- Understand the intricacies of data insights.
- Communicate technical findings effectively.
- Translate data into actionable business recommendations.
Introduction to Fundamental Skills for Data Work: Data Analysis and Interpretation
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Overview
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Build comprehensive analytical skills to extract meaningful insights from data and influence business decisions through evidence-based recommendations. Gain hands-on experience with industry-standard tools including R, Python, SQL, and Excel. This learning path is perfect for aspiring and practicing data analysts who want to master the complete analytical life cycle, from data exploration to actionable business insights.
Syllabus
Courses under this program:
Course 1: Data Literacy: Exploring and Describing Data
-Learn the fundamentals of data fluency and how data can help you make better decisions.
Course 2: Statistics Foundations 1: The Basics
-Learn to understand your data using basics of statistics, such as defining the middle, mean, and median of your data set; measuring the standard deviation; and finding outliers.
Course 3: Statistics Foundations 2: Probability
-Learn to understand your data in beginner-friendly lessons, using probability. Topics include permutations, percentiles, how to use probability trees, and much more.
Course 4: Learning Data Analytics: 1 Foundations
-This course covers foundational data analysis skills such as thinking like an analyst, gathering useful data, SQL queries, data cleaning, and more. Are you ready to be an analyst?
Course 5: Data Analyst Mindset: 10 Nontechnical Ways to Influence Decisions
-Learn 10 fundamental non-technical skills that will set you up for success as a data analyst.
Course 6: Predictive Analytics Essential Training: Data Mining
-Get useful, real-world insights into using predictive analysis and data mining to solve problems.
Course 7: SQL: Data Reporting and Analysis
-Get the data you need for analysis and reporting by writing your own SQL code. Learn how to write basic SQL queries, sort and filter data, and join results from different tables.
Course 8: Power BI Data Methods
-Get a comprehensive overview of the data end of Power BI—also known as Power Query—and learn how to use it to automate the data querying process and restructuring of data sets.
Course 1: Data Literacy: Exploring and Describing Data
-Learn the fundamentals of data fluency and how data can help you make better decisions.
Course 2: Statistics Foundations 1: The Basics
-Learn to understand your data using basics of statistics, such as defining the middle, mean, and median of your data set; measuring the standard deviation; and finding outliers.
Course 3: Statistics Foundations 2: Probability
-Learn to understand your data in beginner-friendly lessons, using probability. Topics include permutations, percentiles, how to use probability trees, and much more.
Course 4: Learning Data Analytics: 1 Foundations
-This course covers foundational data analysis skills such as thinking like an analyst, gathering useful data, SQL queries, data cleaning, and more. Are you ready to be an analyst?
Course 5: Data Analyst Mindset: 10 Nontechnical Ways to Influence Decisions
-Learn 10 fundamental non-technical skills that will set you up for success as a data analyst.
Course 6: Predictive Analytics Essential Training: Data Mining
-Get useful, real-world insights into using predictive analysis and data mining to solve problems.
Course 7: SQL: Data Reporting and Analysis
-Get the data you need for analysis and reporting by writing your own SQL code. Learn how to write basic SQL queries, sort and filter data, and join results from different tables.
Course 8: Power BI Data Methods
-Get a comprehensive overview of the data end of Power BI—also known as Power Query—and learn how to use it to automate the data querying process and restructuring of data sets.
Taught by
Barton Poulson, PhD, Eddie Davila, Robin Hunt, Mico Y., Keith McCormick, Emma Saunders and Helen Wall