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» Advanced

  1. Introduction to Data Analytics

  2. Introduction to R Programming

  3. Data Manipulation in R

  4. Data Import Techniques in R

  5. Exploratory Data Analysis

  6. Data Visualization in R

  7. Data Mining: Clustering Techniques

  8. Data Mining: Association Rule Mining & Collaborative filtering

  9. Linear and Logistic Regression

  10. Anova and Sentiment Analysis

  11. Data Mining: Decision Trees and Random Forest

  12. Project Work

Hands on Projects

PROJECT 1
Case Study Cardio Fitness Data
PROJECT 2

Predict Wine Quality Case study using Logistic Regression in R

PROJECT 3
Data Preparation – Case study of Cardio data
PROJECT 4
Regression_Festival Rewards data using leaner Model
PROJECT 5

Bank executed a personal loan campaign using Decision Tree

PROJECT 6

Use K-Means clustering to group teen students into Engineering College Data

 PROJECT 7

PCA Practice using batting data sets

PROJECT 8

Neural Network practice

PROJECT 9

Breast Cancer Prediction – KNN Classifier & How to choose the K value

PROJECT 10

Bank Marketing Analytics – Decison Tree & Random Forest Classifier

 

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