Data Visualization Nanodegree
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Nanodegree key: nd197
Version: 1.0.0
Locale: en-us
Content
Part 01 : Welcome to the Nanodegree Program
- Module 01: Orientation Course
- Lesson 01: Welcome to the Data Visualization Nanodegree programWelcome to the Data Visualization Nanodegree program! In this lesson, you will learn more about the structure of the program and meet the team.
- Concept 01: Nanodegree Introduction
- Concept 02: How can I apply the skills I learn to my job?
- Concept 03: What you will build
- Concept 04: Pre-requisites
- Lesson 02: Welcome to UdacityYou are starting a challenging but rewarding journey! Take 5 minutes to read how to get help with projects and content.
- Concept 01: What It Takes
- Concept 02: Project Reviews
- Concept 03: Knowledge
- Concept 04: Mentors and Student Hub
- Concept 05: Community Initiatives
- Concept 06: Meet the Careers Team
- Concept 07: Introduction to the Career Portal
- Concept 08: Access Your Career Portal
- Concept 09: Your Udacity Professional Profile
- Concept 10: Prepare for the Udacity Talent Program
- Lesson 03: Get Help with Your AccountWhat to do if you have questions about your account or general questions about the program.
- Concept 01: FAQ
- Concept 02: Support
- Lesson 04: Introduction to Data Visualization Nanodegree programWelcome to the Data Visualization Nanodegree program! In this lesson, you will learn more about the structure of the program and meet the team.
- Concept 01: Meet your instructors
- Concept 02: Day in the Life: Instructor Interview
- Concept 03: Skills you’ll learn in this program
- Lesson 01: Welcome to the Data Visualization Nanodegree programWelcome to the Data Visualization Nanodegree program! In this lesson, you will learn more about the structure of the program and meet the team.
Module 02: Careers Services Orientation
- Lesson 01: Nanodegree Career ServicesThe Careers team at Udacity is here to help you move forward in your career - whether it’s finding a new job, exploring a new career path, or applying new skills to your current job.
Module 01: Intro to Data Visualization
- Lesson 01: Data Visualization FundamentalsIn this lesson you learn to evaluate the quality of data visualizations and build high quality visualizations, starting with the fundamentals of data dashboards.
- Concept 01: Data Visualization Introduction
- Concept 02: Why Do We Use Data Visualizations?
- Concept 03: Motivation for Data Visualization
- Concept 04: Further Motivation
- Concept 05: Data Types Review
- Concept 06: Identifying Data Types
- Concept 07: Univariate Plots
- Concept 08: Univariate Plots
- Concept 09: Scatter Plots
- Concept 10: Quizzes On Scatter Plots
- Concept 11: Correlation Coefficients
- Concept 12: Correlation Coefficient Quizzes
- Concept 13: Line Plots
- Concept 14: What is the Question?
- Concept 15: What About with More Than Two Variables?
- Concept 16: Multiple Variables Quiz
- Concept 17: Why Data Dashboards
- Concept 18: Introduction to Data Dashboards
- Concept 19: Quiz On Visual Encodings
- Concept 20: Recap
- Concept 21: What’s Next?
- Lesson 02: Design PrinciplesIn this lesson you learn to implement the best design practices, and to use the most appropriate chart for a particular situation.
- Concept 01: Introduction
- Concept 02: Lesson Overview
- Concept 03: Exploratory vs. Explanatory Analyses
- Concept 04: Quiz: Exploratory vs. Explanatory
- Concept 05: What Makes a Bad Visual?
- Concept 06: What Experts Say About Visual Encodings
- Concept 07: Chart Junk
- Concept 08: Data Ink Ratio
- Concept 09: Design Integrity
- Concept 10: Bad Visual Quizzes (Part I)
- Concept 11: Bad Visual Quizzes (Part II)
- Concept 12: Text: Effective Explanatory Visual Recap
- Concept 13: Using Color
- Concept 14: Designing for Color Blindness
- Concept 15: Shape, Size, & Other Tools
- Concept 16: General Design Tips
- Concept 17: Good Visual
- Concept 18: Tell A Story
- Concept 19: Same Data, Different Stories
- Concept 20: Quizzes on Data Story Telling
- Concept 21: Recap
- Concept 22: Onwards!
- Lesson 03: Creating Visualizations in TableauThis lesson teaches you how build data visualizations in Tableau using data hierarchies, filters, groups, sets, and calculated fields, as well as create map-based data visualizations in Tableau.
- Concept 01: Video: What is Tableau?
- Concept 02: Text: Installing Tableau
- Concept 03: Video: How This Lesson Is Structured?
- Concept 04: Text: Outline of Topics Covered
- Concept 05: Commas vs Periods
- Concept 06: Video: Connecting to Data
- Concept 07: Text: Connecting to Data Recap
- Concept 08: Quiz: Connecting to Data
- Concept 09: Video: Combining Data
- Concept 10: Text: Combining Data Recap
- Concept 11: Quiz: Combining Data
- Concept 12: Video: What Can You Create In Tableau?
- Concept 13: Video: Worksheets
- Concept 14: Text: Worksheets
- Concept 15: Quiz: Worksheets
- Concept 16: Text: Saving to Tableau Public
- Concept 17: Video: Aggregations
- Concept 18: Text: Aggregations
- Concept 19: Quiz: Aggregations
- Concept 20: Video: Hierarchies
- Concept 21: Text: Hierarchies
- Concept 22: Quiz: Hierarchies
- Concept 23: Video: Marks & Filters
- Concept 24: Text: Marks & Filters I
- Concept 25: Quiz: Marks & Filters I
- Concept 26: Text: Marks & Filters II
- Concept 27: Quiz: Marks & Filters II
- Concept 28: Video: Show Me
- Concept 29: Text: Show Me
- Concept 30: Quiz: Show Me
- Concept 31: Video: Small Multiples & Dual Axis
- Concept 32: Text: Small Multiples & Dual Axis
- Concept 33: Text: Map Configuration
- Concept 34: Quiz: Small Multiples
- Concept 35: Quiz: Dual Axis
- Concept 36: Video: Groups & Sets
- Concept 37: Text: Groups & Sets
- Concept 38: Quiz: Groups
- Concept 39: Quiz: Sets
- Concept 40: Video: Calculated Fields
- Concept 41: Text: Calculated Fields
- Concept 42: Quiz: Calculated Fields
- Concept 43: Video: Table Calculations
- Concept 44: Text: Table Calculations
- Concept 45: Quiz: Table Calculations
- Concept 46: Text: Recap
- Concept 47: Video: What’s Next?
- Lesson 04: Telling Stories with TableauIn this final lesson you learn how to build interactive Tableau dashboards and tell impactful stories using data.
- Concept 01: Video: Communicating With Your Data
- Concept 02: Video + Text: What’s Ahead?
- Concept 03: Video: Hierarchies with Trina
- Concept 04: Quiz: Hierarchies with Trina
- Concept 05: Video: Building Dashboards & Stories with Trina
- Concept 06: Text: General Notes for Building Data Dashboards with Trina
- Concept 07: Text: General Notes for Building Stories
- Concept 08: Quiz: Building Dashboards & Stories with Trina
- Concept 09: Video: Extra Practice with Dashboards
- Concept 10: Quiz: Extra Practice with Dashboards
- Concept 11: Text: Lesson Recap
- Concept 12: Video: Congratulations!
- Lesson 05: Build a Data Visualization projectIn this project, you’ll build interactive dashboards with Tableau and use them to discover and communicate insights from data.Project Description - Build Data DashboardsProject Rubric - Build Data Dashboards
- Lesson 01: Data Visualization FundamentalsIn this lesson you learn to evaluate the quality of data visualizations and build high quality visualizations, starting with the fundamentals of data dashboards.
Module 01: Dashboard Design
- Lesson 01: Planning PhaseIn order to design a dashboard that meets our users needs we need to first understand what they are after and what are their pain points. Early discussions are critical in the planning phase.
- Concept 01: Meet your Instructor
- Concept 02: Welcome to Dashboard Design
- Concept 03: Welcome to Lesson 1
- Concept 04: Getting to Know your Audience
- Concept 05: Audience Attributes
- Concept 06: Exercise 1
- Concept 07: Audience Motivations
- Concept 08: Example Dashboards
- Concept 09: Audience Dimensions
- Concept 10: Pain points
- Concept 11: Demo 1
- Concept 12: Exercise 2
- Concept 13: Pulling Data from Priorities
- Concept 14: Demo 2
- Concept 15: Check in With Stakeholders
- Concept 16: Exercise 3
- Concept 17: Stating Your Objective
- Concept 18: Demo 3
- Concept 19: Exercise 4
- Concept 20: Conclusion
- Lesson 02: Design PhaseStudents will learn about the design phase of creating their dashboards. This includes considering graphicacy, chart choice, visual hiearchy. Tools like sketching and wireframing are practiced.
- Concept 01: Design Phase
- Concept 02: Graphicacy
- Concept 03: Graphicacy Examples
- Concept 04: Demo 1
- Concept 05: Quiz
- Concept 06: Exercise 1
- Concept 07: Chart Choice
- Concept 08: Exercise 2
- Concept 09: Visual Hierarchy
- Concept 10: Demo 2
- Concept 11: Exercise 3
- Concept 12: Wireframing
- Concept 13: Demo 3
- Concept 14: Exercise 4
- Concept 15: Layouts
- Concept 16: Common Layouts
- Concept 17: Alignment
- Concept 18: Quiz 2
- Concept 19: Building your prototype
- Concept 20: Handling Text
- Concept 21: Conclusion
- Lesson 03: Design a Data Dashboard Midterm ProjectIn this project, you will build a dashboard prototype along with sketches and wireframes for the prototype. The dashboard will be designed based on the Superstore database from Tableau.Project Description - Design a Data Dashboard Midterm ProjectProject Rubric - Design a Data Dashboard Midterm Project
- Concept 01: Overview
- Concept 02: Instructions
- Concept 03: Dataset
- Lesson 04: Polishing Dashboards for ProductionIn this lesson, students will learn how to design the final dashboard by attending to the text hierarchy, affordance, interactivity of the dashboard, annotations, and color scheme.
- Concept 01: Introduction
- Concept 02: Color
- Concept 03: Color is Difficult
- Concept 04: Encoding
- Concept 05: Quiz 1
- Concept 06: Colors and Culture
- Concept 07: Coloring KPIs
- Concept 08: Quiz 2
- Concept 09: Demo 1
- Concept 10: Common Color Mistakes
- Concept 11: Dual Encoding
- Concept 12: Challenge Encoding
- Concept 13: Color blindness VS confusion
- Concept 14: Tools
- Concept 15: Exercise 1
- Concept 16: Solution to Exercise 1
- Concept 17: Interactivity
- Concept 18: Interaction Design
- Concept 19: Affordance
- Concept 20: Interaction Types
- Concept 21: Interactions as Targets
- Concept 22: Quiz 3
- Concept 23: Fitt’s Law
- Concept 24: Schneiderman’s Mantra
- Concept 25: Annotations
- Concept 26: What is an Annotation
- Concept 27: Annotation Example 1
- Concept 28: Annotation Anatomy
- Concept 29: Annotation Example 2
- Concept 30: Context
- Concept 31: Quiz 4
- Concept 32: Course Conclusion
- Lesson 05: Design a Data Dashboard Final ProjectIn this final project, students complete the dashboard they designed in the mid-point. They will add color, annotations, interactivity and make it production ready.Project Description - Design a Data Dashboard Final ProjectProject Rubric - Design a Data Dashboard Final Project
- Lesson 01: Planning PhaseIn order to design a dashboard that meets our users needs we need to first understand what they are after and what are their pain points. Early discussions are critical in the planning phase.
Module 01: Data Storytelling
- Lesson 01: Define Problem StatementIn this lesson students will understand how to clearly articulate the problem statement that is driving the analysis, and why it matters.
- Concept 01: Meet Your Instructor
- Concept 02: Data Storytelling: Course Outline
- Concept 03: What is a Data Story?
- Concept 04: Why is Storytelling Important?
- Concept 05: Effective Data Story
- Concept 06: What is a Problem Statement?
- Concept 07: Merits of Effective Statement
- Concept 08: Ineffective Problem Statement
- Concept 09: Demo 1
- Concept 10: Exercise 1
- Concept 11: Solution to Exercise 1
- Concept 12: Conclusion
- Lesson 02: Issue Trees and Building a Ghost DeckIn this lesson students will learn to build an analysis roadmap to stay efficient with your analysis time. An analysis roadmap consists of two key elements: (1) an issue tree and (2) a ghost deck.
- Concept 01: Introduction to Lesson
- Concept 02: Structure a problem
- Concept 03: Issue Trees
- Concept 04: Hypothesis Driven Structuring
- Concept 05: Demo 1
- Concept 06: Exercise 1
- Concept 07: Solution to Exercise 1
- Concept 08: Exercise 2
- Concept 09: Solution to Exercise 2
- Concept 10: What goes into ghost deck
- Concept 11: Strong Syntheses
- Concept 12: Logical train of thought
- Concept 13: Caveats
- Concept 14: Demo 2
- Concept 15: Solution Demo 2
- Concept 16: Exercise 3
- Concept 17: Solution to Exercise 3
- Concept 18: Conclusion
- Lesson 03: Build a Data Story Midterm ProjectProject Description - Build a Data Story Midterm ProjectProject Rubric - Build a Data Story Midterm Project
- Concept 01: Introduction
- Concept 02: Instructions
- Concept 03: Dataset
- Lesson 04: Limitations and BiasesThe data you work with is flawed and in this lesson students will learn where bias can be introduced in the collection, processing, and analysis process and call these caveats out.
- Concept 01: Lesson outline
- Concept 02: Overview of biases
- Concept 03: Biases in Data Collection
- Concept 04: Biases in Data Collection Part 2
- Concept 05: Common Questions Asked
- Concept 06: Biases in Data Processing
- Concept 07: Dealing with Missingness
- Concept 08: Exercise 1
- Concept 09: Solution to Exercise 1
- Concept 10: Quiz 4
- Concept 11: Commonly Asked Questions II
- Concept 12: Biases in Data Insights
- Concept 13: Conclusion
- Lesson 05: Visualizations and Tying it TogetherThis lesson ties everything together. It covers effective visualizations depending on the problem you are solving, and reviewing a data presentation end to end.
- Concept 01: Visualizations and Tying Together
- Concept 02: Visualizations: Overview
- Concept 03: Relationships
- Concept 04: Comparison
- Concept 05: Temporal
- Concept 06: Distributions
- Concept 07: Metric Output
- Concept 08: Exercise 1
- Concept 09: Data Normalization
- Concept 10: Solution: FIFA Visualizations 1
- Concept 11: FIFA: Visualization 2
- Concept 12: FIFA: Visualization 3
- Concept 13: Tying it together
- Concept 14: FIFA End to End
- Concept 15: FIFA: Overview of Analysis 1
- Concept 16: FIFA: Overview of Analysis 2
- Concept 17: FIFA: Limitations and Biases
- Concept 18: FIFA: Next Steps
- Concept 19: Lesson recap
- Concept 20: Course recap
- Lesson 06: Build a Data Story Final ProjectProject Description - Build a Data Story Final ProjectProject Rubric - Build a Data Story Final Project
- Lesson 01: Define Problem StatementIn this lesson students will understand how to clearly articulate the problem statement that is driving the analysis, and why it matters.
Module 01: Advanced Data Storytelling
- Lesson 01: Eight Data Story TypesStudents learn about sequential data stories, and how eight different story types can be used to find and tell interesting data stories.
- Concept 01: Meet Your Instructor
- Concept 02: Advanced data storytelling course
- Concept 03: What is a Data Story
- Concept 04: Eight data story types
- Concept 05: 1. Change over time
- Concept 06: 2. Hierarchy drill down
- Concept 07: 3. Zoom in/Out
- Concept 08: Quiz
- Concept 09: 4. Contrasting values
- Concept 10: 5. Intersections
- Concept 11: 6. Different factors
- Concept 12: 7. Outliers
- Concept 13: 8. Correlation
- Concept 14: Data Storytelling
- Concept 15: Conclusion
- Lesson 02: Creating stories in TableauStudents will learn how to tell interactive stories by creating stories in Tableau. They will learn how to add a Hans Rosling bubble chart to Tableau and how to create a Tableau Storypoint Workbook.
- Concept 01: Creating a Story in Tableau
- Concept 02: Creating a New Story
- Concept 03: Adding Sheets to a Story
- Concept 04: Exercise 1
- Concept 05: Solution for Exercise 1
- Concept 06: Annotating story points
- Concept 07: Exercise 2
- Concept 08: Solution: Exercise 2
- Concept 09: Adding Dashboards to Stories
- Concept 10: Exercise 3
- Concept 11: Solution: Exercise 3
- Concept 12: Formatting Dashboards
- Concept 13: Exercise 4
- Concept 14: Solution: Exercise 4
- Concept 15: Conclusion
- Lesson 03: Animate a Data Story Midterm ProjectIn this lesson, students will apply the skills they have acquired in this Advanced Data Storytelling course to use the World Bank Indicators data file to create an interactive Tableau Story.Project Description - Animate a Data Story Midterm ProjectProject Rubric - Animate a Data Story Midterm Project
- Concept 01: Introduction
- Concept 02: Dataset
- Concept 03: Instructions
- Lesson 04: Animating VisualizationsStudents will use datasets for animating data and build out animations with Tableau pages and get introduced to Flourish.
- Concept 01: Animating Visualizations
- Concept 02: Why Animations?
- Concept 03: Animating Using Tableau Pages
- Concept 04: Quiz 1
- Concept 05: Exercise 1
- Concept 06: Introduction to Flourish
- Concept 07: Importing Data
- Concept 08: Selecting Data Column
- Concept 09: Exercise 2
- Concept 10: Solution to Exercise 2
- Concept 11: Formatting in Flourish
- Concept 12: Solution to Exercise 3
- Concept 13: Animating
- Concept 14: Solution to Exercise 4
- Concept 15: Other Tools to Animate
- Concept 16: Conclusion and What’s Next
- Lesson 05: Animation and NarrationStudents will learn how to add audio and narration to their data stories using Flourish, including setting up the files, charts, animation and audio files to create interactive stories.
- Concept 01: Lesson intro
- Concept 02: Create new story Flourish
- Concept 03: Solution to Exercise 1
- Concept 04: Adding New Slides and Narrative Text
- Concept 05: Solution Exercise 2
- Concept 06: Recording an Audio File to MP3
- Concept 07: Adding audio to your story
- Concept 08: Playing & Sharing Your Narrated Story
- Concept 09: Lesson congratulations
- Concept 10: Course recap
- Lesson 06: Animate a Data Story Final ProjectIn this lesson, students will create an animated data story and add an audio track to create a narrated Flourish story that they can add to their portfolio.Project Description - Animate a Data Story Final ProjectProject Rubric - Animate a Data Story Final Project
- Concept 01: Introduction
- Concept 02: Dataset
- Concept 03: Instructions
Part 06 : Career Services
These Career Services will ensure you make meaningful connections with industry professionals to accelerate your career growth - whether looking for a job or opportunities to collaborate with your peers. Unlike your Nanodegree projects, you do not need to meet specifications on these Services to progress in your program. Submit these Career Services once, and get honest, personalized feedback and next steps from Udacity Career Coaches!
- Lesson 01: Eight Data Story TypesStudents learn about sequential data stories, and how eight different story types can be used to find and tell interesting data stories.
Module 01: Career Services
- Lesson 01: Industry ResearchYou’re building your online presence. Now learn how to share your story, understand the tech landscape better, and meet industry professionals.
- Concept 01: Self-Reflection: Design Your Blueprint for Success
- Concept 02: Debrief: Self-Reflection Exercise Part 1
- Concept 03: Debrief: Self-Reflection Exercise Part 2
- Concept 04: Map Your Career Journey
- Concept 05: Debrief: Map Your Career Journey
- Concept 06: Conduct an Informational Interview
- Concept 07: How to Request an Informational Interview
- Concept 08: Ways to Connect
- Concept 09: Ask Good Questions
- Concept 10: Debrief: Sample Questions Quiz
- Concept 11: Keep the Conversation Going
- Lesson 02: Take 30 Min to Improve your LinkedInFind your next job or connect with industry peers on LinkedIn. Ensure your profile attracts relevant leads that will grow your professional network.Project Description - Improve Your LinkedIn ProfileProject Rubric - Improve Your LinkedIn Profile
- Concept 01: Get Opportunities with LinkedIn
- Concept 02: Use Your Story to Stand Out
- Concept 03: Why Use an Elevator Pitch
- Concept 04: Create Your Elevator Pitch
- Concept 05: Use Your Elevator Pitch on LinkedIn
- Concept 06: Create Your Profile With SEO In Mind
- Concept 07: Profile Essentials
- Concept 08: Work Experiences & Accomplishments
- Concept 09: Build and Strengthen Your Network
- Concept 10: Reaching Out on LinkedIn
- Concept 11: Boost Your Visibility
- Concept 12: Up Next
- Lesson 03: Resume ReviewImprove your resume by getting personalized feedback on how you communicate your qualifications for a job.Project Description - Resume Review Career ServiceProject Rubric - Resume Review Career Service
- Lesson 01: Industry ResearchYou’re building your online presence. Now learn how to share your story, understand the tech landscape better, and meet industry professionals.
Module 01: Capstone
- Lesson 01: Capstone ProjectNow you will put your data visualization skills to the test by solving a real world problem using all that you have learned throughout the program.Project Description - Capstone ProjectProject Rubric - Capstone Project
- Concept 01: Project Overview
- Concept 02: Project Resources
- Concept 03: Text: Medium Getting Started Post and Links
- Concept 04: Video: Three Steps to Captivate Your Audience
- Concept 05: Video: First Catch Their Eye
- Concept 06: Picture First, Title Second
- Concept 07: Video: More Advice
- Concept 08: More Advice
- Concept 09: Video: End With A Call To Action
- Concept 10: End With A Call To Action
- Concept 11: Project Instructions
Part 08 : Congratulations
- Lesson 01: Capstone ProjectNow you will put your data visualization skills to the test by solving a real world problem using all that you have learned throughout the program.Project Description - Capstone ProjectProject Rubric - Capstone Project
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Part 09 (Elective)__ : [Supplemental] Introduction to Data
Module 01: Introduction to Data
- Lesson 01: Descriptive Statistics IIn this lesson, you will learn about data types, measures of center, and the basics of statistical and mathematical notation.
- Concept 01: Video: Welcome!
- Concept 02: Video: What is Data? Why is it important?
- Concept 03: Video: Data Types (Quantitative vs. Categorical)
- Concept 04: Quiz: Data Types (Quantitative vs. Categorical)
- Concept 05: Video: Data Types (Ordinal vs. Nominal)
- Concept 06: Video: Data Types (Continuous vs. Discrete)
- Concept 07: Video: Data Types Summary
- Concept 08: Text + Quiz: Data Types (Ordinal vs. Nominal)
- Concept 09: Data Types (Continuous vs. Discrete)
- Concept 10: Video: Introduction to Summary Statistics
- Concept 11: Video: Measures of Center (Mean)
- Concept 12: Measures of Center (Mean)
- Concept 13: Video: Measures of Center (Median)
- Concept 14: Measures of Center (Median)
- Concept 15: Video: Measures of Center (Mode)
- Concept 16: Measures of Center (Mode)
- Concept 17: Video: What is Notation?
- Concept 18: Video: Random Variables
- Concept 19: Quiz: Variable Types
- Concept 20: Video: Capital vs. Lower
- Concept 21: Quiz: Introduction to Notation
- Concept 22: Video: Better Way?
- Concept 23: Video: Summation
- Concept 24: Video: Notation for the Mean
- Concept 25: Quiz: Summation
- Concept 26: Quiz: Notation for the Mean
- Concept 27: Text: Summary on Notation
- Lesson 02: Descriptive Statistics IIIn this lesson, you will learn about measures of spread, shape, and outliers as associated with quantitative data. You will also get a first look at descriptive and inferential statistics.
- Concept 01: Video: What are Measures of Spread?
- Concept 02: Video: Histograms
- Concept 03: Video: Weekdays vs. Weekends: What is the Difference
- Concept 04: Video: Introduction to Five Number Summary
- Concept 05: Quiz: 5 Number Summary Practice
- Concept 06: Video: What if We Only Want One Number?
- Concept 07: Video: Introduction to Standard Deviation and Variance
- Concept 08: Video: Standard Deviation Calculation
- Concept 09: Measures of Spread (Calculation and Units)
- Concept 10: Text: Introduction to the Standard Deviation and Variance
- Concept 11: Video: Why the Standard Deviation?
- Concept 12: Video: Important Final Points
- Concept 13: Advanced: Standard Deviation and Variance
- Concept 14: Quiz: Applied Standard Deviation and Variance
- Concept 15: Homework 1: Final Quiz on Measures Spread
- Concept 16: Text: Measures of Center and Spread Summary
- Concept 17: Video: Shape
- Concept 18: Video: The Shape For Data In The World
- Concept 19: Quiz: Shape and Outliers (What’s the Impact?)
- Concept 20: Video: Shape and Outliers
- Concept 21: Video: Working With Outliers
- Concept 22: Video: Working With Outliers My Advice
- Concept 23: Quiz: Shape and Outliers (Comparing Distributions)
- Concept 24: Quiz: Shape and Outliers (Visuals)
- Concept 25: Quiz: Shape and Outliers (Final Quiz)
- Concept 26: Text +Quiz: What Measures of Spread & Center Should We Use?
- Concept 27: Text: Descriptive Statistics Summary
- Concept 28: Video: Descriptive vs. Inferential Statistics
- Concept 29: Quiz: Descriptive vs. Inferential (Bagels)
- Concept 30: Quiz: Descriptive vs. Inferential (Udacity Students)
- Concept 31: Text: Descriptive vs. Inferential Summary
- Concept 32: Video: Summary
- Lesson 03: Spreadsheets 2: Manipulate DataIn this lesson, you will learn basic spreadsheet function: sort and filter data, use text and math functions, split columns and remove duplicates.
- Concept 01: Intro
- Concept 02: Cell Formulas
- Concept 03: Quiz: Spreadsheet Functions
- Concept 04: SUBSTITUTE
- Concept 05: Quiz: SUBSTITUTE
- Concept 06: Extract Text
- Concept 07: Exercise: Extract Text
- Concept 08: Reformat Text
- Concept 09: Quiz: PROPER, UPPER, LOWER
- Concept 10: Math Functions
- Concept 11: Exercise: Math Functions
- Concept 12: Duplicate Rows
- Concept 13: Exercise: Duplicate Rows
- Concept 14: Split Columns
- Concept 15: Exercise: Split Columns
- Concept 16: Sort Data
- Concept 17: Exercise: Sort Data
- Concept 18: Filter Data
- Concept 19: Exercise: Filter Data
- Concept 20: Recap
- Lesson 04: Spreadsheets 3: Analyze DataIn this lesson, you will learn how to summarize data with aggregation and conditional functions. You will learn how to use pivot tables and lookup functions.
- Concept 01: Intro
- Concept 02: Aggregation Functions
- Concept 03: Aggregation Functions
- Concept 04: Logical Functions: IF
- Concept 05: Quiz: Comparison Operators
- Concept 06: Logical Functions: AND, OR, NOT
- Concept 07: Quiz: Logical Functions
- Concept 08: Conditional Aggregation Functions
- Concept 09: Exercise: COUNTIF, SUMIF
- Concept 10: Pivot Tables
- Concept 11: Exercise: Pivot Tables
- Concept 12: Named Ranges
- Concept 13: Named Ranges
- Concept 14: Lookup Functions
- Concept 15: Exercise: VLOOKUP
- Concept 16: Recap
- Lesson 05: Spreadsheets 4: Visualize DataIn this lesson you will build data visualizations for quantitative and categorical data; create pie, bar, line, scatter, histogram, and boxplot charts, and build professional presentations.
- Concept 01: Intro
- Concept 02: Pie Charts
- Concept 03: Exercise: Pie Charts
- Concept 04: Bar Charts
- Concept 05: Scatter and Line Plots
- Concept 06: Quiz: Chart Types
- Concept 07: Exercise: Scatter Plots
- Concept 08: Chart Layout Tools
- Concept 09: Quiz: Chart Layout
- Concept 10: Histograms
- Concept 11: Quiz: Histograms
- Concept 12: Box Plots
- Concept 13: Quiz: Box Plots
- Concept 14: Professional Presentations
- Concept 15: Exercise: Professional Presentations
- Concept 16: Recap
- Lesson 01: Descriptive Statistics IIn this lesson, you will learn about data types, measures of center, and the basics of statistical and mathematical notation.
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