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Predictive, Prescriptive Analytics for Business Decision Making

LEARN HOW TO BUILD PREDICTIVE AND PRESCRIPTIVE MODELS USING NUMERICAL DATA

Foster and hone financial expertise to manage strategic business units

Key Highlights

Course Length

5 weeks

100% Online

With Continuous Learning Community support + Monthly Live Webinars

Effort

6 Hours/Week

Learning Access

Resource Toolkit & Templates + Unlimited Networking Events

Amazing course for even beginners in the field of Predictive analytics. Highly recommend to do this course for enhancing the analytical skills. Examples and case studies explain the concepts very well.
Suresh M
Informatica
I have learned a lot from the course. Many interesting topics that help me to understand this field of Analytics. This course has generated more interest for me to continue learning more in this specialization
Rahul A
Mindworks

What will you Learn?

Top skills you will learn

Course Curriculum

   Regression Fundamentals
   The linear regression equation
   Linear Regression explained
   Linear Regression with independent variable
   Interpreting R -Squared
   Evaluating Model Performance
   Key assumptions of Linear Regression
   Residual Analysis
   Statistical tests to validate assumptions
   Correlation and Casuation
   Heat map and Scatter plots
   Multiple Linear Regression use case
   Interpreting regression outputs
   Regression use cases
    Chapter Quiz
   Time Series Fundamentals
   Visualizing time series data using plots
   Components of Time series
   Stationary time series
   Forecasting fundamentals
   Forecasting techniques
   Forecasting techniques : Exponential Smoothing
   Forecasting techniques : Holt’s method
   Forecasting techniques : Holt’s Winter method
   Forecasting techniques : ACF & PACF
   Forecasting techniques : ARIMA
   Forecasting techniques : ARIMA models in Python
   Applications of Time Series
    Chapter Quiz
   Introduction to Prescriptive Analytics
   Gradient Descent (& code)
   Gradient descent fundamentals
   Stochastic Gradient descent regression
    Chapter Quiz
   Linear Programming fundamentals
   Components of LPP
   Formulating the LPP model
   Solving linear models-Graphical method
   Solving linear models -Simplex method
   Assumptions of LPP
   Business applications of LPP
    Chapter Quiz
   Parametric & Non Parametric Methods – Model building
   Tradeoffs -Accuracy vs Explainability
    Chapter Quiz
   Framework to choose the right model to address business problems
    Chapter Quiz

Ideal For

1 – 8 yrs work experience.- Engineering, Math/Statistics/Programming background preferred
Typical roles: Domain experts, Engineers, Software and IT Professionals, Project
Managers, Business Analysts, Consultants, Entrepreneurs.

Engineers with over 5 years of experience

Common Scenarios to Enroll

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34% of the firms that were top in class in using analytics got about 6% more profitability and were about 5% more productive

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