Tableau 2020 Certified Associate Exam Guide A-Z (w Datasets)

BY
Udemy

Acquire a detailed understanding of Tableau's fundamental and essential concepts to become a certified data professional.

Mode

Online

Fees

₹ 8500

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course overview

Tableau 2020 Certified Associate Exam Guide A-Z (w Datasets) online course is designed by Kirill Eremenko Data Scientist and Ligency I Team and is presented by Udemy for learners who want to gain knowledge of the most powerful and popular data visualization tool available today and move closer to becoming professional data scientists. The Tableau 2020 Certified Associate Exam Guide A-Z (w Datasets) online course aims to teach learners everything they need to know to pass the Tableau certified associate examination with a perfect score on their first attempt after completing this course.


Tableau 2020 Certified Associate Exam Guide A-Z (w Datasets) online classes by Udemy provide learners with hands-on experience of aspects of data sciencebusiness intelligence, and data analytics projects. This course covers every topic from the official test preparation guide, including tableau principles, data connections, organizing, and simplifying data, field kinds, chart types, calculations, mapping, analytics, and dashboards, among others. Learners who wish to participate must enroll by purchasing a lifetime membership to the course.

The highlights

  • Certificate of completion
  • Self-paced course
  • English videos with multi-language subtitles
  • 38 hours of pre-recorded video content
  • 16 articles
  • 2 downloadable resources
  • Practice tests
  • Quizzes
  • 30-day money-back guarantee 
  • Unlimited access
  • Accessible on mobile devices and TV

Program offerings

  • Certificate of completion
  • Self-paced course
  • English videos with multi-language subtitles
  • 38 hours of pre-recorded video content
  • 16 articles
  • 2 downloadable resources
  • Practice tests

Course and certificate fees

Fees information
₹ 8,500
certificate availability

Yes

certificate providing authority

Udemy

Who it is for

What you will learn

Tableau knowledge Knowledge of data visualization

After completing Tableau 2020 Certified Associate Exam Guide A-Z (w Datasets) online training, learners will acquire a thorough understanding of Tableau's features and functionalities for data operations, such as data analytics and data visualization. Learners will discover solutions to a variety of commercial, corporate, and global crises using Tableau. Learners will study Tableau tools and techniques including discrete field, continuous field, measure, aggregations, granularity, groups, hierarchies, level of detail expressions, analytics, and mapping approaches. Students will also learn forecasting strategies and how to create interactive dashboards.

The syllabus

Introduction

  • How this course is structured
  • Get the materials
  • BONUS: Learning Path
  • Installing Tableau

Chart Types [Rotten Tomatoes Movie Ratings]

  • Updates on Udemy Reviews
  • Get Excited!
  • Get the Dataset
  • Barchart
  • Line Chart
  • Stacked Barchart
  • Histograms
  • Heatmaps
  • Treemaps (Part 1)
  • Treemaps (Part 2)
  • Bullet Graph
  • Combined Axis Chart (Part 1)
  • Combined Axis Chart (Part 2)
  • Dual Axis Chart
  • Scatterplot (Part 1)
  • Scatterplot (Part 2)
  • Cross-Tab
  • Bar-in-bar Chart !
  • Boxplots !
  • Using Mark Labels and Annotations
  • Adding Titles, Captions and Tooltips
  • Editing Axes
  • Additional Reading
  • Homework Challenge
  • Homework Solution

Tableau Fundamentals part l [NBA Basketball Teams]

  • Get Excited!
  • Get the Dataset
  • Navigating Tableau
  • Using "Show Me"
  • Using Tableau-generated fields
  • Discrete vs Continuous Fields | Slides
  • Discrete vs Continuous Fields (Practical)
  • Dimensions vs Measures | Slides
  • Aggregation and Granularity (Part 1)
  • Aggregation and Granularity (Part 2)
  • Aggregation and Granularity (Part 3)
  • The 4 Roles of Data Fields | Slides
  • Dimensions (Discrete & Continuous) - Advanced Tutorial
  • Measures (Discrete & Continuous) - Advanced Tutorial
  • Default Aggregation
  • Aggregating Dimensions
  • Data Types in Tableau | Slides
  • Saving a Tableau Packaged Workbook *.twbx
  • Section recap
  • Additional Resource

Tableau Fundamentals part ll [LeBron James vs Michael Jordan]

  • Get Excited!
  • Get the Dataset & Challenge | Connect to the data here as well
  • Date is (almost) Always a Dimension
  • Discrete vs Continuous Date Fields
  • Datepart vs Datetrunc | Slides
  • Datepart vs Datetrunc (Practical)
  • Discrete vs Continuous Date Fields (cont.) - Advanced Tutorial | Slides
  • Datepart (Discrete & Continuous) - Advanced Tutorial
  • Datetrunc (Discrete & Continuous) - Advanced Tutorial
  • Can Date be a Measure?
  • Section recap | PPT slides, quick
  • Homework Challenge
  • Homework Hint
  • Homework Solution

Organizing & Simplifying Data part l [WorldBank Economic Indicators]

  • Get Excited!
  • Get the Dataset & Challenge | Connect to the data here as well
  • Filter data - Dimension Filter
  • Filter data - Date Filter
  • Filter data - Measure Filter
  • Filter data - Relevant Values
  • Filter data - Top 10
  • Filter data - Context Filter (part 1)
  • Filter data - Context Filter (part 2)
  • Filter data - Context Filter (part 3)
  • Filter data - Context Filter (part 4)
  • Filter data - Scope of Filter
  • Add a Parameter - Filters
  • Homework Challenge
  • Homework Hint
  • Homework Solution

Organizing & Simplifying Data part ll [WorldBank Economic Indicators]

  • Get Excited!
  • Get the Dataset & Challenge | Connect to the data here as well
  • Sort data - Computed Sort
  • Sort Data - Manual Sort
  • Build Hierarchies
  • Build Groups - Visual Group
  • Build Groups - Using Labels
  • Build Sets - Static
  • Build Sets - Dynamic
  • Groups vs Sets
  • Build Sets - Combining Sets (part 1)
  • Build Sets - Combining Sets (part 2)
  • Build Sets - Parameter Control
  • Homework Challenge
  • Homework Hint
  • Homework Solution

Analytics [Spotify / Kaggle Dataset]

  • Get Excited!
  • Get the Dataset & Challenge | Connect to the data here as well
  • Reference Lines
  • Reference Bands
  • Reference Bands - Parameter Control (part 1)
  • Reference Bands - Parameter Control (part 2)
  • Data Highlighter
  • Trend Lines
  • Trend Model
  • Reference Distributions
  • Instant Analytics
  • Trend Lines Multiplot (not compulsory for exam)
  • Drag & Drop Analytics
  • Box Plots
  • Extra: Box Plots Theory
  • Bins & Histograms
  • Forecasting (part 1)
  • Forecasting (part 2)
  • Statistical Summary Card
  • Homework Challenge
  • Homework Hint
  • Homework Solution

Data Connections & Data Prep part I [Glassdoor Salaries Data]

  • Get Excited!
  • Get the Dataset & Challenge | Connect to the data here as well
  • Union
  • Union with Wildcard
  • Merging Mismatched Fields
  • Additional reading: Unions
  • Understanding how LEFT, RIGHT, INNER, and OUTER Joins Work
  • Joins with Duplicate Values
  • Joining on Multiple Fields
  • Single Connection Joins
  • Cross-Database (Multiple Connection) Joins
  • Union-Join-Union Challenge
  • Using Calculations in Join Clauses
  • Blending (Part 1)
  • Blending (Part 2)
  • Create a Calculated Field in a Blend

Data Connections & Data Prep part ll [Glassdoor Salaries Data]

  • Get Excited!
  • Get the Dataset
  • Connect to Different Data Source Types
  • Pivot
  • Data Interpreter
  • Automatic & Custom Split
  • Managing Data Properties (Names, Aliases, Types, Geographic Roles, Defaults)
  • Metadata Grid
  • Data Source Filters
  • Filetypes in Tableau | Slides
  • Live Connections vs Packaged Workbooks (*.TWB vs *.TWBX)
  • Metadata Properties vs Packaged Data Sources (*.TDS vs *.TDSX)
  • Tableau Extracts *.HYPER (vs *.TDE) (Part 1)
  • Tableau Extracts *.HYPER (vs *.TDE) (Part 2)
  • Data Extracts with Multiple Tables
  • Extract Limitations
  • Section Recap | PPT Slides, quick
  • Additional Resources

Mapping [AirBnb Dataset]

  • Get Excited!
  • Get the Dataset & Challenge | Connect to the data here as well
  • Modifying Locations
  • Navigating Maps
  • Map Options
  • Filtering Maps
  • Map Layering
  • Geographic Search
  • Lasso & Radial Selection
  • Custom Territories (Part 1)
  • Custom Territories (Part 2)
  • Custom Territories (Part 3)
  • Custom Territories (Part 4)
  • Using Latitude and Longitude Coordinates
  • Exploring our Map
  • Density Plots / Heat Maps
  • Dual Axis Map

Dashboards part I - Device Layouts [Govt Website Traffic Dataset]

  • Get Excited!
  • Get the Dataset & Challenge | Connect to the data here as well
  • Preparing the worksheets
  • Creating the dashboard
  • Dashboard Size
  • Device Preview & Adding Device Layouts (Part 1)
  • Device Preview & Adding Device Layouts (Part 2)
  • Auto-generating the Mobile Layout
  • Layout menu - Exam trick questions
  • Visual best practices for devices
  • Working with Hidden Sheets
  • Publishing & Sharing options
  • Share twbx as an Image
  • Share twbx as a PDF
  • Building a Story

Dashboards part II - Actions [Kiva Loans / Kaggle Dataset]

  • Get the Dataset & Challenge: Kiva Loans | Connect to the data here as well
  • Exploring the Dataset
  • Creating a Map of Kiva Loans (Part 1)
  • Creating a Map of Kiva Loans (Part 2)
  • Creating a Timeline of Funded Amounts
  • Creating a Barchart for Sector
  • Creating a Pie Chart of Split by Gender
  • Build the Kiva Loans Dashboard
  • Action: Filter
  • Action: Highlight
  • Action: Change Parameter
  • Action: Change Parameter (Exam insights: Aggregation)
  • Action: Change Parameter (Concatenation)
  • Action: Change Set Values (Part 1)
  • Action: Change Set Values (Part 2)
  • Action: Change Set Values (Exam tips)
  • Action: Go to Sheet
  • Action: Go to URL
  • Worksheet Actions
  • Displaying a numeric KPI
  • Additional Resources

Calculations part I [Australian Mock Startup Dataset]

  • Get Excited!
  • Get the Dataset & Challenge | Connect to the data here as well
  • Creating a Simple Calculated Field
  • String Calculated Field
  • Date Calculated Field
  • Row-Level vs Aggregated Calculations (Part 1)
  • Row-Level vs Aggregated Calculations (Part 2)
  • Row-Level vs Aggregated Calculations (Part 3)
  • Logic Statements (Part 1)
  • Logic Statements (Part 2)
  • Working with Parameters (Part 1)
  • Working with Parameters (Part 2)
  • Calculated Field In a Blend (Part 1)
  • Calculated Field In a Blend (Part 2)
  • Totals & Sub-totals
  • Ad-Hoc Calculations
  • Homework Challenge
  • Homework Hint
  • Homework Solution

Calculations part II - Table Calculations [Australian Mock Startup Dataset]

  • Get Excited!
  • Get the Dataset & Challenge | Connect to the data here as well
  • Quick Table Calculations: Percent of Total
  • Quick Table Calculations: Rank
  • Quick Table Calculations: Running Total
  • Nested Table Calculations
  • Quick Table Calculations: Moving Average
  • Quick Table Calculations: Difference
  • Quick Table Calculations: Percent Difference
  • Table Calculations Theory: Scope and Direction
  • Hands-on practice with Scope of Table Calculations (Part 1)
  • Hands-on practice with Scope of Table Calculations (Part 2)
  • Hands-on practice with Scope of Table Calculations (Part 3)
  • Custom Table Calculations
  • Hands-on practice with Direction of Table Calculations (Part 1)
  • Hands-on practice with Direction of Table Calculations (Part 2)
  • Table Calculations and Order of operations in Tableau
  • Additional Resources

Calculations part III - LOD Expressions [Australian Mock Startup Dataset]

  • Get Excited!
  • Get the Dataset & Challenge | Connect to the data here as well
  • Level Of Detail (LOD) Expressions Intuition | Slides (fast)
  • Use-Case #1: FIXED LOD - Percent of Total
  • LOD Planning
  • Building the LOD
  • Building the Visualization
  • FIXED LOD - Discussion
  • Use-Case #2: INCLUDE LOD - Average of Top Deals by Store
  • LOD Planning & Building
  • Building the Visualization
  • INCLUDE LOD - Discussion
  • Use-Case #3: EXCLUDE LOD - Comparative Sales Analysis
  • LOD Planning
  • Building the LOD
  • Building the Visualization
  • Building the Visualization - Add a Parameter
  • Building the Visualization - Add Colour
  • EXCLUDE LOD - Discussion (Part 1) (ATTR function)
  • EXCLUDE LOD - Discussion (Part 2)
  • Use-Case #4: Nested LODs
  • LOD Planning & Building - LOD A
  • LOD Planning & Building - LOD B
  • Building the Visualization
  • Nested LODs - Discussion (Part 1)
  • Nested LODs - Discussion (Part 2)
  • Top 15 LOD Expressions
  • Additional Reading
  • Homework Challenge - Cohort Analysis [Online Retail Store Dataset]
  • Homework Hint
  • Homework Solution Part 1
  • Homework Solution Part 2

Practice Exam

  • Practice Exam 1
  • Practice Exam 2

Practice Exam Guided Solutions - Exam

  • Solution to Question 1
  • Solution to Question 2
  • Solution to Question 3
  • Solution to Question 4
  • Solution to Question 5
  • Solution to Question 6
  • Solution to Question 7
  • Solution to Question 8
  • Solution to Question 9
  • Solution to Question 10
  • Solution to Question 11
  • Solution to Question 12
  • Solution to Question 13
  • Solution to Question 14
  • Solution to Question 15
  • Solution to Question 16
  • Solution to Question 17
  • Solution to Question 18
  • Solution to Question 19
  • Solution to Question 20
  • Solution to Question 21
  • Solution to Question 22
  • Solution to Question 23
  • Solution to Question 24
  • Solution to Question 25
  • Solution to Question 26
  • Solution to Question 27
  • Solution to Question 28
  • Solution to Question 29
  • Solution to Question 30
  • Solution to Question 31
  • Solution to Question 32
  • Solution to Question 33
  • Solution to Question 34
  • Solution to Question 35
  • Solution to Question 36

Practice Exam Guided Solutions - Exam 2

  • Solution to Question 1
  • Solution to Question 2
  • Solution to Question 3
  • Solution to Question 4
  • Solution to Question 5
  • Solution to Question 6
  • Solution to Question 7
  • Solution to Question 8
  • Solution to Question 9
  • Solution to Question 10
  • Solution to Question 11
  • Solution to Question 12
  • Solution to Question 13
  • Solution to Question 14
  • Solution to Question 15
  • Solution to Question 16
  • Solution to Question 17
  • Solution to Question 18
  • Solution to Question 19
  • Solution to Question 20
  • Solution to Question 21
  • Solution to Question 22
  • Solution to Question 23
  • Solution to Question 24
  • Solution to Question 25
  • Solution to Question 26
  • Solution to Question 27
  • Solution to Question 28
  • Solution to Question 29
  • Solution to Question 30
  • Solution to Question 31
  • Solution to Question 32
  • Solution to Question 33
  • Solution to Question 34
  • Solution to Question 35
  • Solution to Question 36

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Instructors

Mr Kirill Eremenko

Mr Kirill Eremenko
Data Scientist
Udemy

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