Predictive Analytics

This course is part of Data Analytics for Digital Transformation Specialization

Instructors: Reed H. Harder +1 more

Skills you'll gain

  •   Business Ethics
  •   Python Programming
  •   Data-Driven Decision-Making
  •   Classification And Regression Tree (CART)
  •   Digital Transformation
  •   Applied Machine Learning
  •   Artificial Neural Networks
  •   Performance Metric
  •   Cloud Computing
  •   Scikit Learn (Machine Learning Library)
  •   Data Quality
  •   Statistical Machine Learning
  •   Predictive Analytics
  •   Feature Engineering
  •   Regression Analysis
  • There are 9 modules in this course

    What you'll learn: 1. Build Predictive Models Using Python: Gain hands-on experience with Scikit-learn to develop and refine regression and classification models, applying them to real-world scenarios. 2. Diagnose and Improve Model Performance: Identify issues like overfitting and underfitting, apply cross-validation, and select optimal features to ensure robust, generalizable results. 3. Leverage Advanced Techniques: Explore neural networks, regularization, and cloud-based tools to scale and optimize predictive analytics for complex business challenges. 4. Integrate Analytics into Decision-Making: Translate data-driven insights into actionable strategies to drive innovation and efficiency in digital transformation initiatives.

    Introduction to Predictive Analytics

    Our First Model

    Adding Complexity

    Predictive Analytics in Python

    Training Advanced Models

    Putting it All Together

    Neural Networks in Python

    Practicum

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