Course 1291
Data literacy is the ability to read, use, understand, and communicate data as information. At the organisational level, it is the extent to which the organisation, 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 organisation.
In-Person
Online
In this course, you will learn how to:
Interpret and explain:
Use data in the:
Training Prerequisites
None.
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: Visualising 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: Visualising Data to Communicate Results
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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 organisations 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 business, healthcare, education, government, and more.
Organisations 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 organisation 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.
PDU Information for This Course:
