1053 Courses in Glasgow delivered Online

Overview From agriculture to urban planning, remote sensing technologies are used in a wide range of areas. Thus, learning about these technologies can be highly beneficial for your career progression. Our Remote Sensing Technology Essentials course can help you explore the vital areas of remote sensing technologies. The course will provide you with an overall understanding of remote sensing technology. Here, each module will provide you with valuable information and help you broaden your knowledge. The course will include lessons on the electromagnetic spectrum, characteristics and specifications of sensors and more. You will also gain a solid understanding of image interpretation and data analysis. Finally, the course will describe the applications of remote sensing in the UK. Along with the valuable information, you will also receive a certificate of achievement. This CPDQS-accredited certificate will open new doors of career opportunities in the relevant fields enrol now! Course Preview Learning Outcomes Get introduced to the basics of remote sensing Understanding the principles of the electromagnetic spectrum Learn about the characteristics and specifications of sensor Enhance your knowledge of image interpretation and data analysis Familiarise yourself with the applications of remote sensing in the UK Why Take This Course From John Academy? Affordable, well-structured and high-quality e-learning study materials Engaging tutorial videos, materials from the industry-leading experts Opportunity to study in a user-friendly, advanced online learning platform Efficient exam systems for the assessment and instant result Earn UK & internationally recognised accredited qualification Easily access the course content on mobile, tablet, or desktop from anywhere, anytime Excellent career advancement opportunities Get 24/7 student support via email. What Skills Will You Learn from This Course? Remote sensing data analysis Image interpretation Who Should Take This Remote Sensing Technology Essentials? Whether you're an existing practitioner or an aspiring professional, this course is an ideal training opportunity. It will elevate your expertise and boost your CV with key skills and a recognised qualification attesting to your knowledge. Are There Any Entry Requirements? This Remote Sensing Technology Essentials course is available to all learners of all academic backgrounds. But learners should be aged 16 or over to undertake the qualification. And a good understanding of the English language, numeracy, and ICT will be helpful. Certificate of Achievement After completing this course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates & Transcripts can be obtained either in Hardcopy at £14.99 or in PDF format at £11.99. Career Path​ This exclusive Remote Sensing Technology Essentials course will equip you with effective skills and abilities and help you explore career paths such as  Remote Sensing Technician Remote Sensing Researcher Remote Sensing Data Analyst Consultant Module 01: Introduction to Remote Sensing Introduction to Remote Sensing 00:18:00 Module 02: Electromagnetic Spectrum and Remote Sensing Electromagnetic Spectrum and Remote Sensing 00:18:00 Module 03: Platforms and Sensors Platforms and Sensors 00:19:00 Module 04: Image Interpretation Image Interpretation 00:18:00 Module 05: Remote Sensing Data Analysis Remote Sensing Data Analysis 00:21:00 Module 06: Applications of Remote Sensing in the UK Applications of Remote Sensing in the UK 00:17:00 Module 07: Future Trends in Remote Sensing Future Trends in Remote Sensing 00:18:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Gain a thorough grasp of time series analysis and its effects, as well as practical tips on how to apply machine learning methods and build RNNs. Learn to train RNNs efficiently while taking crucial concepts such as overfitting and underfitting into account. The course offers a useful, hands-on manner for learning Python methods and principles.

If you aim to enhance your Data Engineering skills, our comprehensive Data Engineering course is perfect for you. Designed for success, this Data Engineering course covers everything from basics to advanced topics in Data Engineering. Each lesson in this Data Engineering course is crafted for easy understanding, enabling you to become proficient in Data Engineering. Whether you are a beginner or looking to sharpen your existing skills, this Data Engineering is the ideal choice. With our Data Engineering exclusive bundle, you will get a PDF Certificate, PDF Transcript and Digital Student ID Card (worth £50) Absolutely FREE. Courses are Included in This Data Engineering Bundle: Course 01: Diploma in Data Analysis Fundamentals Course 02: Python for Data Analysis Course 03: Data Analytics with Tableau Course 04: SQL Masterclass: SQL For Data Analytics Course 05: Basic Google Data Studio Course 06: Data Analysis and Forecasting in Excel Why Choose Our Data Engineering Course? FREE Data Engineering certificate accredited Get a free student ID card with Data Engineering Training Get instant access to this Data Engineering course. Learn Data Engineering from anywhere in the world The Data Engineering is affordable and simple to understand The Data Engineering is an entirely online, interactive lesson with voiceover audio Lifetime access to the Data Engineering course materials The Data Engineering comes with 24/7 tutor support So enrol now in this Data Engineering Today to advance your career! Start your learning journey straightaway! This Data Engineering's curriculum has been designed by Data Engineering experts with years of Data Engineering experience behind them. The Data Engineering course is extremely dynamic and well-paced to help you understand Data Engineering with ease. You'll discover how to master the Data Engineering skill while exploring relevant and essential topics. Assessment Process Once you have completed all the courses in the Data Engineering bundle, you can assess your skills and knowledge with an optional assignment. Our expert trainers will assess your assignment and give you feedback afterwards. CPD 60 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Data Engineering bundle is suitable for everyone. Requirements You will not need any prior background or expertise. Career path This Data Engineering bundle will allow you to kickstart or take your career in the related sector to the next stage. Certificates CPD Accredited Digital certificate Digital certificate - Included CPD Accredited Hard copy certificate Hard copy certificate - £29 If you are an international student, you will be required to pay an additional fee of 10 GBP for international delivery, and 4.99 GBP for delivery within the UK, for each certificate

Business Intelligence: In-House Training Business Intelligence (BI) refers to a set of technology-based techniques, applications, and practices used to aggregate, analyze, and present business data. BI practices provide historical and current views of vast amounts of data and generate predictions for business operations. The purpose of Business Intelligence is the support of better business decision making. This course provides an overview of the technology and application of BI and how it can be used to improve corporate performance. What you will Learn You will learn how to: Specify a data warehouse schema Identify the data and visualization to be used for data mining and Business Intelligence Design a Business Intelligence user interface Getting Started Introductions Agenda Expectations Foundation Concepts The challenge of decision making What is Business Intelligence? The Business Intelligence value proposition Business Intelligence taxonomy Business Intelligence management issues Sources of Business Intelligence Data warehousing Data and information Information architecture Defining the data warehouse and its relationships Facts and dimensions Modeling, meta-modeling, and schemas Alternate architectures Building the data warehouse Extracting Transforming Loading Setting up the data and relationships Dimensions and the Fact Table Implementing many-to-many relationships in data warehouse Data marts Online Analytical Processing (OLAP) What is OLAP? OLAP and OLTP OLAP functionality Multi-dimensions Thinking in more than two dimensions What are the possibilities? OLAP architecture Cubism Tools OLAP variations - MOLAP, ROLAP, HOLAP BI using SOA Applications of Business Intelligence Applying BI through OLAP Enterprise Resource Planning and CRM Business Intelligence and financial information Business Intelligence User Interfaces and Presentations Data access Push-pull data access Types of decision support systems Designing the front end Presentation formats Dashboards Types of dashboards Common dashboard features Briefing books and scorecards Querying and Reporting Reporting emphasis Retrofitting Talking back Key Performance Indicators Report Definition and Visualization Typical reporting environment Forms of visualization Unconstrained views Data mining What is in the mine? Applications for data mining Data mining architecture Cross Industry Standard Process for Data Mining (CISP-DM) Data mining techniques Validation The Business Intelligence User Experience The business analyst role Business analysis and data analysis Five-step approach Cultural impact Identifying questions Gathering information Understand the goals The strategic Business Intelligence cycle Focus of Business Intelligence Design for the user Iterate the access Iterative solution development process Review and validation questions Basic approaches Building ad-hoc queries Building on-demand self-service reports Closed loop Business Intelligence Coming attractions - future of Business Intelligence Best practices in Business Intelligence

>> 12-Hour Knowledge Knockdown! Prices Reduced Like Never Before << In the era of big data, the demand for skilled data science professionals has skyrocketed in the UK. According to a recent report, the data science job market in the UK is expected to grow by over 25% by 2026. Aside from that, Candidates with data science skills have a 96% employment rate and can earn on average £40,000 per year. Our Complete Data Science bundle is about to take you on a tour starting from the beginning. This CCTV Operator Training Bundle Contains 4 of Our Premium Courses for One Discounted Price: Course 01: Complete Data Science Course 02: Data Science with Python Course 03: Information Management Course 04: GDPR Data Protection Take our Complete Data Science Bundle to learn how to maximise your potential and climb your chosen professional ladder. By participating in these popular courses, you can learn the fundamentals of Python. Discover Python data types. Loops, list comprehension, functions, lambda expressions, maps, and filters should all be taught. Learn about the numpy. Indexing, slicing, broadcasting, and boolean masking are all covered in our Complete Data Science course. Recognise arithmetic and universal functions. Discover everything there is to know about pandas. Learn how to use Python to become an expert in data analysis and visualisation. Learning Outcomes of Data Science Develop a comprehensive understanding of the data science lifecycle. Master data analysis techniques and Python programming for data manipulation. Gain proficiency in information management and data organization strategies. Understand data protection regulations, including GDPR, and their implications. Learn to build robust data-driven applications and predictive models. Enhance data visualization skills for effective communication of insights. Invest in your future by enrolling today and gain a competitive edge in the rapidly evolving field of data science. Why Choose Our Data Science bund;e? Get a Free CPD Accredited Certificate upon completion of Data Science Get a free student ID card with Data Science Training The Data Science is affordable and simple to understand Lifetime access to the Data Science course materials The Data Science comes with 24/7 tutor support Start your learning journey straightaway! *** Course Curriculum *** Course 01: Complete Data Science Welcome, Course Introduction & overview, and Environment set-up Python Essentials Python for Data Analysis using NumPy Python for Data Analysis using Pandas Python for Data Visualization using matplotlib Python for Data Visualization using Seaborn Python for Data Visualization using pandas Python for interactive & geographical plotting using Plotly and Cufflinks Capstone Project - Python for Data Analysis & Visualization Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Python for Machine Learning - scikit-learn - Logistic Regression Model Python for Machine Learning - scikit-learn - K Nearest Neighbors Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Python for Machine Learning - scikit-learn - Support Vector Machines (SVMs) Python for Machine Learning - scikit-learn - K Means Clustering Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Recommender Systems - (Additional Topic) Natural Language Processing (NLP) - NLTK - (Additional Topic) Course 02: Data Science with Python Unit 01: Introduction To Python Data Science Unit 02: Data Cleaning Packages Unit 03: Data Visualization Packages Course 03: Information Management Module 01: Introduction To Information Management Module 02: Information Management Strategy Module 03: Databases And Information Management Module 04: Management Information Systems (MIS) Module 05: Auditing Information Systems Module 06: Ethical And Social Issues And Data Protection Course 04: GDPR Data Protection Module 01: Basics Of GDPR Module 02: Principles Of GDPR Module 03: Legal Foundation For Processing Module 04: Rights Of Individuals Module 05: Accountability And Governance Module 06: Data Protection Officer Module 07: Security Of Data Module 08: Personal Data Breaches Module 09: International Data Transfers After The Brexit Module 10: Exemptions - Part One and much more... How will I get my Certificate? After successfully completing the course, you will be able to order your Certificates as proof of your achievement. PDF Certificate: Free (Previously it was £12.99*4 = £51) CPD Hard Copy Certificate: £29.99 (Each) CPD 40 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Data Science bundle is suitable for everyone. This bundle is ideal for: Data scientist Data analyst-statistician CSE Students Interns App Developer Coders' Requirements You will not need any prior background or expertise to enrol in this Data Science bundle. Career path This Data Science Training bundle will allow you to kickstart or take your career in the related sector to the next stage. Data Analyst Data Scientist Business Analyst Marketing Analyst Data Engineer Certificates CPD Accredited Digital Certificate Digital certificate - Included Upon passing the Course, you need to order a Digital Certificate for each of the courses inside this bundle as proof of your new skills that are accredited by CPD QS for Free. CPD Accredited Hard Copy Certificate Hard copy certificate - £29 Please note that International students have to pay an additional £10 as a shipment fee.

Learn Python programming by developing robust GUIs and games

Lean Six Sigma Black Belt Certification Program: 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)

Project Quality Management: Virtual In-House Training In today's environment, quality is the responsibility of everyone. Project success is no longer just the fulfillment of a project on schedule, on budget, and within the scope. Today, projects aren't successful unless the customer's needs are met at the highest level of quality at the lowest cost to the organization. Project Managers must know customer needs, and manage to them throughout the project lifecycle, in order to gain acceptance. Project Quality Management provides an interactive, hands-on environment for participants to practice identification of critical quality requirements (quality planning), fulfillment of those requirements through well-designed processes (Quality Assurance), and statistical awareness of technical specifications of project deliverables (Quality Control). What You Will Learn You'll learn how to: Plan for higher quality project deliverables Measure key performance indicators on projects, processes, and products Turn data into useful project information Take action on analyzed data that will drive down non-value-added costs and drive up customer acceptance and satisfaction Reduce defects and waste in current project management processes Foundation Concepts Quality Defined Customer Focus Financial Focus Quality Management Process Management Cost of Quality Planning for Quality Project Manager Role in Planning Voice of the Customer Quality Management Plan Measurement System Accuracy Data Gathering Data Sampling Manage Quality Process Management Process Mapping Process Analysis Value Stream Mapping Standardization Visual Workplace and 5S Error Proofing (Poka-Yoke) Failure Mode and Effect Analysis Control Quality The Concept of Variation Common Cause Special Cause Standard Business Reports Tracking Key Measurements Control Charts Data Analysis Variation Root Cause Analysis Variance Management Designing for Quality

Duration 3 Days 18 CPD hours This course is intended for Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform Overview This course teaches students the following skills: Derive insights from data using the analysis and visualization tools on Google Cloud Platform Interactively query datasets using Google BigQuery Load, clean, and transform data at scale Visualize data using Google Data Studio and other third-party platforms Distinguish between exploratory and explanatory analytics and when to use each approach Explore new datasets and uncover hidden insights quickly and effectively Optimizing data models and queries for price and performance Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course! This four-course accelerated online specialization teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The courses feature interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The courses also cover data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization. This specialization is intended for the following participants: Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform To get the most out of this specialization, we recommend participants have some proficiency with ANSI SQL. Introduction to Data on the Google Cloud Platform Highlight Analytics Challenges Faced by Data Analysts Compare Big Data On-Premises vs on the Cloud Learn from Real-World Use Cases of Companies Transformed through Analytics on the Cloud Navigate Google Cloud Platform Project Basics Lab: Getting started with Google Cloud Platform Big Data Tools Overview Walkthrough Data Analyst Tasks, Challenges, and Introduce Google Cloud Platform Data Tools Demo: Analyze 10 Billion Records with Google BigQuery Explore 9 Fundamental Google BigQuery Features Compare GCP Tools for Analysts, Data Scientists, and Data Engineers Lab: Exploring Datasets with Google BigQuery Exploring your Data with SQL Compare Common Data Exploration Techniques Learn How to Code High Quality Standard SQL Explore Google BigQuery Public Datasets Visualization Preview: Google Data Studio Lab: Troubleshoot Common SQL Errors Google BigQuery Pricing Walkthrough of a BigQuery Job Calculate BigQuery Pricing: Storage, Querying, and Streaming Costs Optimize Queries for Cost Lab: Calculate Google BigQuery Pricing Cleaning and Transforming your Data Examine the 5 Principles of Dataset Integrity Characterize Dataset Shape and Skew Clean and Transform Data using SQL Clean and Transform Data using a new UI: Introducing Cloud Dataprep Lab: Explore and Shape Data with Cloud Dataprep Storing and Exporting Data Compare Permanent vs Temporary Tables Save and Export Query Results Performance Preview: Query Cache Lab: Creating new Permanent Tables Ingesting New Datasets into Google BigQuery Query from External Data Sources Avoid Data Ingesting Pitfalls Ingest New Data into Permanent Tables Discuss Streaming Inserts Lab: Ingesting and Querying New Datasets Data Visualization Overview of Data Visualization Principles Exploratory vs Explanatory Analysis Approaches Demo: Google Data Studio UI Connect Google Data Studio to Google BigQuery Lab: Exploring a Dataset in Google Data Studio Joining and Merging Datasets Merge Historical Data Tables with UNION Introduce Table Wildcards for Easy Merges Review Data Schemas: Linking Data Across Multiple Tables Walkthrough JOIN Examples and Pitfalls Lab: Join and Union Data from Multiple Tables Advanced Functions and Clauses Review SQL Case Statements Introduce Analytical Window Functions Safeguard Data with One-Way Field Encryption Discuss Effective Sub-query and CTE design Compare SQL and Javascript UDFs Lab: Deriving Insights with Advanced SQL Functions Schema Design and Nested Data Structures Compare Google BigQuery vs Traditional RDBMS Data Architecture Normalization vs Denormalization: Performance Tradeoffs Schema Review: The Good, The Bad, and The Ugly Arrays and Nested Data in Google BigQuery Lab: Querying Nested and Repeated Data More Visualization with Google Data Studio Create Case Statements and Calculated Fields Avoid Performance Pitfalls with Cache considerations Share Dashboards and Discuss Data Access considerations Optimizing for Performance Avoid Google BigQuery Performance Pitfalls Prevent Hotspots in your Data Diagnose Performance Issues with the Query Explanation map Lab: Optimizing and Troubleshooting Query Performance Advanced Insights Introducing Cloud Datalab Cloud Datalab Notebooks and Cells Benefits of Cloud Datalab Data Access Compare IAM and BigQuery Dataset Roles Avoid Access Pitfalls Review Members, Roles, Organizations, Account Administration, and Service Accounts

24 Hours Left! Don't Let the Winter Deals Slip Away - Enrol Now in this Data Analyst Course! Unlock the power of Data Analysis and become a master of insights with our Data Analyst (Data Analytics) course. Gain the Data Analyst skills to decipher complex datasets, extract valuable information, and make data-driven decisions that drive success as a Data Analyst. Join us on this Data Analyst (Data Analytics) course and embark on a journey to transform raw data into actionable intelligence, empowering businesses to thrive in the digital age with Data Analyst (Data Analytics) Courses Included in This Data Analyst (Data Analytics) Training: Course 01: Diploma in Data Analysis at QLS Level 5 Course 02: Diploma in Business Data Analysis at QLS Level 5 Course 03: SQL Masterclass: SQL For Data Analytics Learning outcome of this Data Analyst (Data Analytics) course: Master retail Data analytics for data-driven decisions. Uncover consumer behavior with retail psychology. Enhance retail performance through data analytics. Apply data-driven strategies for retail planning. Optimise inventory and product assortment in retail. Why Prefer This Data Analysis at QLS Level 5 Course? Opportunity to earn a certificate endorsed by the Quality Licence Scheme. Get a free student ID card! (£10 postal charge will be applicable for international delivery) Get instant access to this Data Analyst (Data Analytics) course. Learn Data Analyst (Data Analytics) from anywhere in the world Data Analyst (Data Analytics) is affordable and simple to understand Data Analyst (Data Analytics) is entirely online, interactive lesson with voiceover audio Lifetime access to the Data Analyst (Data Analytics) course materials Data Analyst (Data Analytics) comes with 24/7 tutor support Start your learning journey straight away with this Data Analyst (Data Analytics) course and take a step toward a brighter future! Why Prefer This Data Analyst (Data Analytics) Course? FREE certificate on Data Analyst (Data Analytics) accredited by CPDQS Get instant access to this Data Analyst (Data Analytics) course. Learn Data Analyst (Data Analytics) from anywhere in the world Data Analyst (Data Analytics) is affordable and simple to understand Data Analyst (Data Analytics) is entirely online, interactive lesson with voiceover audio Lifetime Access to the Data Analyst (Data Analytics) course materials Data Analyst (Data Analytics) comes with Data Analysis Assessment Process of Data Analyst(Data Analytics) QLS Course: Assignment & MCQ Based 60% Marks to pass Instant Assessment Certificate of Data Analyst QLS Endorsed Certificate (additional cost) CPD Approved Certificate CPD 150 CPD hours / points Accredited by CPD Quality Standards Course 01- Data Analysis: Modifying a Worksheet 25:59 1: Insert, Delete, and Adjust Cells, Columns, and Rows Preview 10:08 2: Search for and Replace Data 08:38 3: Use Proofing and Research Tools 07:13 Working with Lists 37:47 4: Sort Data 10:03 5: Filter Data 09:49 6: Query Data with Database Functions 09:02 7: Outline and Subtotal Data 08:53 Analyzing Data 12:33 8: Apply Intermediate Conditional Formatting 06:50 9: Apply Advanced Conditional Formatting 05:43 Visualizing Data with Charts 38:03 10: Create Charts 13:18 11: Modify and Format Charts 12:16 12: Use Advanced Chart Features 12:29 Using PivotTables and PivotCharts 44:25 13: Create a PivotTable 13:28 14: Analyze PivotTable Data 12:00 15: Present Data with PivotCharts 07:35 16: Filter Data by Using Timelines and Slicers 11:22 Working with Multiple Worksheets and Workbooks 24:00 17: Use Links and External References 12:24 18: Use 3-D References 05:51 19: Consolidate Data 05:45 Using Lookup Functions and Formula Auditing 30:28 20: Use Lookup Functions 12:45 21: Trace Cells 09:05 22: Watch and Evaluate Formulas 08:38 Automating Workbook Functionality 35:27 23: Apply Data Validation 13:28 24: Search for Invalid Data and Formulas with Errors 04:06 25: Work with Macros 17:53 Creating Sparklines and Mapping Data 07:19 26: MapData 07:19 Forecasting Data 27:54 27: Determine Potential Outcomes Using Data Tables 08:47 28: Determine Potential Outcomes Using Scenarios 09:16 29: Use the Goal Seek Feature 04:16 30: Forecasting Data Trends 05:35 Course 02- Module 1: Introduction to Retail Analytics 32:03 31: Introduction to Retail Analytics Preview 32:03 Module 2: Retail Psychology 07:06 32: Retail Psychology 07:06 Module 3: Retail and Data Analytics 12:00 33: Retail and Data Analytics 12:00 Module 4: Benefits of Retail Analytics 16:26 34: Benefits of Retail Analytics 16:26 Module 5: Retail Strategy 09:44 35: Retail Strategy 09:44 Module 6: Retail Buying and Merchandising 11:27 36: Retail Buying and Merchandising 11:27 Module 7: Forecasting 23:27 37: Forecasting 23:27 Module 8: Retail Pricing 16:30 38: Retail Pricing 16:30 Module 9: Analytics Software 19:37 39: Analytics Software 19:37 Module 10: Supply Chain Management in Retailing 07:37 40: Supply Chain Management in Retailing 07:37 Module 11: The Sales Process and Dealing with Customers at the Checkout 04:57 41: The Sales Process and Dealing with Customers at the Checkout 04:57 Module 12: Selling in Multiple Channels 12:40 42: Selling in Multiple Channels 12:40 Module 13: Taking Trends and Targeting Customers Effectively 05:38 43: Taking Trends and Targeting Customers Effectively 05:38 Assessment (Optional) 12:00 44: MCQ Question 12:00 Order Your Certificate 02:00 45: Order Your CPD Certificate 01:00 46: Order Your QLS Endorsed Certificate 01:00 Who is this course for? Data Analyst (Data Analytics) Training This course is for people who want to quickly and easily learn about Data Analyst (Data Analytics). Requirements Data Analyst (Data Analytics) Training You will not need any prior background or expertise to enrol in this Data Analyst (Data Analytics) course. Career path Data Analyst: £25,000 - £50,000 Junior Data Scientist: £30,000 - £60,000 Senior Data Analyst/Scientist: £50,000 - £100,000 Data Analytics Manager: £60,000 - £120,000 Certificates Cademy certificate of completion Digital certificate - Included Will be downloadable when all lectures have been completed Certificate of completion Digital certificate - £10 Diploma in Retail And Data Analytics at QLS Level 5 Hard copy certificate - £119 Show off Your New Skills with a Certificate of Completion After successfully completing the Diploma in Retail And Data Analytics at QLS Level 5, you can order an original hardcopy certificate of achievement endorsed by the Quality Licence Scheme. The certificate will be home-delivered, with a pricing scheme of - 119 GBP inside the UK 129 GBP (including postal fees) for International Delivery Certificate Accredited by CPDQS 29 GBP for Printed Hardcopy Certificate inside the UK 39 GBP for Printed Hardcopy Certificate outside the UK (International Delivery)