3993 Analyst courses in Stonehaven delivered Online

Ask & You Shall Achieve! Discover Collaborative Problem Solving to Realize Greater Value in the Agile Framework If you want to succeed in today's economy, the true measure of your success is not in getting people to work; it's not even in getting people to work hard. It's about getting people to work hard TOGETHER, to achieve and create something good... something valuable. To create value, you must know HOW value is measured and HOW to allow your team members to best contribute their talents. The wisdom already exists within your team. It's your job to allow it to flow. Do you know what questions to ask yourself? Do you know what questions to ask your team? Are you asking questions that increase collaboration, co-creation, and co-elevation? In this presentation, we will explore Agile, Axiology, and Asking better questions that lead to better solutions, better results, and greater value. Learning Objectives: Understand the hierarchy of value and impact on leadership Discover the 3 dimensions of Questions Use the principles of axiology to lead and motivate Discover the Collaborative Problem Solving (CPS) Process

Enabling Agility by Measuring What Matters Sally is simply a transformer-someone who is passionate about helping teams and organizations do what they do better. In this session, she aims to help transformation leaders assess their transformation maturity in each of the 7 Pillars of Enterprise Business Agility; and understand how to accelerate their transformation by aligning teams to outcomes and removing their obstacles. What is Business Agility? Challenges and Enablers The 7 Pillars of Enterprise Business Agility The 3 Metrics that Matter Aligning Teams to Outcomes Measuring Team Health and Removing Obstacles This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.

Modern Agile: Discovering Better Ways to Be Awesome Genuine agility is enormously effective in helping us achieve our dreams. The trouble is, Agile has grown into a complex tangle of roles and rituals, frameworks and tools, processes and certifications. We need a return to simplicity. Modern Agile is here to help.Designed for people in many domains (not just IT), Modern Agile is defined by four guiding principles: Make People Awesome, Make Safety a Prerequisite, Experiment & Learn Rapidly and Deliver Value Continuously. Understanding and deeply practicing these four principles will help you get better results faster.In this talk I'll share how these four (principles power world-famous companies and how they can help you work with greater speed, simplicity, safety and success. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.

Data Analysis In Excel is suitable for anyone aspiring to or already working in this field or simply want to learn deeper into data analysis. You will be able to add this qualification to your CV by downloading your certificate instantly without any cost. To make this course more accessible for you, we have designed it for both part-time and full-time students. This course is packed into the bite-size module for your convenience. You can study at your own pace or become accredited within hours! If you require support, our experienced tutors are always available to help you throughout the comprehensive syllabus of this course and answer all your queries through email. This Data Analysis In Excel aims to introduce Data Analysis in Excel 2016. You'll learn the best way to enter and organize data, sort and map data, perform calculations with simple functions, format the appearance of your data and cells, and build charts and PivotTables for data analysis. You will know how to validate data, search and remove invalid data. The course covers Lookup information using VLOOKUP, and INDEX-MATCH, data forecasting and cleansing, providing external and 3D references and inserting sparklings, so that you have a great foundation in the world's most popular spreadsheet programme. Finally, you will learn different features to visualise or analyse your data in the most convenient way, which allows you to take the right business decisions for your company Who is this Course for? Data Analysis In Excel is perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic background. Requirements Our Data Analysis In Excel is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. CPD Certificate from Course Gate  At the successful completion of the course, you can obtain your CPD certificate from us. You can order the PDF certificate for £9 and the hard copy for £15. Also, you can order both PDF and hardcopy certificates for £22. Career path This course opens a new door for you to enter the relevant job market and also gives you the opportunity to acquire extensive knowledge along with required skills to become successful. You will be able to add our qualification to your CV/resume which will help you to stand out in the competitive job industry. Course Curriculum Modifying a Worksheet Insert, Delete, and Adjust Cells, Columns, and Rows 00:10:00 Search for and Replace Data 00:09:00 Use Proofing and Research Tools 00:07:00 Working with Lists Sort Data 00:10:00 Filter Data 00:10:00 Query Data with Database Functions 00:09:00 Outline and Subtotal Data 00:09:00 Analyzing Data Create and Modify Tables 00:15:00 Apply Intermediate Conditional Formatting 00:07:00 Apply Advanced Conditional Formatting 00:05:00 Visualizing Data with Charts Create Charts 00:13:00 Modify and Format Charts 00:12:00 Use Advanced Chart Features 00:12:00 Using PivotTables and PivotCharts Create a PivotTable 00:13:00 Analyze PivotTable Data 00:12:00 Present Data with PivotCharts 00:07:00 Filter Data by Using Timelines and Slicers 00:11:00 Working with Multiple Worksheets and Workbooks Use Links and External References 00:12:00 Use 3-D References 00:06:00 Consolidate Data 00:05:00 Using Lookup Functions and Formula Auditing Use Lookup Functions 00:12:00 Trace Cells 00:09:00 Watch and Evaluate Formulas 00:08:00 Automating Workbook Functionality Apply Data Validation 00:13:00 Search for Invalid Data and Formulas with Errors 00:04:00 Work with Macros 00:18:00 Creating Sparklines and Mapping Data Create Sparklines 00:07:00 MapData 00:07:00 Forecasting Data Determine Potential Outcomes Using Data Tables 00:08:00 Determine Potential Outcomes Using Scenarios 00:09:00 Use the Goal Seek Feature 00:04:00 Forecasting Data Trends 00:05:00 Certificate and Transcript Order Your Certificates or Transcripts 00:00:00

Through video lessons, PDF handouts, mock exams and online assessment, you will gain a complete understanding of the role of a business administrator in a modern office environment. Upon completion, you will earn a CPD accredited qualification as proof of your skills. The course begins with the basics of office admin work, including interpersonal communication, time management and being a successful influencer, before moving onto the specifics of business finance management, payroll, and recruitment. Why choose this course Earn an e-certificate upon successful completion. Accessible, informative modules taught by expert instructors Study in your own time, at your own pace, through your computer tablet or mobile device Benefit from instant feedback through mock exams and multiple-choice assessments Get 24/7 help or advice from our email and live chat teams Full Tutor Support on Weekdays Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Mock exams Multiple-choice assessment Certification After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for £9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for £15.99, which will reach your doorsteps by post. Who is this course for? Advanced Diploma in Business Administration is suitable for anyone who want to gain extensive knowledge, potential experience and professional skills in the related field. This is a great opportunity for all student from any academic backgrounds to learn more on this subject. Course Contents Module 01: Business Administration Module 02: Management of Business Module 03: Functions, Nature and Levels of Management Module 04: Characteristics of Professional Managers Module 05: Business Process Management Module 06: Different Phases of Business Process Lifecycle Module 07: The Monitoring and Optimising Phase of Business Management Module 08: Project Management Module 09: Marketing, Sales and Negotiation Module 10: Leadership and Critical Thinking Module 11: Business Relationship and Change Management Module 12: Human Resource Management Module 13: Risk Management Module 14: Business Communications and Report Writing Module 15: Accounting and Financial Management Module 16: Payroll Management and Career Opportunity

Managing Agile and Waterfall Projects: A Hybrid Approach With the growing interest in Agile approaches, how can we take a measured approach? Organizations can't just simply drop everything to become 100% Agile. Not only are hybrid approaches acceptable, they are common in transitioning organizations. We need to understand the strengths and weaknesses of both the traditional and Agile methods to find the best combination that gives us the best of both worlds. This presentation will cover how to combine both approaches into a hybrid model, and help you understand the general criteria of how one approach would be chosen over another.Learning Objectives This presentation will cover how to combine both approaches into a hybrid model, and help you understand the general criteria of how one approach would be chosen over another. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.

Measurement and Governance for Agile Leaders - Why it's not Working and What it Does To achieve true business agility. leaders must not only grow and support self-reliant. cross-functional. self-organizing teams; they must also change the way their organizations fund and oversee their agile initiatives. They must believe in feedback and allow that feedback to work. However. old measures like 'on time' and 'within budget' are not useful when markets and customers are constantly changing. potentially resulting in delivering great solutions to problems that no longer exist. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.

Establishing a Business Analysis Framework to Increase Organizational Agility Establishing a Business Analysis Framework to Increase Organizational Agility In managing today's complex project portfolios, many organizations are faced with challenges due to globalization, changing business priorities, and technological demands. To respond quickly to these challenges, organizations have to embrace change in order to become more agile. Business analysis is a critical element to achieving this organizational agility. More importantly, establishing an effective business analysis framework ensures that an organization can repeatedly deliver solutions that are aligned to goals and objectives that may evolve over time. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.

Overview of Data Science & Machine Learning with Python Join our Data Science & Machine Learning with Python course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Data Science & Machine Learning with Python course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Data Science & Machine Learning with Python course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now! This Data Science & Machine Learning with Python Course will help you to learn: Learn strategies to boost your workplace efficiency. Hone your skills to help you advance your career. Acquire a comprehensive understanding of various topics and tips. Learn in-demand skills that are in high demand among UK employers This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this Data Science & Machine Learning with Python. Enrol today and complete the course to achieve a certificate that can change your career forever. Details Perks of Learning with IOMH One-To-One Support from a Dedicated Tutor Throughout Your Course. Study Online - Whenever and Wherever You Want. Instant Digital/ PDF Certificate. 100% Money Back Guarantee. 12 Months Access. Process of Evaluation After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion - Digital / PDF Certificate After completing the Data Science & Machine Learning with Python course, you can order your CPD Accredited Digital / PDF Certificate for £5.99.  Certificate of Completion - Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. Shipping Charges: Inside the UK: £3.99 International: £10.99 Who Is This Course for? This Data Science & Machine Learning with Python is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand.  On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements You don't need any educational qualification or experience to enrol in the Data Science & Machine Learning with Python course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career Path The certification and skills you get from this Data Science & Machine Learning with Python Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:04:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using NumPy 00:04:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:06:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Data Science & Machine Learning with Python 00:00:00

Are you looking to enhance your Data Analysis with Excel skills? If yes, then you have come to the right place. Our comprehensive course on Data Analysis with Excel will assist you in producing the best possible outcome by mastering the Data Analysis with Excel skills. The Data Analysis with Excel is for those who want to be successful. In the Data Analysis with Excel, you will learn the essential knowledge needed to become well versed in Data Analysis with Excel. Our Data Analysis with Excel starts with the basics of Data Analysis with Excel and gradually progresses towards advanced topics. Therefore, each lesson of this Data Analysis with Excel is intuitive and easy to understand. Why would you choose the Data Analysis with Excel from Compliance Central: Lifetime access to Data Analysis with Excel materials Full tutor support is available from Monday to Friday with the Data Analysis with Excel Learn Data Analysis with Excel skills at your own pace from the comfort of your home Gain a complete understanding of Data Analysis with Excel Accessible, informative Data Analysis with Excel learning modules designed by expert instructors Get 24/7 help or advice from our email and live chat teams with the Data Analysis with Excel bundle Study Data Analysis with Excel in your own time through your computer, tablet or mobile device. A 100% learning satisfaction guarantee with your Data Analysis with Excel Improve your chance of gaining in demand skills and better earning potential by completing the Data Analysis with Excel Data Analysis with Excel Curriculum Breakdown of the Data Analysis with Excel Modifying a Worksheet Insert, Delete, and Adjust Cells, Columns, and Rows Search for and Replace Data Use Proofing and Research Tools Working with Lists Sort Data Filter Data Query Data with Database Functions Outline and Subtotal Data Analyzing Data Apply Intermediate Conditional Formatting Apply Advanced Conditional Formatting Visualizing Data with Charts Create Charts Modify and Format Charts Use Advanced Chart Features Using PivotTables and PivotCharts Create a PivotTable Analyze PivotTable Data Present Data with PivotCharts Filter Data by Using Timelines and Slicers Working with Multiple Worksheets and Workbooks Use Links and External References Use 3-D References Consolidate Data Using Lookup Functions and Formula Auditing Use Lookup Functions Trace Cells Watch and Evaluate Formulas Automating Workbook Functionality Apply Data Validation Search for Invalid Data and Formulas with Errors Work with Macros Creating Sparklines and Mapping Data Create Sparklines MapData Forecasting Data Determine Potential Outcomes Using Data Tables Determine Potential Outcomes Using Scenarios Use the Goal Seek Feature Forecasting Data Trends CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Data Analysis with Excel helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in Data Analysis with Excel. It is also great for professionals who are already working in Data Analysis with Excel and want to get promoted at work. Requirements To enrol in this Data Analysis with Excel, all you need is a basic understanding of the English Language and an internet connection. Career path The Data Analysis with Excel will enhance your knowledge and improve your confidence in exploring opportunities in various sectors related to Data Analysis with Excel. Certificates CPD Accredited PDF Certificate Digital certificate - Included CPD Accredited PDF Certificate CPD Accredited Hard Copy Certificate Hard copy certificate - £10.79 CPD Accredited Hard Copy Certificate Delivery Charge: Inside the UK: Free Outside of the UK: £9.99