1114 Courses delivered Online

Lean Six Sigma Green Belt Certification Program: On-Demand This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. Green Belt is not just a role, it is also a competency required for leadership positions at many top companies. This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. With a real-world project focus, the series will teach the fundamental methodology, tools, and techniques of the Define, Measure, Analyze, Improve and Control Process Improvement Methodology. This course is delivered through sixteen 3-hour online sessions. What you Will Learn At the end of this program, you will be able to: Identify strategies for effectively leading high performing process improvement teams Analyze whether projects align with business strategy Apply process improvement methodologies to DMAIC steps, based on real world scenarios Explain ways to appropriately respond to process variation Distinguish among best practice problem solving methodologies Evaluate and effectively communicate data-driven decisions, based on real world scenarios Introduction Lean Six Sigma & quality The vision The methodologies The metric Project Selection Why Projects Random idea generation Targeted idea generation CTQs (Critical to Quality) & projects Project screening criteria Quick improvements Introduction to Define Project Planning Developing the core charter Developing a project charter Facilitation Process Management Business process management Top-down process mapping Voice of the Customer Voice of Customer Stakeholder analysis Communication planning Kicking off the project Define Summary Introduction to Measure Data Collection Fact-based decision making Data sampling Operations definitions Data collection plan Measurement system analysis Graphical Statistics for Continuous Data Meet Six SigmaXL Graphical & statistical tools Data stratification Graphical Statistics for Discrete Data Pareto analysis Dot plots Plotting data over time: Looking for patterns Variation Concepts Variation is reality Special Cause and Common Cause variation Example of standard business reporting Individuals Control Chart Process Capability Genesis of process capability Calculating the metrics of Six Sigma Yield metrics: Measuring process efficiency Cost of Poor Quality The Cost of Poor Quality (COPQ) Cost of Quality categories Calculating the Cost of Poor Quality Measure Summary Introduction to Analyze Process Analysis Introduction to process analysis Value-added analysis Cycle time analysis WIP & pull systems Analyzing bottlenecks and constraints Cause & Effect Analysis Fishbone/Ishikawa diagram 5-Whys analysis Graphical & statistical tools Advanced Analysis Why use hypothesis rests? Hypothesis tests Correlation and regression analysis Analyze Summary Introduction to Improve Solutions Creativity techniques Generating alternative solutions Solution selection techniques Introduction to Design of Experiments Introduction to DOE DOE activity Error Proofing Failure mode & effect analysis Poka-Yoke Project Management Fundamentals Successful teams Project roles Conflict management Standardization Standardization The Visual Workplace 5S Piloting & Verifying Results What is a pilot? Evaluating results Improve Summary Introduction to Control Statistical Process Control Review of Special & Common Cause variation Review of Individual Control Chart P-Chart for discrete proportion data Transition Planning Control plan Project closure Control Summary Summary and Next Steps

Lean Six Sigma Green Belt Certification Program - Become Green Belt Certified: On-Demand This course explores the DMAIC process in depth and enables you to achieve IIL's Lean Six Sigma Green Belt Certification. DMAIC is the foundation of Lean Six Sigma and process improvement. The incremental steps of "Define, Measure, Analyze, Improve, Control" give structure and guidance to improving quality, performance, and productivity. Green Belt is not just a role, it is also a competency required for leadership positions at many top companies. This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. With a real-world project focus, the series will teach the fundamental methodology, tools, and techniques of the Define, Measure, Analyze, Improve and Control Process Improvement Methodology. What You Will Learn At the end of this program, you will be able to: Identify strategies for effectively leading high performing process improvement teams Analyze whether projects align with business strategy Apply process improvement methodologies to DMAIC steps, based on real world scenarios Explain ways to appropriately respond to process variation Distinguish among best practice problem solving methodologies Evaluate and effectively communicate data-driven decisions, based on real world scenarios Introduction Lean Six Sigma & quality The vision The methodologies The metric Project Selection Why Projects Random idea generation Targeted idea generation CTQs (Critical to Quality) & projects Project screening criteria Quick improvements Introduction to Define Project Planning Developing the core charter Developing a project charter Facilitation Process Management Business process management Top-down process mapping Voice of the Customer Voice of Customer Stakeholder analysis Communication planning Kicking off the project Introduction to Measure Data Collection Fact-based decision making Data sampling Operations definitions Data collection plan Measurement system analysis Graphical Statistics for Continuous Data Meet Six SigmaXL Graphical & statistical tools Data stratification Graphical Statistics for Discrete Data Pareto analysis Dot plots Plotting data over time: Looking for patterns Variation Concepts Variation is reality Special Cause and Common Cause variation Example of standard business reporting Individuals Control Chart Process Capability Genesis of process capability Calculating the metrics of Six Sigma Yield metrics: Measuring process efficiency Cost of Poor Quality The Cost of Poor Quality (COPQ) Cost of Quality categories Calculating the Cost of Poor Quality Introduction to Analyze Process Analysis Introduction to process analysis Value-added analysis Cycle time analysis WIP & pull systems Analyzing bottlenecks and constraints Cause & Effect Analysis Fishbone/Ishikawa diagram 5-Whys analysis Graphical & statistical tools Advanced Analysis Why use hypothesis tests? Hypothesis tests Correlation and regression analysis Introduction to Improve Solutions Creativity techniques Generating alternative solutions Solution selection techniques Introduction to Design of Experiments Introduction to DOE DOE activity Error Proofing Failure mode & effect analysis Poka-Yoke Project Management Fundamentals Successful teams Project roles Conflict management Standardization Standardization The Visual Workplace 5S Piloting & Verifying Result What is a pilot? Evaluating results Introduction to Control Statistical Process Control Review of Special & Common Cause variation Review of Individual Control Chart P-Chart for discrete proportion data Transition Planning Control plan Project closure

Ethernet LANS training course description This course has been replaced as part of our continuous curriculum development. Please see our Definitive Ethernet switching course What will you learn Describe what Ethernet is and how it works. Install Ethernet networks Troubleshoot Ethernet networks Analyse Ethernet packets Design Ethernet networks Recognise the uses of Hubs, Bridges, switches and routers. Ethernet LANS training course details Who will benefit: Those wishing to find out more about how their LAN works. Prerequisites: Intro to Data comms & networking. Duration 3 days Ethernet LANS training course contents What is Ethernet? LANS, What is Ethernet?, history, standards, the OSI reference model, how Ethernet works, CSMA/CD. Ethernet Cabling UTP, cat 3,4,5, Cat 5e, Cat 6, Cat 7, fibre optic cable, MMF, SMF. Hands on Making a cable. 802.3 physical specifications Distance limitations, hubs and repeaters, 5-4-3-2-1 rule, 10BaseT, 10BaseF, 100BaseTX, 100BaseFX, 1000BaseSX, 1000BaseT, 10gbe. Hands on Working with hubs. Ethernet layer 2 Overview, NICS, device drivers, MAC addresses, broadcasts, multicasts, frame formats, Ether II, 802.3, 802.2, SNAP, compatibility, Ethernet type numbers, Ethernet multicast addresses, Ethernet vendor codes. Hands on Installing Ethernet components, analysing MAC headers. IP and Ethernet ARP Hands on Analysing ARP packets. Ethernet extensions Full/half duplex, auto negotiation, flow control methods, 802.3ad, 802.3af, 802.3ah. Hands on Configuration of full/half duplex. Ethernet speed enhancements Encoding, Carrier extension, packet bursting, jumbo frames. Prioritisation 802.1P, 802.1Q, TOS, WRR, QOS, VLANs. Hands on 802.1p testing Interconnecting LANS Broadcast domains, Collision domains, What are bridges, transparent bridging, What are switches? STP, VLANS, What are routers? Layer 3 switches, Connecting Ethernet to the WAN. Hands on STP, Analysing Ethernet frames in a routed architecture. Troubleshooting and maintaining Ethernet Utilisation, performance, TDR and other testers, bottlenecks, statistics, RMON. Hands on Monitoring performance, troubleshooting tools.

This masterclass will enable you to gain comprehensive awareness and be a supportive guide for Key Staff through fully understanding recent changes and developments in one of the fastest growing categories of safeguarding concerns.

£22/month Interest-free* Payments6 months Deposit£62 Total Price£290 Make an Enquiry × [gravityform id="76" title="false" description="false" ajax="true"] Tutor Support: Till exam Start Anytime: With 3 years of access to course materials Accredited by: Pearson Edexcel & Regulated by OFQUAL Mock Test Practice Get expert feedback on mock test Online Learning: Learn from anywhere, whenever you want Exams Preparation For May/June 2024 Gain the GCSE qualifications you get from school, 100% online at your own pace. Opportunity to book Live 1:1 or Group tutor support via Zoom Excellent student reviews with high satisfaction rates Full assistance is scheduling your GCSE exams Study on your phone, tablet or laptop at your own pace You will get unlimited tutor support via email Why GCSE Maths Course right for you? Our GCSE Maths online course is very flexible, allowing you to learn at your own pace without having to disrupt your busy life. It's designed to help you overcome any difficulties you may have with mathematics. You can book 1:1 or group Live Tutor Support via Zoom with your maths tutor Rita. Once you complete our GCSE Maths course, you'll build a solid foundation for further education and career advancement. Start your journey to a better future today! GCSE Maths Course & Exam Details GCSE Exam Details You choose to sit for the Foundation Tier or Higher Tier For Foundation Tier grades 1 to 5 will be given. For Higher Tier grades 4 to 9 will be given. For more updated information on the grade boundaries, you can check out GCSE Maths Grade Boundaries for All Boards - [2019 to 2023] blog. You can book your GCSE exam with us; we have GCSE exam centres across the UK. Explore the list of GCSE Exam Centres, and see nearest exam centre. In order to book your GCSE exams please email us at info@lead-academy.org Live Tutor Support Details Get personalised guidance and assistance throughout your GCSE exam preparation. Clarify difficult concepts and receive valuable feedback on practice exams, assignments and mock exams. 1:1 or Group Live classes are available with maths tutor Rita until the exam. Group Sessions Cost: £45+VAT per month (Class schedule once a week | 4 classes per month) 1:1 Live Class via Zoom available at the cost of £24+VAT per hour. You'll have the flexibility to choose your own schedule for the classes. Various class schedule options are available in the cart for you to choose from while booking. The classes are designed to prepare you for the exam. You will also get unlimited tutor support via email. Entry Requirements This GCSE Maths Course is available to all students, of all academic backgrounds and no experience or previous qualifications are required. You need a laptop or PC and stable internet connection GCSE Maths Exam Structure The Pearson Edexcel GCSE Maths consists of three paper-based assessments. Paper 1 Topics covered: Number, algebra, ratio, proportion and rates of change, geometry and measures, probability and statistics Exam duration: 1 Hour 30 minutes written exam Marks: 80 Weight: 33.33% of GCSE Question type: Written examination papers with a range of different question types Other information: No calculator is allowed Paper 2 Topics covered: Number, algebra, ratio, proportion and rates of change, geometry and measures, probability and statistics Exam duration: 1 Hour 30 minutes written exam Marks: 80 Weight: 33.33% of GCSE Question type: Written examination papers with a range of different question types Other information: Calculator is allowed Paper 3 Topics covered: Number, algebra, ratio, proportion and rates of change, geometry and measures, probability and statistics Exam duration: 1 Hour 30 minutes written exam Marks: 80 Weight: 33.33% of GCSE Question type: Written examination papers with a range of different question types Other information: Calculator is allowed Course Curriculum GCSE Maths Foundation Tier Number FT In the number FT classes, you will be learning how to order positive and negative integers, decimals, and fractions, use the symbols =, ≠, <, >, ≤, ≥, apply the four operations to integers, decimals, and simple fractions and mixed numbers - both positive and negative, understand and use place value, recognize and use relationships between operations, including inverse operations, use conventional notation for priority of operations, including brackets, powers, roots and reciprocals and many more things. Algebra FT You will be learning about algebraic manipulation in this module. These classes will also cover substituting numerical values into formulae and expressions, including scientific formulae. Understand and use the concepts and vocabulary of expressions, equations, formulae, inequalities, terms, and factors. Ratio, proportion and rates of change FT In these classes, you will learn to change freely between related standard units (e.g. time, length, area) and compound units (e.g. speed, rates of pay, prices) in numerical and algebraic contexts. You will also learn to use scale factors, scale diagrams and maps and understand and use the proportion as equality of ratios. Geometry FT In the geometry FT classes, you will learn details about perimeter, area, squares, rectangles, and triangles. You will also be introduced to the related formulas of perimeter, area, square, rectangles, triangles, and more. Probability FT From the probability FT chapter, you will learn about relating relative expected frequencies to theoretical probability; using appropriate language and the 0 to 1 probability scale, apply the property that the probabilities of an exhaustive set of outcomes sum to 1 and apply the property that the probabilities of an exhaustive set of mutually exclusive events sum to 1 and enumerate sets and combinations of sets systematically, using tables, grids, venn diagrams. Statistics FT You will learn to Interpret, analyse, and compare the distributions of data sets from empirical distributions, apply statistics to describe a population, use and interpret scatter graphs of bivariate data, and recognize correlation; this learning will help in understanding data, surveys, and more. Mock Paper 1 GCSE Maths Mock Paper Instruction GCSE Maths FT Paper-1 GCSE Maths FT Paper-1 MS GCSE Maths FT Paper-2 GCSE Maths FT Paper-2 MS GCSE Maths FT Paper-3 GCSE Maths FT Paper-3 MS Mock Paper 2 GCSE Maths Mock Paper Instruction GCSE Maths FT Paper-1. GCSE Maths FT Paper-1 MS. GCSE Maths FT Paper-2. GCSE Maths FT Paper-2 MS. GCSE Maths FT Paper-3. GCSE Maths FT Paper-3 MS. GCSE Maths Higher Tier Number HT In the number HT classes, you will be learning how to order positive and negative integers, decimals, and fractions, use the symbols =, ≠, <, >, ≤, ≥, apply the four operations to integers, decimals, and simple fractions and mixed numbers - both positive and negative, understand and use place value, recognize and use relationships between operations, including inverse operations, use conventional notation for the priority of operations, including brackets, powers, roots and reciprocals, and many more things. Algebra HT You will be learning about algebraic manipulation in this module. These classes will also cover the substitution of numerical values into formulae and expressions, including scientific formulae. Understand and use the concepts and vocabulary of expressions, equations, formulae, inequalities, terms, and factors. Ratio, proportion and rates of change HT In these classes, you will learn to change freely between related standard units (e.g. time, length, area) and compound units (e.g. speed, rates of pay, prices) in numerical and algebraic contexts. You will also learn to use scale factors, scale diagrams and maps and understand and use the proportion as equality of ratios. Geometry HT In the geometry HT classes, you will learn about perimeter, area, squares, rectangles, and triangles in detail. Along with this, you will be introduced to the related formulas of perimeter, area, square, rectangles, triangles, and more. Probability HT From the probability HT chapter, you will learn about relating relative expected frequencies to theoretical probability; using appropriate language and the 0 to 1 probability scale, apply the property that the probabilities of an exhaustive set of outcomes sum to 1 and apply the property that the probabilities of an exhaustive set of mutually exclusive events sum to 1 and enumerate sets and combinations of sets systematically, using tables, grids, Venn diagrams. Statistics HT You will learn to Interpret, analyse, and compare the distributions of data sets from empirical distributions, apply statistics to describe a population, use and interpret scatter graphs of bivariate data, and recognize correlation; this learning will help in understanding data, surveys, and more. Mock Paper 1 GCSE Maths Mock Paper Instruction GCSE Maths HT Paper-1 GCSE Maths HT Paper-1 MS GCSE Maths HL Paper-2 GCSE Maths HL Paper-2 MS GCSE Maths HL Paper-3 GCSE Maths HL Paper-3 MS Mock Paper 2 GCSE Maths Mock Paper Instruction GCSE Maths HT Paper-1. GCSE Maths HT Paper-1 MS. GCSE Maths HT Paper-2. GCSE Maths HT Paper-2 MS. GCSE Maths HT Paper-3. GCSE Maths HT Paper-3 MS. Awarding Body Pearson Edexcel is the most popular and prestigious awarding body in the UK and internationally. GCSE is a recognised academic credential at the secondary level worldwide. This qualification involves theoretical study and research. Pearson Edexcel prepares learners for higher education or employment. Edexcel's qualifications meet the needs of modern learners and are based on high British education standards. Pearson Edexcel's qualifications provide learners with necessary skills and knowledge to achieve their goals. FAQs Why should I do this higher-tier GCSE Math course? You must do the higher GCSE Math as it requires for university admission and also every stage of your life. GCSE Math is one of the core subjects of the GCSE course that every student should study. Do you offer any fundamental courses in GCSE Math? Yes, we offer the fundamental GCSE Math course, which helps you improve basic math. If you feel your math basics must be polished, you can do this course with us. How to pass GCSE maths? To pass the General Certificate of Secondary Education maths, start revision early and consistently, and practise with quality revision, not just reading through notes. Believe in your ability and personalise your approach to the exam. Focus on learning the basics first, like fractions and algebra. Practising under timed conditions can help you develop a strategy that works best for you. How many marks do you need to pass Pearson Edexcel maths? To pass Pearson Edexcel Maths, you need to achieve a grade of 4 or higher. In terms of marks, this equates to achieving at least 120 out of 240 for the Foundation tier and at least 135 out of 240 for the Higher tier. However, it's important to note that the grade boundaries can vary slightly from year to year, depending on the difficulty of the exam. What is the grading system for the exam? The grades for GCSE range from 9-1, with 9 being the highest grade and 1 being the lowest. I made my payment. How will I get access to the course? A confirmation email will be sent to your registered email after payment. Hereafter anytime, you can start your learning journey with Lead Academy. I am from outside the UK. Will I get access to the Course? Yes, you can. Since it is an e-learning course, anyone from anywhere can enrol in our courses. What is an Accredited course? The professional body approves the procedures if any e-learning platform claims its courses are accredited. What is an Edexcel accredited course? Exdexcel is a British multinational education and examination body. If any functional skills training providers claim the course is Edexcel accredited, that means the course has been approved by the governor body of Edexcel. Their certificates have been valued in the UK and worldwide.

Linux engineer certification training course description LPIC-2 is the second certification in LPI's multi level professional certification program. This course teaches the skills necessary to pass the LPI 201 exam; the first of two LPIC-2 exams. Specifically, the course covers the administration of Linux systems in small to medium sized mixed networks. What will you learn Perform advanced administration tasks. Perform advanced file system administration. Linux engineer certification training course details Who will benefit: Linux administrators. Prerequisites: Linux system administration (LPIC-1) Duration 5 days Linux engineer certification fundamentals training course contents Part I The LPI 201 Exam Starting a System The Linux Boot Process, Firmware Startup, BIOS Startup, UEFI Startup, Linux Bootloaders, GRUB Legacy, GRUB 2, Alternative Bootloaders, Secure Bootloaders, Process Initialization, SysV Method, systemd Method, Upstart Method, System Recovery, Kernel Failures, Root Drive Failure. Maintaining the System Fluid Messaging, Static Messaging, System backups, Backup Strategies, Performing Backups, Installing Programs from Source, Obtaining and unpacking Installation Files, Compiling Programs, Resource Usage: Managing, measuring, predicting and troubleshooting. Mastering the Kernel What Is the Kernel? Kernel Features, Parts of the Kernel, Kernel Versions, Obtaining Source Code, Creating the Configuration File, Compiling and Installing the Kernel, Compiling and Installing Modules, Creating an Initial RAM Disk, Booting the New Kernel, Creating a Kernel Package, Maintaining the Kernel, Working with Module Files, Module Commands, Working with Hardware, Automatically Detecting Hardware, Troubleshooting the Kernel. Managing the Filesystem The Linux Filesystem, Filesystem Structures, Filesystem Types, Making Filesystems, Attaching Filesystems, Memory-Based Linux Filesystems, the Btrfs Filesystem, Btrfs Subvolumes, Btrfs Snapshots, Optical Filesystems, Swap Filesystems, Network-Based Filesystems, Auto-Mounting, Encrypted Filesystems, Maintaining Linux Filesystems, Adjusting a Filesystem, Checking and Repairing a Filesystem, SMART. Administering Advanced Storage Devices Configuring RAID, Implementing RAID on Linux, Managing a RAID Array, Adjusting Storage Devices, Looking at Drive Interface Concepts, Testing and Tuning Drives, Implementing iSCSI, Managing Logical Volumes, LVM, Creating Logical Volumes, Supporting Logical Volumes, Understanding the Device Mapper. Navigating Network Services Networking Basics, The Physical Layer, The Network Layer, The Transport Layer, The Application Layer, Configuring Network Features, Network Configuration Files, Graphical Tools, Command-Line Tools, Basic Network Troubleshooting, Checking the Log Files, the ARP Cache, Sending Test Packets, Testing Network Routes, Testing Client/Server Connectivity, Finding Host Information, Network Security, Advanced Network Troubleshooting, Viewing Open Network Connections, Viewing Network Statistics, Scanning the Network, Capturing Network Traffic.

In today's data-driven world, 82% of businesses demand Data Science professionals - and they're willing to pay for it! With average global salaries of Data Scientists and Machine Learning experts surpassing $120,000 annually, it's clear: the future belongs to those who understand data. Our Advanced Diploma in Data Science & Machine Learning - Level 7 is meticulously designed to offer profound knowledge and skills . This Data Science & Machine Learning bundle encompasses a comprehensive selection, from the nuances of Statistics & Probability to the intriguing applications of Machine Learning in Flutter. Also, this comprehensive Data Science & Machine Learning bundle ensures you're well-equipped with the essential knowledge required in today's competitive global market. By opting for this Data Science & Machine Learning advanced diploma, you're not just learning - you're investing in a future filled with opportunities, lucrative incomes, and immense professional demand globally. Data Science & Machine Learning Course Learning Outcomes Grasp the fundamentals of Statistics & Probability. Acquire proficiency in Python for Data Science. Understand R programming in data analytics context. Dive deep into MySQL and its applications in Data Science. Master SQL techniques for Data Visualization and Analytics. Lay a strong foundation in basic machine learning concepts. Navigate through Azure Machine Learning and its utilities. This Data Science & Machine Learning bundle course, however, is designed to be your compass, guiding you through the intricacies of the most pivotal topics. With the Advanced Diploma, you delve deep into the mathematical bedrock of data science through Statistics & Probability. Python and R, the stalwarts of data programming, are unravelled, offering insights into their unique capabilities. SQL's unmatched prowess in data visualisation and analytics is highlighted, while Azure provides a window into the world of cloud-based machine learning. Lastly, understand the synergy of machine learning and mobile applications through Flutter. The benefits? A holistic understanding, positioning you ahead in the academic sphere and offering a competitive edge should you venture into research or further studies. Courses in this Data Science & Machine Learning bundle: Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 Data Science & Machine Learning with Python R Programming for Data Science Learn MySQL from Scratch for Data Science and Analytics SQL for Data Science, Data Analytics and Data Visualization Machine Learning Basics "Azure Machine Learning" Machine Learning use in Flutter, The Complete Guide Certificate of Achievement Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the Data Science & Machine Learning course as proof of their achievement. You can order the endorsed certificate for only £129 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this Data Science & Machine Learning course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the Data Science & Machine Learning course has been reviewed and approved by the QLS and meets the highest quality standards. CPD 180 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Data Science & Machine Learning bundle is ideal for: Aspiring Data Scientists. Statisticians looking to expand into Machine Learning. Developers keen on integrating Machine Learning in apps. Research scholars in data-driven fields. Requirements To enrol in this Data Science & Machine Learning course, all you need is a basic understanding of the English Language and an internet connection. Career path Data Scientist Machine Learning Engineer Data Analyst SQL Database Administrator Research Scientist (Data Specialization) Flutter Developer with ML Integration Certificates 8 CPD Accredited PDF Certificate Digital certificate - Included CPD Accredited Hard Copy Certificate Hard copy certificate - Included Delivery Charge: Inside the UK: £3.99 Outside the UK: £9.99 QLS Endorsed Hard Copy Certificate Hard copy certificate - Included Delivery Charge: Inside the UK: Free Outside the UK: £9.99 Other CPD Accredited Hard Copy Certificate Hard copy certificate - £9.99 Free Courses Hard Copy Certificates Are £9.99 Each. Delivery Charge: Inside the UK: Free Outside the UK: £9.99

About Course Master the statistical skills you need to understand and analyze biomedical research data with this Biostatistics Online Course Are you working on public health, clinical medicine, biology or related fields? Are you familiar with the process of obtaining an accurate picture from a large number of data points? This Biostatistics Online Course demonstrates how to use statistical techniques to summarize the characteristics of a data set to draw meaningful conclusions. In this course, you will learn all about Biostatistics and its application in medical and life sciences. This course is a comprehensive introduction to the field of biostatistics, covering a wide range of topics from basic statistical concepts to more advanced biostatistical methods.Biostatistics Online Course modules: Module 1: Introduction to Biostatistics This module provides an overview of biostatistics, its applications in the field of health sciences, and the different types of study designs used in biomedical research. It also introduces the basic concepts of statistics, including data types, variables, inferential statistics, hypothesis testing, and the role of statistics in biostatistics and evidence-based medicine. Module 2: Probability This module covers the basics of probability, including probability distributions, random variables, and sampling distributions. Students will learn how to calculate and interpret probabilities in the context of biomedical research. Module 3: Descriptive Statistics This module covers the different measures of central tendency and variability, as well as graphical representations of data. Students will learn how to describe and summarize data from biomedical studies using these methods. Module 4: Inferential Statistics This module covers the fundamental concepts of inferential statistics, including estimation, hypothesis testing, confidence intervals, and p-values. Students will learn how to use these methods to draw conclusions about populations based on data from samples. Module 5: Regression Analysis This module introduces the basics of regression analysis, including simple linear regression, multiple linear regression, and logistic regression. Students will learn how to use these methods to model relationships between variables and to make predictions. Module 6: Biostatistics Tools This module covers a variety of biostatistical tools that are commonly used in biomedical research, including survival analysis, clinical trials, and epidemiological studies. Students will learn how to use these tools to answer specific research questions. Module 7: Statistical Software and Tools This module introduces students to popular statistical software programs, such as R and SPSS. Students will learn how to import, manage, and analyze data using these software programs, as well as how to perform statistical tests and generate summary statistics. Module 8: Ethical Considerations and Reporting Guidelines This module covers the importance of ethical considerations in biostatistics and the reporting guidelines for statistical analysis in research publications. Students will also learn about best practices for data management and data sharing. Why You Should Take This Course Whether you are a student, researcher, or healthcare professional, biostatistics is an essential skill for understanding and interpreting biomedical research. This course provides a comprehensive and accessible introduction to the field of biostatistics, covering all the essential topics that you need to know. By taking this course, you will learn how to: Design and conduct biomedical studies Collect and manage data Analyze data using statistical methods Interpret statistical results Communicate statistical findings effectively This course is ideal for students in the fields of public health, medicine, nursing, epidemiology, and other health sciences. It is also beneficial for researchers, healthcare professionals, and anyone else who wants to learn more about biostatistics. Enroll today and start your journey to becoming a biostatistics expert! To find more course in this topic, search more . What Will You Learn? Design and conduct biomedical studies Collect and manage data Analyze data using statistical methods Interpret statistical results Communicate statistical findings effectively Course Content Introduction to Biostatistics Introduction to Biostatistics Probability Module 2 Probability Descriptive Statistics Descriptive Statistics Inferential Statistics Inferential Statistics Regression Analysis Regression Analysis Biostatistics Tools Biostatistics Tools Statistical Software and Tools Statistical Software and Tools Ethical Considerations and Reporting Guidelines Ethical Considerations and Reporting Guidelines A course by Xpert Learning RequirementsBasic understanding of Mathematics and Statistics Audience Students in health sciences Researchers Healthcare professionals Anyone interested in learning about biostatistics Audience Students in health sciences Researchers Healthcare professionals Anyone interested in learning about biostatistics

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***24 Hour Limited Time Flash Sale*** Data Science & Machine Learning, Excel Pivot & Machine Learning with Python Admission Gifts FREE PDF & Hard Copy Certificate| PDF Transcripts| FREE Student ID| Assessment| Lifetime Access| Enrolment Letter Immerse yourself in the world of Data Science, Machine Learning and Python with our exclusive bundle! Presenting eight thoughtfully curated courses, this bundle aims to enhance your understanding of intricate concepts. Within this collection, we proudly offer three QLS-endorsed courses: "2021 Data Science & Machine Learning with R from A-Z", "Excel Pivot Tables, Pivot Charts, Slicers, and Timelines", and "Machine Learning with Python", each complemented by a hardcopy certificate upon completion. Additionally, delve deeper with our five relevant CPD QS accredited courses. Explore Python Data Science with Numpy, Pandas, and Matplotlib. Uncover the secrets of R Programming for Data Science, enhance your statistical prowess with Statistics & Probability for Data Science & Machine Learning, and master spatial visualisation in Python. To top it all, there's a course on Google Data Studio for Data Analytics. Key Features of the Data Science & Machine Learning, Excel Pivot & Machine Learning with Python Bundle: 3 QLS-Endorsed Courses: We proudly offer 3 QLS-endorsed courses within our Data Science & Machine Learning, Excel Pivot & Machine Learning with Python bundle, providing you with industry-recognized qualifications. Plus, you'll receive a free hardcopy certificate for each of these courses. QLS Course 01: 2021 Data Science & Machine Learning with R from A-Z QLS Course 02: Excel Pivot Tables, Pivot Charts, Slicers, and Timelines QLS Course 03: Machine Learning with Python 5 CPD QS Accredited Courses: Additionally, our bundle includes 5 relevant CPD QS accredited courses, ensuring that you stay up-to-date with the latest industry standards and practices. Course 01: Python Data Science with Numpy, Pandas and Matplotlib Course 02: R Programming for Data Science Course 03: Statistics & Probability for Data Science & Machine Learning Course 04: Spatial Data Visualisation and Machine Learning in Python Course 05: Google Data Studio: Data Analytics In Addition, you'll get Five Career Boosting Courses absolutely FREE with this Bundle. Course 01: Professional CV Writing Course 02: Job Search Skills Course 03: Self-Esteem & Confidence Building Course 04: Professional Diploma in Stress Management Course 05: Complete Communication Skills Master Class Convenient Online Learning: Our Data Science & Machine Learning, Excel Pivot & Machine Learning with Python courses are accessible online, allowing you to learn at your own pace and from the comfort of your own home. Learning Outcomes: Master the usage of Excel Pivot Tables, Pivot Charts, Slicers, and Timelines. Develop proficiency in Machine Learning using Python. Acquire skills to manipulate data using Numpy, Pandas, and Matplotlib. Learn to code in R for Data Science applications. Understand the application of Statistics & Probability in Data Science & Machine Learning. Learn to create impactful data visualisations and analyse data using Google Data Studio. The "Data Science & Machine Learning, Excel Pivot & Machine Learning with Python" bundle is a comprehensive compilation designed to equip you with the theoretical knowledge necessary for the fast-evolving data-driven world. The three QLS-endorsed courses provide foundational understanding in Data Science, Machine Learning with R, Excel Pivot functionalities, and Machine Learning with Python, thereby setting a strong base. Furthermore, the five CPD QS accredited courses offer a deeper dive into the world of Data Science. Whether it is harnessing Python's power for data science tasks, exploring R programming, mastering statistical techniques, understanding spatial data visualisation in Python, or learning to navigate Google Data Studio for Data Analytics, this bundle has you covered. With this comprehensive learning experience, gain the theoretical insight needed to navigate and succeed in the dynamic field of data science. CPD 250 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Individuals interested in theoretical concepts of Data Science and Machine Learning. Professionals looking to enhance their knowledge in Excel Pivot Tables and Charts. Aspiring data scientists who want to learn Python and R programming for data science. Anyone seeking to understand data visualisation and analytics through Python and Google Data Studio. Career path Data Scientist: Leveraging data for actionable insights (£40,000 - £90,000 per annum). Machine Learning Engineer: Designing and implementing machine learning systems (£50,000 - £90,000 per annum). Excel Analyst: Using Excel for data analysis and visualisation (£30,000 - £60,000 per annum). Python Developer: Developing applications using Python (£40,000 - £80,000 per annum). Certificates Digital certificate Digital certificate - Included Hard copy certificate Hard copy certificate - Included