Duration 2 Days 12 CPD hours This course is intended for This course is designed for professionals in a variety of job roles who are currently using Tableau to perform numerical or general data analysis, visualization, and reporting. They need to provide data visualizations from multiple data sources, or combine data to show comparisons, manipulate data through calculations, create interactive visualizations, or create visualizations that showcase insights from statistical analysis. This course is also designed for students who plan to obtain Tableau Desktop Certified Associate certification, which requires candidates to pass the Tableau Desktop Certified Associate exam. Overview Blend data multiple sources. Join data. Access data in PDFs. Refine visualizations with sets and parameters. Analyze data with calculations. Visualize data with advanced calculations. Perform statistical analysis and forecasting. Create geographic visualizations. Get answers with Ask and Explain The advent of cloud computing and storage has ushered in the era of "big data." With the abundance of computational power and storage, organizations and employees with many different roles and responsibilities can benefit from analyzing data to find timely insights and gain competitive advantage. Data-backed visualizations allow anyone to explore, analyze, and report insights and trends from data. Tableau© software is designed for this purpose. Tableau was built to connect to a wide range of data sources and allows users to quickly create visualizations of connected data to gain insights, show trends, and create reports. Beyond the fundamental capabilities of creating data driven visualizations, Tableau allows users to manipulate data with calculations to show insights, make visualizations interactive, and perform statistical analysis. This gives users the ability to create and share data driven insights with peers, executives, and clients. Prerequisites Tableau Desktop: Part 1 Lesson 1: Blending Data from Multiple Sources Topic A: Blend Data Topic B: Refine Blends to Visualize Key Information Lesson 2: Joining Data Topic A: Create Joins Topic B: Troubleshoot Joins Topic C: Merge Data with Unions Lesson 3: Accessing Data in PDFs Topic A: Connect to PDFs Topic B: Clean Up and Organize PDF Data Lesson 4: Refining Visualizations with Sets and Parameters Topic A: Create Sets Topic B: Analyze Data with Sets Topic C: Apply Parameters to Refine Visualizations Topic D: Create Advanced Visualizations Lesson 5: Analyzing Data with Calculations Topic A: Create Calculated Fields to Analyze Data Topic B: Manipulate Data with Functions Topic C: Analyze Data with Table Calculations Lesson 6: Visualizing Data with Advanced Calculations Topic A: Create Groups and Bins with Calculations Topic B: Analyze Data with LOD Expressions Lesson 7: Performing Statistical Analysis and Forecasting Topic A: Perform Statistical Analysis Topic B: Forecast Data Trends Lesson 8: Creating Geographic Visualizations Topic A: Create Maps Topic B: Customize Mapped Data Lesson 9: Getting Answers with Ask and Explain Topic A: Ask Data Topic B: Explain Data Additional course details: Nexus Humans Tableau Desktop - Part 2 training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Tableau Desktop - Part 2 course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
Machine learning is a vital aspect of data science, and it is the fundamental building block of artificial intelligence. This course is designed to help you master the basics of machine learning by taking you through ten comprehensive modules. Learning outcomes: Understand the basic principles of machine learning and its significance in today's world. Learn how to use Minitab for data analysis and data cleaning. Understand how regression trees and classification trees work and how to apply them. Understand binary logistic regression and its applications. Understand data modelling and how to use different predictors. Learn how to evaluate and improve the performance of machine learning models. The Machine Learning Basics course is designed to help individuals develop a fundamental understanding of machine learning. In this course, you will learn about the basics of machine learning, including regression, predictors, data cleaning, and data models. Additionally, you will learn how to use Minitab for data analysis and how to apply binary logistic regression, regression trees, and classification trees. The course includes ten comprehensive modules that will help you develop the skills you need to become a machine learning expert. This course is for anyone who wants to learn the basics of machine learning, including students, data analysts, and business professionals. By the end of the course, you will have a deep understanding of machine learning principles, including how to apply machine learning algorithms to solve real-world problems. Certification Upon completion of the course, learners can obtain a certificate as proof of their achievement. You can receive a £4.99 PDF Certificate sent via email, a £9.99 Printed Hardcopy Certificate for delivery in the UK, or a £19.99 Printed Hardcopy Certificate for international delivery. Each option depends on individual preferences and locations. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Students who want to learn about machine learning. Data analysts who want to enhance their skills. Business professionals who want to understand machine learning. Anyone who wants to develop a fundamental understanding of machine learning. Career path Career paths related to this industry are: Data analyst: £20,000 - £50,000 per year Machine learning engineer: £30,000 - £90,000 per year Data scientist: £35,000 - £80,000 per year Business intelligence analyst: £25,000 - £55,000 per year Artificial intelligence (AI) specialist: £45,000 - £100,000 per year Software engineer: £25,000 - £70,000 per year
Duration 5 Days 30 CPD hours Overview Mining data Manipulating data Visualizing and reporting data Applying basic statistical methods Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making. CompTIA Data+ gives you the confidence to bring data analysis to life. As the importance for data analytics grows, more job roles are required to set context and better communicate vital business intelligence. Collecting, analyzing, and reporting on data can drive priorities and lead business decision-making. 1 - Identifying Basic Concepts of Data Schemas Identify Relational and Non-Relational Databases Understand the Way We Use Tables, Primary Keys, and Normalization 2 - Understanding Different Data Systems Describe Types of Data Processing and Storage Systems Explain How Data Changes 3 - Understanding Types and Characteristics of Data Understand Types of Data Break Down the Field Data Types 4 - Comparing and Contrasting Different Data Structures, Formats, and Markup Languages Differentiate between Structured Data and Unstructured Data Recognize Different File Formats Understand the Different Code Languages Used for Data 5 - Explaining Data Integration and Collection Methods Understand the Processes of Extracting, Transforming, and Loading Data Explain API/Web Scraping and Other Collection Methods Collect and Use Public and Publicly-Available Data Use and Collect Survey Data 6 - Identifying Common Reasons for Cleansing and Profiling Data Learn to Profile Data Address Redundant, Duplicated, and Unnecessary Data Work with Missing Value Address Invalid Data Convert Data to Meet Specifications 7 - Executing Different Data Manipulation Techniques Manipulate Field Data and Create Variables Transpose and Append Data Query Data 8 - Explaining Common Techniques for Data Manipulation and Optimization Use Functions to Manipulate Data Use Common Techniques for Query Optimization 9 - Applying Descriptive Statistical Methods Use Measures of Central Tendency Use Measures of Dispersion Use Frequency and Percentages 10 - Describing Key Analysis Techniques Get Started with Analysis Recognize Types of Analysis 11 - Understanding the Use of Different Statistical Methods Understand the Importance of Statistical Tests Break Down the Hypothesis Test Understand Tests and Methods to Determine Relationships Between Variables 12 - Using the Appropriate Type of Visualization Use Basic Visuals Build Advanced Visuals Build Maps with Geographical Data Use Visuals to Tell a Story 13 - Expressing Business Requirements in a Report Format Consider Audience Needs When Developing a Report Describe Data Source Considerations For Reporting Describe Considerations for Delivering Reports and Dashboards Develop Reports or Dashboards Understand Ways to Sort and Filter Data 14 - Designing Components for Reports and Dashboards Design Elements for Reports and Dashboards Utilize Standard Elements Creating a Narrative and Other Written Elements Understand Deployment Considerations 15 - Understand Deployment Considerations Understand How Updates and Timing Affect Reporting Differentiate Between Types of Reports 16 - Summarizing the Importance of Data Governance Define Data Governance Understand Access Requirements and Policies Understand Security Requirements Understand Entity Relationship Requirements 17 - Applying Quality Control to Data Describe Characteristics, Rules, and Metrics of Data Quality Identify Reasons to Quality Check Data and Methods of Data Validation 18 - Explaining Master Data Management Concepts Explain the Basics of Master Data Management Describe Master Data Management Processes Additional course details: Nexus Humans CompTIA Data Plus (DA0-001) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the CompTIA Data Plus (DA0-001) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
Learn to build an HR Dashboard using Excel with our comprehensive course. From data introduction to designing index and tabs, analyze employee data effectively using pivot tables and charts. Ideal for HR professionals and analysts looking to create insightful dashboards for HR metrics and analysis.
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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.
Unlock the power of data with our “Data Science and Data Analytics” course. From setting up your data science environment to mastering essential packages like NumPy, Pandas, and Matplotlib, this program empowers you to analyze, visualize, and derive actionable insights from data.
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