Visual Analytics – Data science Kurzusok

Kurzuskód

visa_LBG

Időtartalma

14 hours (usually 2 days including breaks)

Követelmények

Experience of analysis, statistics and producing data an advantage

Összefoglaló

Ez az osztálytermi képzés előadásokat és számítógépes példákat, valamint esettanulmány-gyakorlatokat fog tartalmazni.

Machine Translated

Kurzusleírás

  1. Introduction to Visual Analytics
    • 5 Principles of Data Visualisation
    • Tables vs charts
    • What makes visualisations effective
    • Gestalt Principles of Visual Perception
  2. Types of charts and how to choose the right one
    • Common types of charts
    • Choosing the right chart for your data
    • Understanding your audience
    • Handling missing data
  3. Advanced charts
    • Sankey
    • Radar
    • Treemap
    • Heatmap
    • Boxplot, violin plot
    • Choosing the right chart for your data
    • Choosing the right chart for your audience
    • Eliminating clutter from charts
  4. Storytelling with data
    • The importance of storytelling
    • Building a narrative structure
    • Drawing attention
    • Including call to action
  5. Creating dashboards and infographics
    • Exploratory vs explanatory analysis
    • How to convey your message
    • Live presentation vs report
    • Visualisations that are simple, informative and engaging
    • The characteristics of a good dashboard
    • The characteristics of a good infographic
  6. Common mistakes and misleading charts
    • Charts that should be avoided
    • How we are being deceived by colour, scale and size
  7. Visual analytics case studies

 

Vélemények

★★★★★
★★★★★

Rokon kategóriák

Rokon tanfolyam

Kedvezmények tanfolyamokra

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Néhány ügyfelünk

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  • creating new courses outlines
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At the moment we are focusing on the following areas:

  • Statistic, Forecasting, Big Data Analysis, Data Mining, Evolution Alogrithm, Natural Language Processing, Machine Learning (recommender system, neural networks .etc...)
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