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Data Analytics Foundations

See how data analytics drives smarter decisions across industries. You'll build a solid foundation in statistical modeling and learn to translate raw data into clear, actionable insights. This beginner-friendly course is a strong starting point for putting data to work in business today.

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  • 18 and older
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  • 185 Madison Ave, New York, NY & Virtually Online

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  • Mon, Nov 16 at 10:00am - 5:00pm
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Class Description

Description

Begin your exploration of data analytics and discover its applications across diverse industries and organizational contexts. You will develop a foundational understanding of statistical modeling techniques and practice using data-driven insights to forecast upcoming trends and make informed decisions that drive business success.

Learn the Fundamentals of Data Analytics:

In this beginner-friendly course, you will learn the essential elements of the data analytics process, including the core concepts of descriptive statistics, inferential statistics, and understanding data distributions and patterns.

Use Data to Drive Strategic Decision-Making:

Organizations everywhere rely on predictive and prescriptive analytics to forecast future outcomes and make critical business decisions. This course explores how different industries and organizations apply data strategically, what analytical tools they employ, and how big data influences modern business practices and competitive positioning.

Explore Statistical Analysis and Modeling Techniques:

You will learn about statistical algorithms, mathematical theorems, and analytical models that professionals use to extract insights from complex data sets.

Learn more about Data Analytics Foundations at Noble Desktop.

Syllabus

Basic Data Analysis

  • Measures of Central Tendency
  • Measures of Position
  • Measures of Dispersion
  • The Normal Curve
  • Descriptive Statistics

Predictive Analytics I

  • Forecasting
  • Series Forecast

Data Visualization I

  • Charts
  • Icon Sets
  • Histograms
  • Moving Average

Predictive Analytics

  • Correlation
  • Regression - overview
  • Regression - analysis
  • Linear regression
  • Multiple regression

Probability

  • Probability I
  • Probability II
  • Binomial Probability
  • Poisson Probability

Prescriptive Analytics I

  • What If Analysis
  • Data Table (3 variables)
  • Scenario Manager
  • Scenario Manager - Pivot

Data Visualization II

  • Sparklines
  • Color Scales
  • Drawing Shapes
  • Pivot Tables
  • Pivot Charts

Prescriptive Analytics II

  • Solver - overview
  • Linear Programming
  • The Solver model
  • Non-Linear Programming
  • Evolutionary Solver

Refund Policy

  • Students may cancel up to 14 days before the class/program start date and receive a refund, less the registration fee (10% of the undiscounted course price). 
  • Cancellations within 14 days are not permitted, but students may reschedule up to three business days before the class start date.
  • For cancellations and reschedules, please email us at [email protected]

In any event where a customer wants to cancel their enrollment and is eligible for a full refund, a 5% processing fee will be deducted from the refund amount.

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