong>Course 02</strong>: Azure Machine Learning</li><li><strong>Course 03</strong>: Python Intermediate Training</li><li><strong>Course 04</strong>: Python Data Science</li><li><strong>Course 05</strong>: 2021 Data Science &amp; Machine Learning with R from A-Z</li><li><strong>Course 06</strong>: Complete Python Machine Learning &amp; Data Science Fundamentals</li><li><strong>Course 07</strong>: Learn Python, JavaScript, and Microsoft SQL for Data science</li><li><strong>Course 08</strong>: Spatial Data Visualisation and Machine Learning in Python</li><li><strong>Course 09</strong>: Complete Python Machine Learning &amp; Data Science Fundamentals</li><li><strong>Course 10</strong>: Python Programming Bible | Networking, GUI, Email, XML, CGI</li><li><strong>Course 11</strong>: Deep Learning &amp; Neural Networks Python - Keras</li><li><strong>Course 12</strong>: The Complete Python 3 Course: Beginner to Advanced!</li><li><strong>Course 13</strong>: Building Big Data Pipelines with PySpark MongoDB and Bokeh</li><li><strong>Course 14</strong>: Clinical Data Management with SAS Programming</li><li><strong>Course 15</strong>: Certificate in Data Entry and Management</li><li><strong>Course 16</strong>: Quick Data Science Approach from Scratch</li><li><strong>Course 17</strong>: SQL for Data Science, Data Analytics and Data Visualization</li><li><strong>Course 18</strong>: Programming AutoCAD with SQL Server Database Using C#</li><li><strong>Course 19</strong>: Big Data Analytics with PySpark Power BI and MongoDB</li><li><strong>Course 20</strong>: Develop Big Data Pipelines with R &amp; Sparklyr &amp; Tableau</li><li><strong>Course 21</strong>: Develop Big Data Pipelines with R, Sparklyr &amp; Power BI</li><li><strong>Course 22</strong>: Data Center Training Essentials: Power &amp; Electrical</li><li><strong>Course 23</strong>: Business Intelligence and Data Mining</li><li><strong>Course 24</strong>: Data Analysis In Excel</li><li><strong>Course 25</strong>: CV Writing and Job Searching</li><li><strong>Course 26</strong>: Learn to Level Up Your Leadership</li><li><strong>Course 27</strong>: Networking Skills for Personal Success</li><li><strong>Course 28</strong>: Ace Your Presentations: Public Speaking Masterclass</li><li><strong>Course 29</strong>: Learn to Make a Fresh Start in Your Life</li><li><strong>Course 30</strong>: Motivation - Motivating Yourself &amp; Others</li></ul><p><strong>What will make you stand out?</strong></p><p>Upon completion of this online Python for Data Science and Machine Learning-(30 in 1) CPD Accredited Courses! Bundle, you will gain the following:</p><ul><li>CPD QS Accredited Proficiency with this  Python for Data Science and Machine Learning  Bundle </li><li>After successfully completing the  Python for Data Science and Machine Learning bundle, you will receive a FREE PDF Certificate from REED as evidence of your newly acquired abilities.</li><li>Lifetime access to the whole collection of learning materials of this  Python for Data Science and Machine Learning       Bundle</li><li>The online test with immediate results </li><li>You can study and complete the  Python for Data Science and Machine Learning bundle at your own pace.</li><li>Study for the  Python for Data Science and Machine Learning bundle using any internet-connected device, such as a computer, tablet, or mobile device.</li></ul><p>The  Python for Data Science and Machine Learning-(30 in 1) CPD Accredited Courses! bundle is a premier learning resource, with each course module holding respected CPD accreditation, symbolising exceptional quality. The content is packed with knowledge and is regularly updated to ensure it remains relevant. This bundle offers not just education but a constantly improving learning experience designed to enrich both your personal and professional development.</p><p>Advance the future of learning with the   Python for Data Science and Machine Learning bundle, a comprehensive, complete collection of 30 courses. Each course in the  Python for Data Science and Machine Learning bundle has been handpicked by our experts to provide a broad range of learning opportunities. Together, these modules form an important and well-rounded learning experience.</p><p>Our mission is to deliver high-quality, accessible education for everyone. Whether you are starting your career, switching industries, or enhancing your professional skills, the   Python for Data Science and Machine Learning bundle offers the flexibility and convenience to learn at your own pace. Make the   Python for Data Science and Machine Learning package your trusted partner in your lifelong learning journey.</p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        300 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>The Python for Data Science and Machine Learning-(30 in 1) CPD Accredited Courses! is perfect for:</p><ul><li>Expand your knowledge and skillset for a fulfilling career with the  Python for Data Science and Machine Learning bundle.</li><li>Become a more valuable professional by earning CPD certification and mastering in-demand skills with the  Python for Data Science and Machine Learning bundle.</li><li>Discover your passion or explore new career options with the diverse learning opportunities in the  Python for Data Science and Machine Learning bundle.</li><li>Learn on your schedule, in the comfort of your home - the  Python for Data Science and Machine Learning bundle offers ultimate flexibility for busy individuals.</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You are warmly invited to register for this bundle. Please be aware that no formal entry requirements or qualifications are necessary. This curriculum has been crafted to be open to everyone, regardless of previous experience or educational attainment.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Gain a wide range of skills across various fields, improve your problem-solving capabilities, and keep current with industry trends. Perfect for those aiming for career advancement, exploring a new professional direction, or pursuing personal growth. Begin your journey with the  Python for Data Science and Machine Learning bundle.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Certificates</h4>
        <p>
            Digital certificate -
            Included
        </p>

                        </div>

Compliance Central

Python for Data Science and Machine Learning-(30 in 1) CPD Accredited Courses!

<h2 style="color: var(--text-heading); box-sizing: border-box;" id="isPasted" fr-original-style="color: var(--text-heading);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><span style="font-size: 24px; box-sizing: border-box;" fr-original-style="font-size: 24px;">This course at a glance</span></strong></h2><ul style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0);"><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0);">Accredited by CPDQE</li><li id="isPasted" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Learn how to clean, process, wrangle, and manipulate data</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Know how to create a resume for a data science job</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Get a grasp of NumPy by learning how to use it for numerical data</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Uncover the secret of different Python libraries, such as Pandas, Matplotlib, SciPy and many more</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Explore machine learning concepts and algorithms</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Discover developing custom data solutions</span></li></ul><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(38, 99, 82) !important;">You can create various applications for science, math, machine learning, and data science with Python. As a high-level, general-purpose programming language, Python is quite English-like and easy to learn. This&nbsp;<b fr-original-style="" style="box-sizing: border-box;">Python for Data Science and Machine Learning</b>&nbsp;course will show you how to use Python for machine learning and data science.</p><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">During the course, you will master every useful Python skill you need for data science and machine learning. If you find it challenging to write complex Python programs, we&rsquo;ll show you how to do so with our step-by-step instructions based on actual work contexts. You&rsquo;ll also learn how to run the regression, classification, and clustering and the specifics of supervised and unsupervised machine learning. Moreover, this course covers how statistics work for data science, hypothesis testing, and much more.</p><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">An expert instructor designed this&nbsp;<b fr-original-style="" style="box-sizing: border-box;">&ldquo;Python for Data Science and Machine Learning&rdquo;</b>&nbsp;course to provide you with the best learning experience possible. Our goal is for you to learn and apply the lessons from this course to improve your skills.&nbsp;</p><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">To become a master of Python, Enrol Now!</p><h3 style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);"><span style="font-size: 24px; box-sizing: border-box;" fr-original-style="font-size: 24px;">Accredited by</span></h3><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);">This course is <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">CPDQE&nbsp;</strong>accredited, which serves as an impactful mechanism for skill enhancement.&nbsp;</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Continuing Professional Development (CPD) stands as a crucial, widely acknowledged method that aids individuals, organisations, and entire industries in staying current with their skills and knowledge.</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">CPD not only facilitates the elevation of global standards and benchmarks, aligning with the growing forces of globalisation and consumer expectations but also transforms learning into a deliberate and proactive process. It motivates professionals to uphold a consistently high level of performance and demonstrates their unwavering commitment to a specific job role or profession.</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);"><br fr-original-style="" style="box-sizing: border-box;"></p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><span style="font-size: 24px; box-sizing: border-box;" fr-original-style="font-size: 24px;">Course Curriculum</span></strong></p><ul fr-original-style="" style="box-sizing: border-box;"><li id="isPasted" fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Introduction to Python for Data Science &amp; Machine Learning from A-Z</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Science &amp; Machine Learning Concepts</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python For Data Science</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Statistics for Data Science</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Probability and Hypothesis Testing</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">NumPy Data Analysis</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Pandas Data Analysis</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Data Visualization</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Introduction to Machine Learning</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Loading &amp; Exploration</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Cleaning</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Feature Selecting and Engineering</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Linear and Logistic Regression</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">K Nearest Neighbours</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Decision Trees</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Ensemble Learning and Random Forests</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Support Vector Machines</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">K-Means</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">PCA</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Science Career</strong></li></ul>

This course aims to teach you how to use Python for machine learning and data science.



Python for Data Science and Machine Learning

<strong>In this practical, hands-on course, you'll learn how to use R for effective data analysis and visualization and how to make use of that data in a practical manner. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language.</strong>
        <p>The course covers practical issues in statistical computing that include programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting on R code. Blending practical work with solid theoretical training, we take you from the basics of R programming to mastery.

We understand that theory is important to build a solid foundation, we also understand that theory alone isn't going to get the job done so that's why this course is packed with practical hands-on examples that you can follow step by step. Even if you already have some coding experience, or want to learn about the advanced features of the R programming language, this course is for you!

R coding experience is either required or recommended in job postings for data scientists, machine learning engineers, big data engineers, IT specialists, database developers, and much more. Adding R coding language skills to your resume will help you in any one of these data specializations requiring mastery of statistical techniques.

By the end of the course, you'll be a professional data scientist with R and confidently apply for jobs and will feel good knowing that you have the skills and knowledge to back it up.

All resources are placed here: https://github.com/PacktPublishing/Data-Science-and-Machine-Learning-with-R-from-A-Z-Course-Updated-for-2021-</p>
        <h2>What You Will Learn</h2><p>Learn data cleaning, processing, wrangling, and manipulation<br>Learn plotting in R (graphs, charts, plots, histograms, and more)<br>How to create a resume and land your first job as a data scientist<br>Learn machine learning and its various practical applications<br>Learn data and file management in R<br>Use R to clean, analyze, and visualize data</p>
        <h2>Audience</h2><p>This course is designed for beginners who want to learn about data science and machine learning. No prior knowledge of R is required.</p>
        <h2>Approach</h2><p>This course takes you through data analysis in R, data visualization in R, and machine learning with hands-on step-by-step training.</p>
        <h2>Key Features</h2><p>Learn data extraction and web scraping * Learn to build custom data solutions * Learn automating dynamic report generation</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Data-Science-and-Machine-Learning-with-R-from-A-Z-Course-Updated-for-2021-</p>
        <h2>About the Author</h2><h3>Juan E. Galvan</h3><p>Juan E. Galvan has been an entrepreneur since grade school. His background is in the tech space from digital marketing, e-commerce, web development to programming. He believes in continuous education with the best of a university degree without all the downsides of burdensome costs and inefficient methods. He looks forward to helping people expand their skillsets.</p>
        <h2>Course Outline</h2><h4>1. Data Science and Machine Leaning Course Introduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Data Science and Machine Learning Introduction Section Overview</p><p style='margin: 0'>This video explains data science and machine learning.</p></td></tr><tr><td style='padding: 15px;'><p>2. What is Data Science?</p><p style='margin: 0'>This video explains the concept of data science.</p></td></tr><tr><td style='padding: 15px;'><p>3. Machine Learning Overview</p><p style='margin: 0'>This video gives an overview of machine learning.</p></td></tr><tr><td style='padding: 15px;'><p>4. Data Science + Machine Learning Marketplace</p><p style='margin: 0'>This video explains the various trends and job opportunities in data science and machine learning.</p></td></tr><tr><td style='padding: 15px;'><p>5. Who is this Course For?</p><p style='margin: 0'>This video explains the audience for this course.</p></td></tr><tr><td style='padding: 15px;'><p>6. Data Science and Machine Learning Job Opportunities</p><p style='margin: 0'>This video explains the various job opportunities in data science and machine learning.</p></td></tr><tr><td style='padding: 15px;'><p>7. Data Science Job Roles</p><p style='margin: 0'>This video explains the various job roles for data science.</p></td></tr></tbody></table><br><h4>2. Getting Started with R</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Getting Started with R</p><p style='margin: 0'>This video explains the concept of R.</p></td></tr><tr><td style='padding: 15px;'><p>2. R Basics</p><p style='margin: 0'>This video explains the R basics.</p></td></tr><tr><td style='padding: 15px;'><p>3. Working with Files</p><p style='margin: 0'>This video explains working with files in R.</p></td></tr><tr><td style='padding: 15px;'><p>4. R Studio</p><p style='margin: 0'>This video explains R studio.</p></td></tr><tr><td style='padding: 15px;'><p>5. Tidyverse Overview</p><p style='margin: 0'>This video provides an overview of tidyverse.</p></td></tr><tr><td style='padding: 15px;'><p>6. Additional Resources</p><p style='margin: 0'>This video shares some additional resources that will help you get along with the course.</p></td></tr></tbody></table><br><h4>3. Data Types and Structures in R</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Data Types and Structures in R Section Overview</p><p style='margin: 0'>This video explains data types and structures in R.</p></td></tr><tr><td style='padding: 15px;'><p>2. Basic Types</p><p style='margin: 0'>This video explains basic types in R.</p></td></tr><tr><td style='padding: 15px;'><p>3. Vectors - Part One</p><p style='margin: 0'>This video introduces you to vectors.</p></td></tr><tr><td style='padding: 15px;'><p>4. Vectors - Part Two</p><p style='margin: 0'>This video explains how to interact with R using vectors.</p></td></tr><tr><td style='padding: 15px;'><p>5. Vectors: Missing Values</p><p style='margin: 0'>This video explains vector missing values.</p></td></tr><tr><td style='padding: 15px;'><p>6. Vectors: Coercion</p><p style='margin: 0'>This video explains coercion.</p></td></tr><tr><td style='padding: 15px;'><p>7. Vectors: Naming</p><p style='margin: 0'>This video explains vector naming.</p></td></tr><tr><td style='padding: 15px;'><p>8. Vectors: Miscellaneous</p><p style='margin: 0'>This video explains miscellaneous yet important concepts in vectors.</p></td></tr><tr><td style='padding: 15px;'><p>9. Working with Matrices</p><p style='margin: 0'>This video explains working with matrices.</p></td></tr><tr><td style='padding: 15px;'><p>10. Working with Lists</p><p style='margin: 0'>This video explains working with lists.</p></td></tr><tr><td style='padding: 15px;'><p>11. Introduction to Data Frames</p><p style='margin: 0'>This video explains introduction to data frames.</p></td></tr><tr><td style='padding: 15px;'><p>12. Creating Data Frames</p><p style='margin: 0'>This video explains creating data frames.</p></td></tr><tr><td style='padding: 15px;'><p>13. Data Frames: Helper Functions</p><p style='margin: 0'>This video explains data frames helper functions.</p></td></tr><tr><td style='padding: 15px;'><p>14. Data Frames: Tibbles</p><p style='margin: 0'>This video explains Tibbles in data frames.</p></td></tr></tbody></table><br><h4>4. Intermediate R</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Intermedia R Section Introduction</p><p style='margin: 0'>This video introduces you to R section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Relational Operators</p><p style='margin: 0'>This video explains relational operators.</p></td></tr><tr><td style='padding: 15px;'><p>3. Logical Operators</p><p style='margin: 0'>This video explains logical operators,</p></td></tr><tr><td style='padding: 15px;'><p>4. Conditional Statements</p><p style='margin: 0'>This video explains conditional statements.</p></td></tr><tr><td style='padding: 15px;'><p>5. Working with Loops</p><p style='margin: 0'>This video explains working with loops.</p></td></tr><tr><td style='padding: 15px;'><p>6. Working with Functions</p><p style='margin: 0'>This video explains working with functions in R.</p></td></tr><tr><td style='padding: 15px;'><p>7. Working with Packages</p><p style='margin: 0'>This video explains working with packages.</p></td></tr><tr><td style='padding: 15px;'><p>8. Working with Factors</p><p style='margin: 0'>This video explains working with factors in R.</p></td></tr><tr><td style='padding: 15px;'><p>9. Dates and Times</p><p style='margin: 0'>This video explains dates and times in R.</p></td></tr><tr><td style='padding: 15px;'><p>10. Functional Programming</p><p style='margin: 0'>This video explains functional programming.</p></td></tr><tr><td style='padding: 15px;'><p>11. Data Import/Export</p><p style='margin: 0'>This video explains how to import and export data in R.</p></td></tr><tr><td style='padding: 15px;'><p>12. Working with Databases</p><p style='margin: 0'>This video explains working with databases.</p></td></tr></tbody></table><br><h4>5. Data Manipulation in R</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Data Manipulation Section Introduction</p><p style='margin: 0'>This video introduces you to data manipulation.</p></td></tr><tr><td style='padding: 15px;'><p>2. Tidy Data</p><p style='margin: 0'>This video explains tidy data.</p></td></tr><tr><td style='padding: 15px;'><p>3. The Pipe Operator</p><p style='margin: 0'>This video explains pipe operator.</p></td></tr><tr><td style='padding: 15px;'><p>4. {dplyr}: The Filter Verb</p><p style='margin: 0'>This video explains the filter verb.</p></td></tr><tr><td style='padding: 15px;'><p>5. {dplyr}: The Select Verb</p><p style='margin: 0'>This video explains the select verb</p></td></tr><tr><td style='padding: 15px;'><p>6. {dplyr}: The Mutate Verb</p><p style='margin: 0'>This video explains the mutate verb.</p></td></tr><tr><td style='padding: 15px;'><p>7. {dplyr}: The Arrange Verb</p><p style='margin: 0'>This video explains the purpose of arrange verb.</p></td></tr><tr><td style='padding: 15px;'><p>8. {dplyr}: The Summarize Verb</p><p style='margin: 0'>This video explains the summarize verb.</p></td></tr><tr><td style='padding: 15px;'><p>9. Data Pivoting: {tidyr}</p><p style='margin: 0'>This video explains data pivoting.</p></td></tr><tr><td style='padding: 15px;'><p>10. String Manipulation: {stringr}</p><p style='margin: 0'>This video explains string manipulation.</p></td></tr><tr><td style='padding: 15px;'><p>11. Web Scraping: {rvest}</p><p style='margin: 0'>This video explains web scraping.</p></td></tr><tr><td style='padding: 15px;'><p>12. JSON Parsing: {jsonlite}</p><p style='margin: 0'>This video explains JSON parsing.</p></td></tr></tbody></table><br><h4>6. Data Visualization in R</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Data Visualization in R Section Introduction</p><p style='margin: 0'>This video explains data visualization in R.</p></td></tr><tr><td style='padding: 15px;'><p>2. Getting Started with Data Visualization in R</p><p style='margin: 0'>This video explains getting started with data visualization in R.</p></td></tr><tr><td style='padding: 15px;'><p>3. Aesthetics Mappings</p><p style='margin: 0'>This vide explains aesthetics mappings.</p></td></tr><tr><td style='padding: 15px;'><p>4. Single Variable Plots</p><p style='margin: 0'>This video focuses on single variable plots.</p></td></tr><tr><td style='padding: 15px;'><p>5. Two Variable Plots</p><p style='margin: 0'>This video explains two variable plots.</p></td></tr><tr><td style='padding: 15px;'><p>6. Facets, Layering, and Coordinate Systems</p><p style='margin: 0'>This video explains facets, layering, and coordinate systems.</p></td></tr><tr><td style='padding: 15px;'><p>7. Styling and Saving</p><p style='margin: 0'>This video explains styling and saving.</p></td></tr></tbody></table><br><h4>7. Creating Reports with R Markdown</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction to R Markdown</p><p style='margin: 0'>This video is an introduction to R.</p></td></tr></tbody></table><br><h4>8. Building Webapps with R Shiny</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction to R Shiny</p><p style='margin: 0'>This video is an introduction to R Shiny</p></td></tr><tr><td style='padding: 15px;'><p>2. Creating a Basic R Shiny App</p><p style='margin: 0'>This video helps you to create a basic R shiny app.</p></td></tr><tr><td style='padding: 15px;'><p>3. Other Examples with R Shiny</p><p style='margin: 0'>This video gives various examples with R shiny.</p></td></tr></tbody></table><br><h4>9. Introduction to Machine Learning</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction to Machine Learning Part One</p><p style='margin: 0'>This video is an introduction to machine learning.</p></td></tr><tr><td style='padding: 15px;'><p>2. Introduction to Machine Learning Part Two</p><p style='margin: 0'>This video explains the different approaches in machine learning.</p></td></tr></tbody></table><br><h4>10. Data Preprocessing</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Data Preprocessing Introduction</p><p style='margin: 0'>This video introduces you to data preprocessing.</p></td></tr><tr><td style='padding: 15px;'><p>2. Data Preprocessing</p><p style='margin: 0'>This video explains some of the practical ways of data preprocessing.</p></td></tr></tbody></table><br><h4>11. Linear Regression: A Simple Model</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Linear Regression: A Simple Model Introduction</p><p style='margin: 0'>This video explains a simple linear regression model.</p></td></tr><tr><td style='padding: 15px;'><p>2. A Simple Model</p><p style='margin: 0'>This video demonstrates a practical application of machine learning.</p></td></tr></tbody></table><br><h4>12. Exploratory Data Analysis</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Exploratory Data Analysis Introduction</p><p style='margin: 0'>This video gives an introduction to exploratory data analysis.</p></td></tr><tr><td style='padding: 15px;'><p>2. Hands-on Exploratory Data Analysis</p><p style='margin: 0'>This video explains hands-on exploratory data analysis.</p></td></tr></tbody></table><br><h4>13. Linear Regression - a Real Model</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Linear Regression - Real Model Section Introduction</p><p style='margin: 0'>This video explains linear regression - a real model.</p></td></tr><tr><td style='padding: 15px;'><p>2. Linear Regression in R - Real Model</p><p style='margin: 0'>This video explains linear regression in R.</p></td></tr></tbody></table><br><h4>14. Logistic Regression</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction to Logistic Regression</p><p style='margin: 0'>This video introduces you to logistic regression.</p></td></tr><tr><td style='padding: 15px;'><p>2. Logistic Regression in R</p><p style='margin: 0'>This video explains logistic regression in R.</p></td></tr></tbody></table><br><h4>15. Starting a Career in Data Science</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Starting a Data Science Career Section Overview</p><p style='margin: 0'>This video explains section overview of data science and career.</p></td></tr><tr><td style='padding: 15px;'><p>2. Creating a Data Science Resume</p><p style='margin: 0'>This video explains creating a data science resume.</p></td></tr><tr><td style='padding: 15px;'><p>3. Getting Started with Freelancing</p><p style='margin: 0'>This vide explains how to get started with freelancing.</p></td></tr><tr><td style='padding: 15px;'><p>4. Top Freelance Websites</p><p style='margin: 0'>This video focuses on top freelancing websites.</p></td></tr><tr><td style='padding: 15px;'><p>5. Personal Branding</p><p style='margin: 0'>This video explains personal branding.</p></td></tr><tr><td style='padding: 15px;'><p>6. Networking Do's and Don'ts</p><p style='margin: 0'>This video explains networking do's and don'ts.</p></td></tr><tr><td style='padding: 15px;'><p>7. Setting Up a Website</p><p style='margin: 0'>This video explains how to set up a website.</p></td></tr></tbody></table>

In this practical, hands-on course, you'll learn how to use R for effective data analysis and visualization and how to make use of that data in a practical manner. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language.

Data Science and Machine Learning with R from A-Z Course [Updated for 2021]

Janets

Data Science and Machine Learning using Python : A Bootcamp

Get involved in a learning adventure, mastering R from foundational basics to advanced techniques. This course is a gateway to the realm of data science. Explore statistical machine learning models and intricacies of deep learning and create interactive Shiny apps. Unleash the power of R and elevate your proficiency in data-driven decision-making.

R Ultimate 2023 - R for Data Science and Machine Learning

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					<div><p>Python has steadily ascended the ranks in the tech world, becoming the go-to language for Data Science and Machine Learning pursuits. Its versatility and ease of use make it an optimal choice for those aspiring to delve into the intricate realms of data analysis and algorithm development. By integrating Python into the curriculum, this course ensures that learners are not only familiar with the language but also proficient in its application to Data Science and Machine Learning tasks.</p><p>Data Science, on the other hand, stands as the backbone of today's analytical advancements. With the ever-growing quantum of data, there's a dire need for professionals who can sift through this data deluge and extract meaningful insights. This course simplifies complex topics, making it easier for learners to grasp the intricate mechanics of data manipulation, processing, and analysis. By emphasizing Python's role in Data Science, the course underscores its significance in modern-day data operations.</p><p>Lastly, Machine Learning represents the pinnacle of automated data analysis. With the power of Python and the methodologies of Data Science, Machine Learning enables systems to learn from data and make decisions. This course elucidates these concepts, teaching learners to design, implement, and test Machine Learning algorithms. The synergy of Python, Data Science, and Machine Learning in this curriculum ensures that, by the end, learners are well-equipped to tackle any data challenge that comes their way.</p></div>
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			<h2><b> Learning outcome</b></h2>		</div>
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										<span>Acquire in-depth knowledge of Data Science techniques using Python.</span>
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										<span>Understand and implement Machine Learning algorithms.</span>
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										<span>Analyze and visualize data with Python libraries like Pandas and Matplotlib.</span>
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										<span>Evaluate and compare Machine Learning algorithms for optimum results.</span>
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										<span>Develop real-time prediction models using trained datasets.</span>
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			<h2> <b>Why should I take this course?</b></h2>		</div>
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										<span>Stay ahead in the rapidly growing field of Data Science and Machine Learning.</span>
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										<span>Enhance career opportunities in the tech and data sectors.</span>
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										<span>Learn to use Python, a leading programming language in Data Science.</span>
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										<span>Address real-world business challenges using data analysis.</span>
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										<span>Achieve proficiency in handling and visualizing large datasets.</span>
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			<h2> <b>Requirements</b></h2>		</div>
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										<span>Eagerness to learn Data Science and Machine Learning.</span>
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Skill Up

Master Data Science and Machine Learning with Python to transform data-driven decisions in businesses.

Data Science & Machine Learning with Python

<strong>In the fast-paced world of data science and machine learning, you have to stay up-to-date and keep ahead of the competition. For this, you have to constantly be on the lookout for the latest trends in tools and techniques for data science and machine learning. You don't want to miss out on the latest trend and the tool of the future! Right now, that tool is the Julia programming language. It's the hot new language that all ML and data science experts are very excited about. Learning Julia will open up several doors for you in your career!</strong>
        <p>The objective of this course is to give you a strong foundation needed to excel in Julia and learn the core of the language as well as the applied side in the shortest amount of time possible.

We won't waste time with the theory of why Julia is fast. We will jump right into the details and start coding. You will quickly realize how easy it is to learn this state-of-the-art and promising language. You will see how you can start using Julia to excel in your current job without moving the whole stack to Julia immediately.

After explaining the basic concepts, we jump to case studies in data science and then machine learning. We apply both traditional machine learning models and then get to deep learning. You will see how Julia can help you create deep learning models from scratch in just a few lines of code and then move on to the state-of-the-art models without spending too much time.

This way, you get to learn the most important concepts in this subject in the shortest amount of time possible without having to deal with the details of the less relevant topics. Once you have developed an intuition of the important stuff, you can then learn the latest and greatest models even on your own!

By the end of the course, you will have a strong understanding of Julia programming language fundamentals.
The code files are available here: https://github.com/PacktPublishing/Julia-Programming-Language---From-Zero-to-Expert-</p>
        <h2>What You Will Learn</h2><p>Learn coding in Julia programming language<br>Use DataFrames (equivalent to Pandas) in Julia<br>Create ML models from scratch in a way that helps you make modifications easily<br>Learn data wrangling with Julia<br>Use Julia to perform data manipulation, Apache Arrow, grouping, and analysis<br>Classify using decision trees and random forests</p>
        <h2>Audience</h2><p>This course is for all levels of data science and machine learning practitioners aiming to enhance their abilities and skill level in DS and ML. Developers who want to know how to harness the power of big data can also go for this course.<br><br>A basic understanding of programming is a must. Understanding Python, basic data science (reading CSVs and so on), and basic concepts of deep learning (such as classification) is not necessary but would be helpful.</p>
        <h2>Approach</h2><p>This course follows a code-oriented and case-study-based approach. In this course, you will learn by practice as every concept explanation is followed by practical implementation.</p>
        <h2>Key Features</h2><p>Learn the syntax of Julia and its differences from Python * Learn machine learning models, both traditional and deep * Explore data science case studies, including analysis and clustering</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Julia-Programming-Language---From-Zero-to-Expert-</p>
        <h2>About the Author</h2><h3>Dr. Mohammad Nauman</h3><p>Dr. Mohammad Nauman has a PhD in computer science and a PostDoc from the Max Planck Institute for software systems. He has been programming since early 2000 and has worked with many different languages, tools, and platforms. He holds extensive research experience with many state-of-the-art models. His research in Android security has led to some major shifts in the Android permission model.
He loves teaching and the most important reason he teaches online is to make sure that maximum people can learn through his content. Hope you have fun learning with him!</p>
        <h2>Course Outline</h2><h4>1. Intro and Setting up</h4><p></p><br><h4>2. Core Language Basics</h4><p></p><br><h4>3. Arrays and Matrices: Native Language Support</h4><p></p><br><h4>4. Functions and Fun Stuff</h4><p></p><br><h4>5. Getting Started with Data Science</h4><p></p><br><h4>6. Case Studies in Data Science</h4><p></p><br><h4>7. Deep Learning - Flux in Julia</h4><p></p><br><h4>8. Parting Words</h4><p></p>

Programming

In the fast-paced world of data science and machine learning, you have to stay up-to-date and keep ahead of the competition. For this, you have to constantly be on the lookout for the latest trends in tools and techniques for data science and machine learning. You don't want to miss out on the latest trend and the tool of the future! Right now, that tool is the Julia programming language. It's the hot new language that all ML and data science experts are very excited about. Learning Julia will open up several doors for you in your career!

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