Introduction to Data Literacy Training

Course 1291

  • Duration: 2 days
  • Language: English
  • 11 PMI PDUs
  • Level: Foundation

Data literacy is the ability to read, use, understand, and communicate data as information. At the organizational level, it is the extent to which the organization, and its members, comprehends and communicates data to drive value. A data-literate workforce will be able to understand, share common knowledge of, and have meaningful conversations about data.

After taking this data literacy course, you'll be able to understand, use, read, and interpret enterprise data consistently and derive trusted insights. Your skills will be manifested in the execution of your role in the organization.

Data Literacy Training Delivery Methods

  • In-Person

  • Online

Data Literacy Training Information

In this course, you will learn how to:

Interpret and explain:

  • Straightforward statistical operations such as correlations or judge averages.
  • A business case based on concrete, accurate, and relevant data.
  • The output of the organization's systems or processes to stakeholders.
  • The output of machine learning algorithms.
  • The essence of data shared with colleagues or other organizations.

Use data in the:

  • Managing complex supply chains.
  • Understanding of market and customer requirements.
  • Driving product and service innovations.
  • Evaluation and monitoring of process efficiencies.
  • Mitigation of risks.
  • Spotting unexpected operational issues and identification of their root causes.

Training Prerequisites


Data Literacy Training Outline

Module 1: Qualitative vs. Quantitative Data
Module 2: Structured vs. Unstructured Data
Module 3: Data at Rest, in Use, and Motion
Module 4: Transactional vs. Master Data
Module 5: Big Data
Module 6: Storing Data
Module 7: Database
Module 8: Data Warehouse
Module 9: Data Marts
Module 10: The ETL Process
Module 11: Big Data Frameworks
Module 12: Cloud Systems
Module 13: Edge Computing
Module 14: Batch vs. Stream Processing
Module 15: Graph Database
Module 16: Visualizing unfamiliar data

Module 1: Analysis vs. Analytics
Module 2: Descriptive Statistics
Module 3: Inferential Statistics
Module 4: Business Intelligence (BI)
Module 5: Artificial Intelligence (AI)
Module 6: Machine Learning (ML)
Module 7: Supervised Learning
Module 8: Regression Analysis
Module 9: Time Series Forecasting
Module 10: Classification
Module 11: Unsupervised Learning
Module 12: Clustering
Module 13: Association Rules
Module 14: Reinforcement Learning
Module 15: Deep Learning
Module 16: Natural Language Processing (NLP)

Module 1: Data Quality Assessment
Module 2: Data Description
Module 3: Measures of Central Tendency
Module 1: Measures of Spread

Module 1: Correlation Analysis
Module 2: Correlation Coefficient
Module 3: Correlation and Causation
Module 4: Simple Linear Regression
Module 5: R-Squared
Module 6: Forecasting
Module 7: Forecast Errors
Module 8: Statistical Tests
Module 9: Hypothesis Testing
Module 10: P-Value
Module 11: Statistical Significance
Module 12: Classification
Module 13: Accuracy
Module 14: Recall and Precision
Module 15: Visualizing Data to Communicate Results

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Data Literacy Training FAQs

Data literacy is reading, understanding, creating and communicating data as information. It involves skills, knowledge, and the mindset necessary to use data effectively to make informed decisions.

Data is becoming increasingly important in many areas of work and life. Data literacy helps individuals and organizations make better decisions, solve complex problems, and identify new opportunities.

Anyone who works with data or needs to make data-driven decisions can benefit from this data literacy training course. This includes individuals in fields such as business, healthcare, education, government, and more.

Organizations can support employee data literacy by providing regular training programs, access to relevant data sets, and daily opportunities to apply their data skills. Promoting a data-driven culture and encouraging ongoing learning and development in data literacy is also essential.

Check out our free webinar on Data Literacy as a primer on this topic. You will learn how Data Literacy can help your organization get the most value from your data, and how understanding the Data language can help with your day-to-day work.

Certification candidates and existing credential holders are responsible for reporting all Continuing Certification Requirements Program (CCR) activities to PMI (Project Management Institute). To report the completion of a Learning Tree course, you can use the Online PDU (Professional Development Units) Resources System.

  • Go to the PMI Continuing Certification Requirements System
  • Log in with your username and password
  • Locate the claim code associated with your course in the table in this document
  • Click on “Report PDU for this activity”
  • Fill in the date started and date completed
  • Click on the box agreeing that this claim is accurate and then submit

PDU Information for This Course:

  • Total PDUs: 11
  • Ways of Working PDUs: 4
  • Power Skills PDUs: 0
  • Business Acumen PDUs: 7
  • PMI Claim Code: 1154M7RT4R
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