Skill Analyses
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      Assessment Skills Catalogue

      Explore our skills catalogue for your hiring and assessment needs.

      Advanced Modeling – Deep Learning

      • Applications of deep learning

      • Applying natural language processing with deep learning

      • Building deep learning architectures

      • Executing deep learning

      • Framing deep learning

      • Introduction to deep learning

      • Preparing data for deep learning

      Advanced Modeling – Machine Learning

      • Deploying machine learning

      • Executing machine learning

      • Machine learning data

      Artificial Intelligence

      • Applying AI in organizations
      • Designing human-centered AI products
      • Evaluating AI product performance
      • Introduction to boosting productivity with AI
      • Prioritizing AI initiatives

      Databases & Wrangling

      • Applying OLAP/OLTP and implementing databases
      • Data structure and formatting
      • Describing data essentials
      • Feature engineering
      • Integrating and managing data
      • Managing processing and workflow
      • Selecting and working with databases and warehouses

      Data Essentials

      • Applying data storytelling

      • Comparing methods

      • Describing data essentials

      • Designing charts

      • Identifying data and methods

      • Interpreting visuals

      • Selecting visuals

      • Using data 

      Data Quality

      • Exploring and analyzing data
      • Exploring data quality and structure 

      PySpark

      • Exploring data with PySpark
      • Modeling with PySpark
      • Wrangling data with PySpark

      Python

      •  Exploratory data analysis with Python
      • Modeling with Python
      • Working with Python
      • Wrangling data with Python

      Power BI

      • Analyzing data with Power BI
      • Reporting with Power BI

      Spreadsheets

      • Exploring data with spreadsheets
      • Working with spreadsheets
      • Wrangling data with spreadsheets

      SQL 

      • Exploring data with SQL
      • Working with SQL
      • Wrangling data with SQL

      Statistics

      • Advanced modeling

      • Applying classification and clustering

      • Applying natural language processing

      • Applying time series analysis

      • Data exploration and description

      • Hypothesis testing and inferential statistics

      • Regression and predictive modeling

      • Sampling techniques 

      Storytelling with Data

      • Applying data storytelling
      • Building data storytelling narratives
      • Choosing data storytelling elements
      • Connecting through data storytelling
      • Defining data storytelling audience/purpose
      • Designing Charts
      • Designing visual narrative text
      • Designing visual narrative
      • Gathering data for storytelling
      • Incorporating data in data storytelling
      • Interpreting charts
      • Presenting data stories
      • Selecting visuals
      • Structuring data storytelling narratives

      Partial List of Additional Topics

      • Applying data ethics
      • Applying data to decision-making
      • Citizen's guide to SQL
      • Collecting data for statistical analysis
      • Defining data roles
      • Designing a statistical study
      • Designing surveys
      • Establishing data governance
      • Establishing organizational data strategy
      • Framing data problems
      • Identifying chart types
      • Interpreting metrics
      • Interpreting statistical results
      • Interpreting statistics
      • Introduction to data wrangling
      • Introduction to reading charts
      • Introduction to visual literacy
      • Managing data innovation
      • Managing data projects
      • Protecting your data
      • Selecting data tools
      • Shaping organizational data culture
      • Uncovering the story in data
      • Working with dashboards

      We are continuously building new skills and can build custom skills upon request. If you require something not shown above, please reach out to support@quanthub.com .