1113 Statistics courses delivered Online

In today's digital age, mastering the role of a Data Entry Administrator through an online training course is indispensable. The Data Entry Administrator Online Training Course equips individuals with the essential skills to navigate the intricacies of data entry efficiently. In a world reliant on data for decision-making, accuracy and speed are paramount, making proficiency in data entry indispensable across various industries. By grasping the fundamentals laid out in modules like Introduction to Data Entry and Utilizing Excel for Efficient Data Entry, individuals gain a comprehensive understanding of data management. This expertise significantly enhances employability prospects in the UK job market, where demand for Data Entry Administrators remains robust. According to recent surveys, the median salary for Data Entry Administrator positions in the UK stands at £20,000 per annum, highlighting the lucrative nature of this profession. Additionally, the advantages of this course extend beyond immediate job opportunities, with the sector witnessing a steady increase in demand, with a growth rate of approximately 5% annually. Mastering data entry through this course opens doors to a plethora of job opportunities while ensuring a competitive edge in today's dynamic job market. Key Features: CPD Certified Free Certificate from Reed CIQ Approved Developed by Specialist Lifetime Access Course Curriculum: Module 01: Introduction to Data Entry Module 02: Using the Computer for Data Entry Module 03: Common Rules and Guidelines for Data Entry Module 04: Using Excel for Efficient Data Entry Module 05: Using Excel's Flash Fill and Autofill to Automate Data Entry Module 06: How to Create a Data Entry Form in Excel? Module 07: Using Statistics Packages in Data Entry Learning Outcomes: Understand principles of efficient data entry and its importance. Utilise Excel's Flash Fill and Autofill for automated data entry. Create effective data entry forms using Excel's functionalities. Implement common rules and guidelines for accurate data entry. Apply statistics packages effectively for advanced data entry tasks. Enhance data entry efficiency using computer and Excel tools. CPD 10 CPD hours / points Accredited by CPD Quality Standards Data Entry Administrator Online Training 55:57 1: Module 01: Introduction to Data Entry Preview 05:06 2: Module 02: Using the Computer for Data Entry 02:56 3: Module 03: Common Rules and Guidelines for Data Entry 11:12 4: Module 04: Using Excel for Efficient Data Entry 04:43 5: Module 05: Using Excel's Flash Fill and Autofill to Automate Data Entry 05:51 6: Module 06: How to Create a Data Entry Form in Excel? 12:38 7: Module 07: Using Statistics Packages in Data Entry 11:31 8: CPD Certificate - Free 01:00 9: Leave A Review 01:00 Who is this course for? This Data Entry Administrator Online Training course is accessible to anyone eager to learn more about this topic. Through this course, you'll gain a solid understanding of Data Entry Administrator Online Training. Moreover, this course is ideal for: Individuals seeking foundational data entry skills. Office assistants aiming to improve data handling proficiency. Students pursuing careers in administrative roles. Professionals transitioning to data entry positions. Anyone interested in mastering Excel for data management. Requirements There are no requirements needed to enrol into this Data Entry Administrator Online Training course. We welcome individuals from all backgrounds and levels of experience to enrol into this Data Entry Administrator Online Training course. Career path After finishing this Data Entry Administrator Online Training course you will have multiple job opportunities waiting for you. Some of the following Job sectors of Data Entry Administrator Online Training are: Data Entry Clerk - £18K to 25K/year. Administrative Assistant - £18K to 30K/year. Data Analyst - £24K to 35K/year. Office Manager - £22K to 40K/year. Research Assistant - £20K to 30K/year. Certificates Digital certificate Digital certificate - Included Reed Courses Certificate of Completion Digital certificate - Included Will be downloadable when all lectures have been completed.

Unlock your potential as a Business Intelligence Analyst! Master data analysis, reporting, and visualisation skills to drive informed business decisions.

Duration 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm

In simple terms, Forex trading is a trading option for currency, where you buy one currency for a given price and sell it for more money when the exchange rate is in your favour. If you want to learn more about how the process works then consider getting this course. By getting an introductory understanding of both basics of stock market & forex trading, you will learn about stock market trends, understand currency conversion, statistics, forex volatility and market expectation. You will also discover more about aspects of trade, risk management, and trading options. Next part focuses on a variety of topics including forex pairs, market size, liquidity, spot marketing, futures trading and more. Entry Requirement This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Assessment:  At the end of the course, you will be required to sit an online multiple-choice test. Your test will be assessed automatically and immediately so that you will instantly know whether you have been successful. Before sitting for your final exam you will have the opportunity to test your proficiency with a mock exam. Certification: After you have successfully passed the test, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. PDF certificate's turnaround time is 24 hours and for the hardcopy certificate, it is 3-9 working Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market. Stock Market Basics Introduction To Stocks Basics 00:30:00 About Share Basics 00:30:00 The Difference Between Stocks And Shares 00:30:00 Concept Of Fundamentals Of The Stock Market 00:30:00 How Exactly Do Stock Prices Get Determined? 00:30:00 Benefits Of Using Stocks And Shares 01:00:00 When To Get Out Of The Stock Market 00:30:00 Wrapping Up 00:15:00 Stock Market Statistics Understanding the stock market 01:00:00 Identifying trends 01:00:00 What is Forex? 01:00:00 Basics of currency conversion 01:00:00 Understanding Statistics 01:00:00 Forex Volatility And Market Expectation 01:00:00 Aspects Of The Trade 01:00:00 Risk Management 01:00:00 'Buzz' Words 01:00:00 Expert Trading Options 01:00:00 Other Trading Options 01:00:00 In Review 01:00:00 One Final Option 00:30:00 Forex Trading Simplified What Is Forex? 00:30:00 About The New York Stock Exchange 00:30:00 What Is Trading? 00:30:00 What Are Forex Pairs? 00:30:00 About The Market Size And Liquidity 00:30:00 What is A Spot Market? 01:00:00 What Is Futures Trading? 00:30:00 What are Options Trading? 00:30:00 What Are Exchange-traded Funds? 00:30:00 The Dangers Of Trading If You Don't Know How to Cope with It 00:30:00 Practical Forex Trading How a Forex system operates in real time? 00:30:00 The secret to success in forex trading 00:15:00 What is a Spot Market? 00:15:00 How Do You Make Money Trading Forex? 00:30:00 Know Your P's and L's 00:30:00 Opening a Trading Account 00:15:00 Types of Trading 00:15:00 Mock Exam Mock Exam- Stock Market and Forex Trading Diploma 00:20:00 Final Exam Final Exam - Stock Market and Forex Trading Diploma 00:20:00 Order Your Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Lean Six Sigma Black Belt Certification Program: Virtual In-House Training This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners. If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others. Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course. What you Will Learn At the end of this program, you will be able to: Use Minitab for advanced data analysis Develop appropriate sampling strategies Analyze differences between samples using Hypothesis Tests Apply Statistical Process Control to differentiate common cause and special cause variation Explain and apply various process capability metrics Conduct Measurement System Analysis and Gage R&R studies for both discrete and continuous data Conduct and analyze simple and multiple regression analysis Plan, execute, and analyze designed experiments Drive sustainable change efforts through leadership, change management, and stakeholder management Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps Explain the main concepts of Design for Six Sigma including QFD Introduction: DMAIC Review IIL Black Belt Certification Requirements Review Project Selection Review Define Review Measure Review Analyze Review Improve Review Control Introduction: Minitab Tool Introduction to Minitab Minitab basic statistics and graphs Special features Overview of Minitab menus Introduction: Sampling The Central Limit Theorem Confidence Interval of the mean Sample size for continuous data (mean) Confidence Interval for proportions Sample size for discrete data (proportions) Sampling strategies (review) Appendix: CI and sample size for confidence levels other than 95% Hypothesis Testing: Introduction Why use advanced stat tools? What are hypothesis tests? The seven steps of hypothesis tests P value errors and hypothesis tests Hypothesis Testing: Tests for Averages 1 factor ANOVA and ANOM Main Effect Plots, Interaction Plots, and Multi-Vari Charts 2 factor ANOVA and ANOM Hypothesis Testing: Tests for Standard Deviations Testing for equal variance Testing for normality Choosing the right hypothesis test Hypothesis Testing: Chi Square and Other Hypothesis Test Chi-square test for 1 factor ANOM test for 1 factor Chi-square test for 2 factors Exercise hypothesis tests - shipping Non-parametric tests Analysis: Advanced Control Charts Review of Common Cause and Special Cause Variation Review of the Individuals Control Charts How to calculate Control Limits Four additional tests for Special Causes Control Limits after Process Change Discrete Data Control Charts Control Charts for Discrete Proportion Data Control Charts for Discrete Count Data Control Charts for High Volume Processes with Continuous Data Analysis: Non-Normal Data Test for normal distribution Box-Cox Transformation Box-Cox Transformation for Individuals Control Charts Analysis: Time Series Analysis Introduction to Time Series Analysis Decomposition Smoothing: Moving Average Smoothing: EWMA Analysis: Process Capability Process capability Discrete Data: Defect metrics Discrete Data: Yield metrics Process Capability for Continuous Data: Sigma Value Short- and long-term capabilities Cp, Cpk, Pp, Ppk capability indices Analysis: Measurement System Analysis What is Measurement System Analysis? What defines a good measurement system? Gage R&R Studies Attribute / Discrete Gage R&R Continuous Gage R&R Regression Analysis: Simple Correlation Correlation Coefficient Simple linear regression Checking the fit of the Regression Model Leverage and influence analysis Correlation and regression pitfalls Regression Analysis: Multiple Regression Analysis Introduction to Multiple Regression Multicollinearity Multiple Regression vs. Simple Linear Regression Regression Analysis: Multiple Regression Analysis with Discrete Xs Introduction Creating indicator variables Method 1: Going straight to the intercepts Method 2: Testing for differences in intercepts Logistic Regression: Logistic Regression Introduction to Logistic Regression Logistic Regression - Adding a Discrete X Design of Experiments: Introduction Design of Experiment OFAT experimentation Full factorial design Fractional factorial design DOE road map, hints, and suggestions Design of Experiments: Full Factorial Designs Creating 2k Full Factorial designs in Minitab Randomization Replicates and repetitions Analysis of results: Factorial plots Analysis of results: Factorial design Analysis of results: Fits and Residuals Analysis of results: Response Optimizer Analysis of results: Review Design of Experiments: Pragmatic Approaches Designs with no replication Fractional factorial designs Screening Design of Experiment Case Study Repair Time Blocking Closing: Organizational Change Management Organizational change management Assuring project sponsorship Emphasizing shared need for change Mobilizing stakeholder commitment Closing: Project Management for Lean Six Sigma Introduction to project management Project management for Lean Six Sigma The project baseline plan Work Breakdown Structure (WBS) Resource planning Project budget Project risk Project schedule Project executing Project monitoring and controlling and Closing Closing: Design for Lean Six Sigma Introduction to Design for Lean Six Sigma (DMADV) Introduction to Quality Function Deployment (QFD) Summary and Next Steps IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)

This course begins with establishing the motivation for reinforcement learning and then progresses on to equipping you with all the necessary theory. Each section of the course helps you not only understand the fundamentals of RL but also gain necessary coding skills by taking you through exercises. By the end of the course, you will be able to complete a project using the OpenAI Gym toolkit.

Embark on a transformative journey into data analytics with our comprehensive course. Discover the power of data & analytics through engaging modules designed to equip you with skills and knowledge. Whether you're a novice or a seasoned professional, this data analytics course is your gateway to unlocking the potential of big data analytics. From understanding the basics like what is data analytics and harnessing the power of statistics to mastering data visualisation tools, each step is crafted to empower you with the tools necessary to navigate the world of data analytics confidently. With the Google Data Analytics Professional Certificate, you'll gain invaluable insights and practical experience that can catapult you into lucrative data analytics jobs. From enhancing your employability to boosting your earning potential, this course opens doors to a myriad of opportunities in this field. Learning Outcomes: Acquire a solid foundation in data analytics principles and techniques. Develop proficiency in using various data analytics tools and software. Gain skills in data mining, storage, and visualisation. Cultivate a data-analytic mindset to tackle complex problems effectively. Explore career pathways in data science with confidence and clarity. Why buy this Data Analytics Course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Certification After studying the course materials of the Data Analytics there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this Data Analytics course for? Aspiring data analysts seeking to kickstart their careers. Professionals looking to enhance their skillset in this field. Students interested in exploring the fascinating world of data science. Entrepreneurs aiming to leverage analytics for business growth. Individuals seeking to transition into lucrative data analytics jobs. Prerequisites This Data Analytics does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Data Analytics was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path Data Analyst: £25,000 - £50,000 Per Annum Data Scientist: £30,000 - £70,000 Per Annum Business Intelligence Analyst: £28,000 - £55,000 Per Annum Data Engineer: £35,000 - £65,000 Per Annum Database Administrator: £25,000 - £55,000 Per Annum Analytics Manager: £40,000 - £80,000 Per Annum Course Curriculum Module 01: Introduction to the World of Data Introduction to the World of Data 01:00:00 Module 02: Basics of Data Analytics Basics of Data Analytics 00:40:00 Module 03: Statistics for Data Analytics Statistics for Data Analytics 01:00:00 Module 04: Actions Taken in the Data Analysis Process Actions Taken in the Data Analysis Process 00:55:00 Module 05: Gathering the Right Information Gathering the Right Information 01:00:00 Module 06: Storing Data Storing Data 01:15:00 Module 07: Data Mining Data Mining 01:00:00 Module 08: Excel for Data Analytics Excel for Data Analytics 01:20:00 Module 09: Tools for Data Analytics Tools for Data Analytics 01:20:00 Module 10: Data-Analytic Thinking Data-Analytic Thinking 01:10:00 Module 11: Data Visualisation That Clearly Describes Insights Data Visualisation That Clearly Describes Insights 00:45:00 Module 12: Data Visualisation Tools Data Visualisation Tools 01:00:00 Assignment Assignment - Data Analytics 00:00:00

***24 Hour Limited Time Flash Sale*** Basics of Data Science - CPD Certified Admission Gifts FREE PDF & Hard Copy Certificate| PDF Transcripts| FREE Student ID| Assessment| Lifetime Access| Enrolment Letter In a world where 2.5 quintillion bytes of data are produced every day, how can professionals leverage this data for strategic decision-making and competitive advantage? In the UK, the data science industry is booming, with an estimated increase in demand for data scientists and analytics professionals by over 28% by 2020. This Basics of Data Science bundle gives you diverse analytical skills to launch or advance your analytics career. Designed to cater to the needs of both seasoned professionals and aspiring newcomers, our Basics of Data Science bundle is a comprehensive program that will equip you with the essential skills and knowledge you need to succeed. Whether you're looking to advance in your current role or embark on a new career journey, this bundle has everything you need to take your professional life to the next level. But that's not all. When you enrol in Basics of Data Science Online Training, you'll receive 30 CPD-Accredited PDF Certificates, Hard Copy Certificates, and our exclusive student ID card, all absolutely free. Courses Are Included In this Bundle: Course 01: Diploma in Data Analysis Fundamentals Course 02: Business Intelligence and Data Mining Course 03: Google Data Studio: Data Analytics Course 04: Statistics Course 05: Statistical Analysis Course 06: Statistics & Probability for Data Science & Machine Learning Course 07: Microsoft Power BI - Master Power BI in 90 Minutes! 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And with 24/7 tutor support, you'll never feel alone in your journey, whether you're a seasoned professional or a beginner. Learning Outcomes of this Bundle Collect, clean, and transform complex datasets using Python and R Create insightful dashboards and visualizations in Power BI Apply statistical techniques to interpret trends and make predictions Build financial models to determine business value and opportunity Automate analytical tasks through SAS and JavaScript Communicate data-driven insights to stakeholders effectively Don't let this opportunity pass you by. Enrol in the Basics of Data Science today and take the first step towards achieving your goals and dreams. Why buy this Bundle? 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Data Analyst Business Analyst Data Scientist Marketing Analyst Financial Analyst Certificates CPD Accredited Digital certificate Digital certificate - Included CPD Accredited Hard copy certificate Hard copy certificate - Included If you are an international student, then you have to pay an additional 10 GBP for each certificate as an international delivery charge.

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Overview For the definitive and certified training in Human Resources, take this training and drive your company to its full potential. This comprehensive course offers an in-depth overview of all the factors and practices that control and influence HR in an organisation. The HR Practice Essentials Level 4 course delivers a masterclass in HR principles and will swiftly enable you to become a skilled practitioner in the area. You will be taught how to capture and analyse essential performance statistics. Additionally, you will learn how to support change, recruit staff, reward employees, manage business relations, organise training, and all the other duties that an HR manager will uphold. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is this course for? There is no experience or previous qualifications required for enrolment on this HR Practice Essentials Level 4. It is available to all students, of all academic backgrounds. Requirements Our HR Practice Essentials Level 4 is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible on tablets and smartphones so you can access your course on wifi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management , Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 14 sections • 14 lectures • 04:21:00 total length •Module 01: Introduction to Human Resource: 00:17:00 •Module 2: Employee Recruitment and Selection Procedure: 00:32:00 •Module 3: Skills of an Effective Administrator: 00:17:00 •Module 4: Employee Training and Development Process: 00:22:00 •Module 5: Performance Appraisal Management: 00:19:00 •Module 6: Employee Relations: 00:14:00 •Module 7: Motivation and Counselling: 00:19:00 •Module 8: Ensuring Health and safety at the Workplace: 00:17:00 •Module 9: Employee Termination: 00:15:00 •Module 10: Business Etiquette: 00:21:00 •Module 11: Employer Record and Statistics: 00:11:00 •Module 12: Business Telephone Skills: 00:21:00 •Module 13: Representing Your Boss and Company: 00:36:00 •Assignment - HR Practice Essentials Level 4: 00:00:00