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Course content

About Marketing Analytics Course with Python

  • Introduction
  • Machine Learning Express Code Folder
  • Setting up the Jupyter and Code Folder
  • Overview of Machine Learning
  • Fundamentals of Supervised and Unsupervised Learning
  • Steps to Build a Model
  • Model Fit and Bias-Variance Tradeoff
  • Model Performance Metrics
  • Set up the Machine Learning Express Code and Data Folder
  • Introduction
  • Import Libraries and Data
  • Check Types of Features
  • Independent and Target Split
  • Check Percentage of Missing Values
  • Imputation of Missing Values
  • Outlier Handling
  • Encoding Categorical Features
  • Feature Scaling
  • Feature Discretization
  • Joining of Data
  • Train Test Split
  • Concept of Outlier Handling
  • Concept of Imputation of Missing Values
  • Concept of Feature Scaling
  • Introduction
  • Feature Selection for Regression Problems
  • Feature Selection for Classification Problems
  • Introduction
  • Business Problem and Data Description
  • Hierarchical Clustering - Concept
  • Hierarchical Clustering - Python  
  • K Means Clustering - Concept
  • K Means Clustering
  • Introduction
  • Business Problem and Data Description
  • PCA
  • Introduction
  • Business Problem 1 and Data Description
  • Simple Linear Regression  
  • Business Problem 2 and Data Description
  • Multiple Linear Regression - Concept
  • Multiple Linear Regression  
  • Decision Tree Regression - Concept
  • Decision Tree Regression  
  • Random Forest Regression - Concept
  • Random Forest Regression  
  • Gradient Boosting Regression - Concept
  • Gradient Boosting Regression 
  • Introduction
  • Business Problem and Data Description
  • Logistic Regression - Concept
  • Decision Tree Classification - Concept
  • Random Forest Classification - Concept
  • Gradient Boosting Classification - Concept
  • Stacking Classifier - Concept
  • KNN Classifier - Concept
  • Naive Bayes Classifier - Concept
  • SVM Classification - Concept
  • Introduction
  • Hyper Parameter Tuning with Grid Search - Concept
  • Grid Search - Python Implementation with SVM
  • Introduction
  • What is Marketing Analytics
  • The 4 P's of Marketing
  • Customer Lifecycle
  • Data Sources and Use Cases for Marketing Analytics
  • Customer Segmentation
  • Marketing Analytics Strategy from Machine Learning
  • Marketing Analytics Use Cases for Retail Domain
  • Why Should You Learn Marketing Analytics Course with Python Training?

    The annual salary of an Marketing Analytics Course with Python is $125k.

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    What you will get at Zeblearnindia Learning?

    Zeblearnindia Learning is a premier institute offering training in SAP Online Courses, Web Designing, Data Science, Full-Stack Development, Salesforce, Workday, Machine Learning, Software Testing, and Video Editing. With the option to choose between online and offline (classroom) learning, our well-structured courses cater to students, working professionals, business owners, and entrepreneurs. Here’s what you can expect at Zeblearnindia Learning:

    •   Expert-Led Training
    •   Globally Recognized Certifications
    •   100% Job Placement Support
    •   Hands-On Learning
    •   Flexible Learning Options
    •   Affordable Course Fees
    •   Career Growth Opportunities
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    () 60 Minutes WEBINAR with CERTIFICATE

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    We are proud to offer our Marketing Analytics Course with Python services across numerous states nationwide.

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