Course Description:



The Lean Business & Data Analytics Specialized Skill Program provides an applied pathway for professionals seeking to use data to solve business problems, improve processes, evaluate risk, and make better decisions.



The program takes learners through the complete analytics decision process, beginning with defining and prioritizing business problems and progressing through descriptive, predictive, and prescriptive analytics. Learners develop practical skills in data visualization, statistical analysis, probability, sampling and estimation, regression, forecasting, Monte Carlo simulation, and optimization.



Microsoft Excel serves as a primary analytical platform throughout the program, allowing learners to apply concepts directly to business-oriented problems, datasets, exercises, and decision scenarios.



A distinguishing feature of the program is its integration of analytics with continuous improvement and decision-making. Rather than learning analytical techniques in isolation, participants learn how to move from identifying a business problem to analyzing evidence, evaluating alternatives, predicting outcomes, managing uncertainty, and recommending data-supported actions.



From evidence to action, the program is designed to develop practical analytical capabilities that can be applied in today's data-driven workplace.



Upon successful completion of the program, learners will be able to:



• Define business problems and translate them into structured analytics projects.

• Prioritize improvement opportunities using business and analytical criteria.

• Prepare, organize, analyze, and visualize business data using Microsoft Excel.

• Apply descriptive statistics, probability, sampling, estimation, and statistical inference to business problems.

• Develop and interpret simple and multiple regression models.

• Apply forecasting and time-series techniques to support planning and decision-making.

• Evaluate uncertainty and business risk using Monte Carlo simulation.

• Develop optimization models using linear programming and Excel Solver.

• Integrate descriptive, predictive, and prescriptive analytics to evaluate alternatives and support evidence-based decisions.

• Communicate analytical findings and translate results into practical recommendations.



Course Outline:



PART I - BUSINESS PROBLEM & ANALYTICS FOUNDATIONS

• Introducing Business & Data Analytics

• Defining the Business Problem

• Formulating & Prioritizing Analytics Projects

• Applying Business Analytics with Excel



PART II - DESCRIPTIVE ANALYTICS

• Visualizing & Exploring Data

• Descriptive Statistical Measures

• Probability Distributions & Data Modeling

• Sampling & Estimation

• Statistical Inference



PART III - PREDICTIVE ANALYTICS

• Trendline & Regression Analysis

• Simple & Multiple Regression

• Forecasting & Time-Series Modeling



PART IV - PRESCRIPTIVE ANALYTICS & DECISION SCIENCE

• Monte Carlo Simulation & Risk Analysis

• Linear Optimization

• Excel Solver & Sensitivity Analysis



Program Format and Completion:



The program is self-paced and provides learners with up to 90 days to complete all requirements. Participants may progress at a faster pace and earn their certificate upon successful completion of the required learning activities and assessments.



IMACIA Learning - From Evidence to Action.