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Are you ready to embark on an enlightening journey of wisdom with the Data Analysis, Business Analysis & Data Science bundle, and pave your way to an enriched personal and professional future? If so, then Step into a world of knowledge with our course bundle - IT and Analytics: Data Analysis, Business Analysis & Data Science. Delve into eight immersive CPD Accredited courses, each a standalone course: Course 01: Basic Data Analysis Course 02: Google Data Studio: Data Analytics Course 03: RCA: Root Cause Analysis Course 04: Business Intelligence Analyst Course Course 05: Quick Data Science Approach from Scratch Course 06: IT Administration and Networking Course 07: CompTIA IT Fundamentals ITF+ (FCO-U61) Course 08: IT For Recruiters Traverse the vast landscapes of theory, unlocking new dimensions of understanding at every turn. Let the IT and Analytics: Data Analysis, Business Analysis & Data Science bundle illuminate your path to wisdom. 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Master Deep Learning Heuristics with R! This course will teach you how to use Deep Learning Heuristics to solve complex problems in Agriculture, Cryptocurrencies, Energy Sector, and Financial Markets. With R, you will be able to develop and implement efficient and scalable solutions.
Register on the Diploma in Data Analysis Fundamentals today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get an e-certificate as proof of your course completion. The Diploma in Data Analysis Fundamentals is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With The Diploma in Data Analysis Fundamentals Receive a e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) 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 Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Who Is This Course For The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements The online training is open to all students and has no formal entry requirements. To study the Diploma in Data Analysis Fundamentals, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16. Course Contents Module 01: Introduction Module 02: Agenda and Principles of Process Management Module 03: The Voice of the Process Module 04: Working as One Team for Improvement Module 05: Exercise: The Voice of the Customer Module 06: Tools for Data Analysis Module 07: The Pareto Chart Module 08: The Histogram Module 09: The Run Chart Module 10: Exercise: Presenting Performance Data Module 11: Understanding Variation Module 12: The Control Chart Module 13: Control Chart Example Module 14: Control Chart Special Cases Module 15: Interpreting the Control Chart Module 16: Control Chart Exercise Module 17: Strategies to Deal with Variation Module 18: Using Data to Drive Improvement Module 19: A Structure for Performance Measurement Module 20: Data Analysis Exercise Module 21: Course Project Module 22: Test your Understanding
Explore the diverse landscape of People Analytics, delving into data sources, cleaning methodologies, and statistical measures. Embrace the importance of ethical considerations and real-world applications, culminating in a comprehensive understanding of this evolving field. This course equips you with the skills to navigate People Analytics effectively. Learn to identify and leverage various data sources, apply cutting-edge data analysis techniques, and address challenges associated with ethical considerations, biases, and small sample sizes. Bridge theory with practicality through real-world examples and case studies. After the successful completion of this course, you will be able to: Identify the Different Data types and Sources used in People Analytics. Explain the Importance of Data Cleaning and Preparation in People Analytics. Apply Data Analysis Techniques, and Interpret Statistical Measures Used in People Analytics. Recognise the Challenges Associated with Collecting and Analysing People-Related Data and Formulate Strategies for Addressing the Challenges. Understand the Ethical Considerations Associated with Collecting and Analysing People-Related Data Such as Informed Consent and Confidentiality This course equips you with the essential skills to gather, clean, and analyze people-related data, transforming it into actionable insights that empower better HR decisions and ultimately, business success. You'll gain hands-on experience with data visualization tools, statistical analysis techniques, and practical strategies for tackling common challenges. By delving into real-world case studies and ethical considerations, you'll graduate with the confidence and expertise to champion data-driven HR initiatives that unlock the full potential of your workforce. VIDEO - Course Structure and Assessment Guidelines Watch this video to gain further insight. Navigating the MSBM Study Portal Watch this video to gain further insight. Interacting with Lectures/Learning Components Watch this video to gain further insight. Data Collection and Analysis for People Analytics Self-paced pre-recorded learning content on this topic. Data Collection and Analysis for People Analytics Put your knowledge to the test with this quiz. Read each question carefully and choose the response that you feel is correct. All MSBM courses are accredited by the relevant partners and awarding bodies. Please refer to MSBM accreditation in about us for more details. There are no strict entry requirements for this course. Work experience will be an added advantage to understanding the content of the course. The certificate is designed to enhance the learner's knowledge in the field. This certificate is for everyone who is eager to know more and get updated on current ideas in their respective field. We recommend this certificate for the following audience. People Analytics Specialist HR Data Analyst Workforce Insights Manager Employee Experience Analyst HR Research Consultant Talent Analytics Strategist Data-driven HR Manager Organizational Behavior Analyst Average Completion Time 2 Weeks Accreditation 3 CPD Hours Level Advanced Start Time Anytime 100% Online Study online with ease. Unlimited Access 24/7 unlimited access with pre-recorded lectures. Low Fees Our fees are low and easy to pay online.
Register on the Data Analytics today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a digital certificate as proof of your course completion. The Data Analytics is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With The Data Analytics Receive a e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) 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 Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Who Is This Course For: The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements: The online training is open to all students and has no formal entry requirements. To study the Data Analytics, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16. Course Content 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 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.
Overview Mastering data science skills and expertise can open new doors of opportunities for you in a wide range of fields. Learn the fundamentals and develop a solid grasp of Python data science with the comprehensive Data Science with Python course. This course is designed to assist you in securing a valuable skill set and boosting your career. This course will provide you with quality training on the fundamentals of data analysis with Python. From the step-by-step learning process, you will learn the techniques of setting up the system. Then the course will teach you Python data structure and functions. You will receive detailed lessons on NumPy, Matplotlib, and Pandas. Furthermore, you will develop the skills for Algorithm Evaluation Techniques, visualising datasets and much more. After completing the course you will receive a certificate of achievement. This certificate will help you create an impressive resume. So join today! 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? This course Data Science with Python course is ideal for beginners in data science. It will help them develop a solid grasp of Python and help them pursue their dream career in the field of data science. Requirements The students will not require any formal qualifications or previous experience to enrol in this course. Anyone can learn from the course anytime from anywhere through smart devices like laptops, tabs, PC, and smartphones with stable internet connections. They can complete the course according to their preferable pace so, there is no need to rush. Career Path This course will equip you with valuable knowledge and effective skills in this area. After completing the course, you will be able to explore career opportunities in the fields such as Data Analyst Data Scientist Data Manager Business Analyst And much more! Course Curriculum 90 sections • 90 lectures • 10:19:00 total length •Course Overview & Table of Contents: 00:09:00 •Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types: 00:05:00 •Introduction to Machine Learning - Part 2 - Classifications and Applications: 00:06:00 •System and Environment preparation - Part 1: 00:04:00 •System and Environment preparation - Part 2: 00:06:00 •Learn Basics of python - Assignment 1: 00:10:00 •Learn Basics of python - Assignment 2: 00:09:00 •Learn Basics of python - Functions: 00:04:00 •Learn Basics of python - Data Structures: 00:12:00 •Learn Basics of NumPy - NumPy Array: 00:06:00 •Learn Basics of NumPy - NumPy Data: 00:08:00 •Learn Basics of NumPy - NumPy Arithmetic: 00:04:00 •Learn Basics of Matplotlib: 00:07:00 •Learn Basics of Pandas - Part 1: 00:06:00 •Learn Basics of Pandas - Part 2: 00:07:00 •Understanding the CSV data file: 00:09:00 •Load and Read CSV data file using Python Standard Library: 00:09:00 •Load and Read CSV data file using NumPy: 00:04:00 •Load and Read CSV data file using Pandas: 00:05:00 •Dataset Summary - Peek, Dimensions and Data Types: 00:09:00 •Dataset Summary - Class Distribution and Data Summary: 00:09:00 •Dataset Summary - Explaining Correlation: 00:11:00 •Dataset Summary - Explaining Skewness - Gaussian and Normal Curve: 00:07:00 •Dataset Visualization - Using Histograms: 00:07:00 •Dataset Visualization - Using Density Plots: 00:06:00 •Dataset Visualization - Box and Whisker Plots: 00:05:00 •Multivariate Dataset Visualization - Correlation Plots: 00:08:00 •Multivariate Dataset Visualization - Scatter Plots: 00:05:00 •Data Preparation (Pre-Processing) - Introduction: 00:09:00 •Data Preparation - Re-scaling Data - Part 1: 00:09:00 •Data Preparation - Re-scaling Data - Part 2: 00:09:00 •Data Preparation - Standardizing Data - Part 1: 00:07:00 •Data Preparation - Standardizing Data - Part 2: 00:04:00 •Data Preparation - Normalizing Data: 00:08:00 •Data Preparation - Binarizing Data: 00:06:00 •Feature Selection - Introduction: 00:07:00 •Feature Selection - Uni-variate Part 1 - Chi-Squared Test: 00:09:00 •Feature Selection - Uni-variate Part 2 - Chi-Squared Test: 00:10:00 •Feature Selection - Recursive Feature Elimination: 00:11:00 •Feature Selection - Principal Component Analysis (PCA): 00:09:00 •Feature Selection - Feature Importance: 00:06:00 •Refresher Session - The Mechanism of Re-sampling, Training and Testing: 00:12:00 •Algorithm Evaluation Techniques - Introduction: 00:07:00 •Algorithm Evaluation Techniques - Train and Test Set: 00:11:00 •Algorithm Evaluation Techniques - K-Fold Cross Validation: 00:09:00 •Algorithm Evaluation Techniques - Leave One Out Cross Validation: 00:05:00 •Algorithm Evaluation Techniques - Repeated Random Test-Train Splits: 00:07:00 •Algorithm Evaluation Metrics - Introduction: 00:09:00 •Algorithm Evaluation Metrics - Classification Accuracy: 00:08:00 •Algorithm Evaluation Metrics - Log Loss: 00:03:00 •Algorithm Evaluation Metrics - Area Under ROC Curve: 00:06:00 •Algorithm Evaluation Metrics - Confusion Matrix: 00:10:00 •Algorithm Evaluation Metrics - Classification Report: 00:04:00 •Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction: 00:06:00 •Algorithm Evaluation Metrics - Mean Absolute Error: 00:07:00 •Algorithm Evaluation Metrics - Mean Square Error: 00:03:00 •Algorithm Evaluation Metrics - R Squared: 00:04:00 •Classification Algorithm Spot Check - Logistic Regression: 00:12:00 •Classification Algorithm Spot Check - Linear Discriminant Analysis: 00:04:00 •Classification Algorithm Spot Check - K-Nearest Neighbors: 00:05:00 •Classification Algorithm Spot Check - Naive Bayes: 00:04:00 •Classification Algorithm Spot Check - CART: 00:04:00 •Classification Algorithm Spot Check - Support Vector Machines: 00:05:00 •Regression Algorithm Spot Check - Linear Regression: 00:08:00 •Regression Algorithm Spot Check - Ridge Regression: 00:03:00 •Regression Algorithm Spot Check - Lasso Linear Regression: 00:03:00 •Regression Algorithm Spot Check - Elastic Net Regression: 00:02:00 •Regression Algorithm Spot Check - K-Nearest Neighbors: 00:06:00 •Regression Algorithm Spot Check - CART: 00:04:00 •Regression Algorithm Spot Check - Support Vector Machines (SVM): 00:04:00 •Compare Algorithms - Part 1 : Choosing the best Machine Learning Model: 00:09:00 •Compare Algorithms - Part 2 : Choosing the best Machine Learning Model: 00:05:00 •Pipelines : Data Preparation and Data Modelling: 00:11:00 •Pipelines : Feature Selection and Data Modelling: 00:10:00 •Performance Improvement: Ensembles - Voting: 00:07:00 •Performance Improvement: Ensembles - Bagging: 00:08:00 •Performance Improvement: Ensembles - Boosting: 00:05:00 •Performance Improvement: Parameter Tuning using Grid Search: 00:08:00 •Performance Improvement: Parameter Tuning using Random Search: 00:06:00 •Export, Save and Load Machine Learning Models : Pickle: 00:10:00 •Export, Save and Load Machine Learning Models : Joblib: 00:06:00 •Finalizing a Model - Introduction and Steps: 00:07:00 •Finalizing a Classification Model - The Pima Indian Diabetes Dataset: 00:07:00 •Quick Session: Imbalanced Data Set - Issue Overview and Steps: 00:09:00 •Iris Dataset : Finalizing Multi-Class Dataset: 00:09:00 •Finalizing a Regression Model - The Boston Housing Price Dataset: 00:08:00 •Real-time Predictions: Using the Pima Indian Diabetes Classification Model: 00:07:00 •Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset: 00:03:00 •Real-time Predictions: Using the Boston Housing Regression Model: 00:08:00 •Resources - Data Science & Machine Learning with Python: 00:00:00
Course Overview: Are you ready to unlock the world of digital possibilities by understanding the art and science of data analytics? We live in an era where data back every decision and every action requires insightful analysis. Clive Humby said, "Data is the new oil, and it's the new oil, so it's an invaluable resource for companies worldwide. This comprehensive course covers a broad spectrum of data analytics, starting with an engaging 'Introduction to the World of Data,' before delving into the fundamental components like the 'Basics of Data Analytics,' 'Statistics for Data Analytics,' and the 'Actions Taken in the Data Analysis Process.' Each subsequent module is carefully designed to guide you through various stages of data analytics. You'll explore 'Data Mining,' work with 'Excel for Data Analytics,' and discover 'Tools for Data Analytics.' The curriculum wraps up with a focus on 'Data-Analytic Thinking' and 'Data Visualisation.' Enrol today and start your journey to becoming a data analytics expert! Key Features of the Course: This course comes with a CPD certificate, affirming your proficiency in data analytics. It offers 24/7 learning assistance to ensure you get the most out of your learning journey. The content is presented in easy-to-understand and engaging learning materials, carefully curated to make your journey in data analytics enlightening. Who is This Course For? This course suits professionals seeking to leverage data analytics in their respective fields, individuals aspiring to venture into the data science arena, and students keen to acquire contemporary skills for the digital age. What You Will Learn: Understand the fundamental concepts of data analytics. Apply statistical techniques to analyse large data sets. Implement effective strategies for data collection and storage. Master the art of data mining and extraction of valuable insights. Utilise Excel and other tools effectively for data analysis. Develop a data-analytic mindset for problem-solving. Translate data insights into compelling visualisations. Why Enrol in This Course: This course will open doors to many opportunities. You will learn from top-notch professionals, utilise quality learning materials and have access to trending and recently updated curriculum. Requirements: A basic understanding of computers A willingness to learn Career Path: The expertise gained from this Data Analytics course can pave your way into a variety of professions, such as: Data Analyst (£30,000-£60,000) Business Analyst (£35,000-£70,000) Market Research Analyst (£27,000-£55,000) Operations Analyst (£31,000-£62,000) Quantitative Analyst (£45,000-£85,000) Data Scientist (£50,000-£90,000) Data Engineer (£35,000-£75,000) Certification: On successful completion of this course, you will receive a CPD certificate, testifying your mastery in the field of data analytics. With this recognition, you can confidently showcase your skills and expertise in the professional world. Data analytics is a powerful tool that can be used to make better decisions, improve efficiency, and drive innovation. If you want to join this growing field, this course is for you! FAQ What do you mean by data analytics? Data analytics is the process of collecting, cleaning, analyzing, and interpreting data to extract insights. What data analytics actually do? Data analytics helps businesses make better decisions by providing them with insights into their data. This can include insights into customer behavior, market trends, and product performance. What are the 5 data analytics? The 5 data analytics are: Descriptive analytics: This type of analytics describes what has happened in the past. Diagnostic analytics: This type of analytics identifies the root cause of problems. Predictive analytics: This type of analytics predicts what will happen in the future. Prescriptive analytics: This type of analytics recommends actions to take based on the predictions. Visual analytics: This type of analytics uses visual representations of data to make it easier to understand. What is data analytics examples? Here are some examples of data analytics: A retailer uses data analytics to track customer behaviour and identify trends. A bank uses data analytics to predict which customers are likely to default on their loans. A healthcare provider uses data analytics to identify patients who are at risk for certain diseases. What are 4 types of analytics? The 4 types of analytics are: Descriptive analytics: This type of analytics describes what has happened in the past. Diagnostic analytics: This type of analytics identifies the root cause of problems. Predictive analytics: This type of analytics predicts what will happen in the future. Prescriptive analytics: This type of analytics recommends actions to take based on the predictions. Why do we use data analytics? We use data analytics to make better decisions, improve efficiency, and drive innovation. Here are some of the benefits of using data analytics: Better decision-making: Data analytics can help businesses make better decisions by providing them with insights into their data. Improved efficiency: Data analytics can help businesses improve efficiency by identifying areas where they can save time and money. Driven innovation: Data analytics can help businesses drive innovation by identifying new opportunities and trends. Course Curriculum 13 sections • 13 lectures • 12:25:00 total length •Introduction to the World of Data: 01:00:00 •Basics of Data Analytics: 00:40:00 •Statistics for Data Analytics: 01:00:00 •Actions Taken in the Data Analysis Process: 00:55:00 •Gathering the Right Information: 01:00:00 •Storing Data: 01:15:00 •Data Mining: 01:00:00 •Excel for Data Analytics: 01:20:00 •Tools for Data Analytics: 01:20:00 •Data-Analytic Thinking: 01:10:00 •Data Visualisation That Clearly Describes Insights: 00:45:00 •Data Visualization Tools: 01:00:00 •Assignment - Data Analytics: 00:00:00
Overview Are you ready to dive into data analysis and unlock valuable insights that can drive business growth? Introduction to Data Analysis is a comprehensive course designed to provide learners with a solid foundation in the principles and techniques of data analysis. This course will equip you with the essential skills and knowledge to thrive in data analysis. With a comprehensive curriculum spanning 22 modules, you will delve deep into the world of data, from understanding its fundamentals to harnessing it for meaningful insights. Our expertly crafted curriculum covers data collection, process management, statistical tools, control charts, and strategies to deal with variation.Enrol today in this Introduction to Data Analysis course to succeed in all areas of your life. Let your skill become your greatest asset! Key Features of the Course This course equips learners with the essential tools and knowledge to analyse and interpret data accurately. The course is accredited, ensuring its recognition and credibility within the professional community. Learners will have access to 24/7 learning assistance, allowing them to seek guidance and support whenever needed. Who is This course for? This Introduction to Data Analysis course is suitable for students & professionals from various fields, including business, finance, marketing, healthcare, and more. It is also beneficial for individuals looking to enhance their data analysis skills for personal or professional development. What You Will Learn Throughout the course, you will delve into various modules that cover essential concepts and tools for data analysis. Starting with an introduction to process management principles, you will progress through topics such as the voice of the process, customer feedback analysis, and data visualisation using tools like Pareto charts, histograms, and run charts. You will also gain a deep understanding of variation and control charts and learn how to interpret and use them effectively for process improvement. By the end of the course, learners will have a solid understanding of these topics and be able to apply their knowledge to real-world data analysis scenarios. Why Enrol in This Course Data analysis is one of the most sought-after skills in today's job market. According to LinkedIn, data analysis is among the top 10 most in-demand skills for 2023. Data analysis can help you: Improve your decision-making skills and confidence Enhance your problem-solving and critical-thinking abilities Boost your creativity and innovation potential Increase your productivity and efficiency Advance your career and create earning potential Requirements There are no specific prerequisites for this course. However, a basic understanding of mathematics and statistics will be beneficial. Access to a computer with an internet connection is also required to complete the course. Career Path Completing this Introduction to Data Analysis course can lead to various career opportunities in data analysis. Some of the course-related professions in the UK, along with their average salaries, include: Data Analyst (£35,000 - £45,000 per year) Business Analyst (£40,000 - £55,000 per year) Financial Analyst (£40,000 - £60,000 per year) Market Research Analyst (£25,000 - £40,000 per year) Operations Analyst (£35,000 - £50,000 per year) Healthcare Data Analyst (£35,000 - £50,000 per year) Quality Control Analyst (£25,000 - £35,000 per year) Certification Upon successful completion of the course, learners will receive a CPD certificate, validating their achievement and demonstrating their commitment to professional development in the field of data analysis. Course Curriculum 3 sections • 24 lectures • 02:13:00 total length •Module 01: Introduction: 00:02:00 •Module 02: Agenda and Principles of Process Management: 00:06:00 •Module 03: The Voice of the Process: 00:05:00 •Module 04: Working as One Team for Improvement: 00:04:00 •Module 05: Exercise: The Voice of the Customer: 00:03:00 •Module 06: Tools for Data Analysis: 00:07:00 •Module 07: The Pareto Chart: 00:03:00 •Module 08: The Histogram: 00:03:00 •Module 09: The Run Chart: 00:04:00 •Module 10: Exercise: Presenting Performance Data: 00:05:00 •Module 11: Understanding Variation: 00:06:00 •Module 12: The Control Chart: 00:06:00 •Module 13: Control Chart Example: 00:04:00 •Module 14: Control Chart Special Cases: 00:06:00 •Module 15: Interpreting the Control Chart: 00:10:00 •Module 16: Control Chart Exercise: 00:07:00 •Module 17: Strategies to Deal with Variation: 00:06:00 •Module 18: Using Data to Drive Improvement: 00:14:00 •Module 19: A Structure for Performance Measurement: 00:06:00 •Module 20: Data Analysis Exercise: 00:06:00 •Module 21: Course Project: 00:03:00 •Module 22: Test your Understanding: 00:17:00 •Resources - Introduction to Data Analysis: 00:00:00 •Assignment - Introduction to Data Analysis: 00:00:00
Course Overview: According to a report by the World Economic Forum, data analysts and scientists are among the top emerging job roles. The "Data Analytics with Tableau" course is tailored to equip learners with the vital skills required to excel in this dynamic field. The course delves into the intricacies of data visualisation and analysis using Tableau, a leading software in the industry. It's not merely about understanding data but transforming it into actionable insights that drive business decisions. The course is structured to provide a comprehensive understanding of various aspects of data analytics, including sales, HR, and shipping analytics.Don't miss this opportunity to advance your career with cutting-edge skills in data analytics. Enrol in "Data Analytics with Tableau" now and embark on a journey of professional growth and endless possibilities! Key Features of the Course: CPD Certificate: Upon completion, you will receive a prestigious Continuing Professional Development (CPD) certificate, recognised globally for enhancing your career prospects. 24/7 Learning Assistance: Our dedicated support team ensures you receive prompt assistance, providing a seamless learning experience. Who is This Course For? This course is tailored for individuals who aspire to become data analysts, business intelligence professionals, marketing strategists, or decision-makers seeking to leverage data effectively. No experience with Tableau or coding is required, making it accessible and engaging for beginners. What You Will Learn: Data Analytics with Tableau, This course covers a wide range of topics, starting with connecting and preparing data, where you will learn how to import, clean, and transform data to make it analysis-ready within Tableau. Next, you will master the art of building insightful charts and visualisations using Tableau's rich set of tools, enabling you to communicate data trends and insights effectively. Additionally, you will explore the creation of captivating headline cards and interactive dashboards, gaining expertise in presenting key information and facilitating data exploration. Real-world projects, including Discount Mart, Green Destinations, Super Store, Northwind Trade, and Tesla, will provide you with outstanding experience in applying Tableau to solve practical data challenges. Lastly, you will develop a solid understanding of database concepts and learn to create compelling data stories using Tableau's storytelling features. By the end of this course, you will have the skills and confidence to make data-driven decisions and communicate insights effectively using Tableau. Why Enrol in This Course: Join the recently updated top-reviewed Data Analytics course with Tableau to keep you at the forefront of the field. Expand your analytical skills, unlock career opportunities, and stay current in the rapidly evolving world of data analytics by mastering Tableau, the industry-standard tool for visual analytics. Requirements: No prior experience with Tableau or coding is required. All you need is a computer with internet access, a curious mind, and a passion for exploring the world of data analytics. Career Path: By acquiring data analytics skills with Tableau, you open doors to exciting career paths, such as: Data Analyst (Average Salary: £35,000 - £45,000) Business Intelligence Analyst (Average Salary: £40,000 - £55,000) Marketing Analyst (Average Salary: £30,000 - £40,000) Financial Analyst (Average Salary: £35,000 - £50,000) Data Visualization Specialist (Average Salary: £40,000 - £60,000) Database Administrator (Average Salary: £40,000 - £55,000) Data Scientist (Average Salary: £45,000 - £70,000) Certification: Upon successful completion of the course, you will receive a CPD certificate, internationally recognised for its validation of your expertise in data analytics with Tableau. Enrol now and embark on a transformative journey to become a proficient data analyst and visualisation expert with Tableau! Course Curriculum 9 sections • 41 lectures • 06:47:00 total length •Introduction to the Course: 00:02:00 •What is Tableau? An Introduction to Tableau: 00:03:00 •How this course is Structured: 00:01:00 •Installing the Free Full Version of Tableau: 00:02:00 •Project Brief for Discount Mart: 00:03:00 •Connecting and Preparing Data for Discount Mart: 00:15:00 •Building Charts on Tableau for Discount Mart (Part 1): 00:33:00 •Building Charts on Tableau for Discount Mart (Part 2): 00:16:00 •Creating Headline Cards on Tableau for Discount Mart: 00:10:00 •Building and Publishing Dashboards on Tableau: 00:15:00 •Project Brief for Green Destinations: 00:02:00 •Connecting and Preparing Data for Green Destinations: 00:09:00 •Building Charts on Tableau (Part 1) for Green Destinations: 00:28:00 •Building Charts on Tableau (Part 2) for Green Destinations: 00:08:00 •Creating Headline Cards on Tableau: 00:15:00 •Building a Dashboard for Green Destinations: 00:12:00 •Publish your Dashboard to Tableau Public: 00:02:00 •Project Brief for Super Store: 00:02:00 •Connecting and Preparing Data for Super Store: 00:17:00 •Building Charts on Tableau (Part 1) for Super Store: 00:34:00 •Building Charts on Tableau (Part 2) for Super Store: 00:23:00 •Building a Dashboard: 00:18:00 •Publish your Dashboard to Tableau Public: 00:03:00 •Project Brief for Northwind Trade: 00:03:00 •Connecting and Preparing Data for Northwind Trade: 00:14:00 •Building Charts on Tableau for Northwind Trade: 00:37:00 •Building and Publishing Dashboards for Northwind Trade: 00:10:00 •Project Brief for Tesla: 00:02:00 •Creating a Data Source through Google Sheet Functions: 00:05:00 •Connect to the Data for Tesla: 00:04:00 •Building Charts on Tableau for Tesla: 00:22:00 •Building Headline Cards: 00:09:00 •Building a Tesla Dashboard: 00:08:00 •Publish your Dashboard to Tableau Public: 00:03:00 •Introduction to Database Concepts: 00:01:00 •Understanding Relational Databases: 00:04:00 •Relationships of Database Entities: 00:02:00 •Primary and Foreign Keys: 00:01:00 •Data types and Naming Conventions: 00:04:00 •Creating Stories on Tableau: 00:05:00 •Resources - Data Analytics with Tableau: 00:00:00