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Course Curriculum

Agenda Introduction Details 00:00:00
Introduction to Data Science Details 00:00:00
Installation of R & R Studio Details 00:00:00
Basics of R Studio Details 00:00:00
Data Visualization with R Studio Details 00:00:00
Data Modelling with R Studio Details 00:00:00
Data Joining With R Studio Details 00:00:00
Data Visualization With Ggplot2 Details 00:00:00
Data Preparation With RStudio Details 00:00:00
Data Cleaning With RegExp Details 00:00:00
Data Cleaning Using Unstructured Data Details 00:00:00
Company Casestudy Data Visualization Details 00:00:00
Data Visualization With Plotly Details 00:00:00
R-Assessment 00:15:00
Advanced Data Preparation Projects Details 00:00:00
Advanced Data Preparation Script Files Details 00:00:00
1.2 MySQL
Introduction to MySQL Details 00:00:00
Creating DataBases in MySQL Details 00:00:00
Deep Dive into MySQL Interface Details 00:00:00
Queries in MySQL Details 00:00:00
Clauses in MYSQL Details 00:00:00
Clauses in MySQL-2. Details 00:00:00
MY SQL Data Handling. Details 00:00:00
Data Handling Part -1 Details 00:00:00
MYSQL Clauses-2 Details 00:00:00
MYSQL Aggregate Functions Details 00:00:00
MYSQL Assessment Details 00:00:00
MySQL Script Files Details 00:00:00
1.3 Linear Regression
Linear Regression Overview Details 00:00:00
Supervised & Unsupervised Learning Details 00:00:00
Linear Regression Deep Dive Details 00:00:00
Linear Regression Evalution Metrics Details 00:00:00
Hypothesis Testing Details 00:00:00
Project on Linear Regression Details 00:00:00
How to Improve Model Accuracy Details 00:00:00
Airlines Casestudy Details 00:00:00
Sales Prediction Case Study Details 00:00:00
Lasso & Ridge Regression Details 00:00:00
POC on OLX Details 00:00:00
Linear regression Assessment Details 00:00:00
Linear Regression Projects Details 00:00:00
Linear Regression Script Files Details 00:00:00
1.4 Logistic Regression
Introduction to Logistic Regression Details 00:00:00
Logistic Regression Maths Details 00:00:00
Logistic Regression_Evaluation Metrics. Details 00:00:00
ROC _ AUC Curve Details 00:00:00
Diabetes Case Study on Logistic Regression Details 00:00:00
Cancer Prediction Logistic Regression Details 00:00:00
Different Families in Logistic Model Details 00:00:00
Logistic Regression Assessment Details 00:00:00
1.5 Fundamentals of Machine Learning
Fundamentals of Machine Learning Part-2 Details 00:00:00
Fundamentals of ML Part-1 Details 00:00:00
Insights from Train Test Accuracy Details 00:00:00
Introduction to KNN Details 00:00:00
KNN Math Details 00:00:00
KNN Algorithm CaseStudy Details 00:00:00
KNN Case Study with Normalization Details 00:00:00
1.6 Machine Learning & Advanced Machine Learning
Decision Tree Maths Deep Dive Details 00:00:00
Decision Tree Coding on RStudio Details 00:00:00
Airlines Case study Explanation Details 00:00:00
Airlines Case Study Coding Details 00:00:00
Predicting Cricket Performance Details 00:00:00
Introduction to Gradient Boosting Details 00:00:00
Introduction to Neural Networks Details 00:00:00
Neural Network Architecture Details 00:00:00
Random Forest Maths Details 00:00:00
Random Forest Coding Deep Dive Details 00:00:00
Machine Learning & Advanced Machine Learning Script Files Details 00:00:00
SVM Deep Dive Details 00:00:00
SVM Script using R Details 00:00:00
Discussion Based SVM R coding Details 00:00:00
1.7 Time Series
Introduction to Time Series Modelling Details 00:00:00
Time Series Modelling-2 Details 00:00:00
Characteristics of Time Series Modelling Details 00:00:00
Time Series Modelling Techniques Details 00:00:00
Coding Time Series Modelling using R Details 00:00:00
Time Series Modelling using RNN Details 00:00:00
Time Series Script Files Details 00:00:00
1.8 Deep Learning
Introduction to Neural Networks Details 00:00:00
Neural Network Architecture Details 00:00:00
Different Optimizers Details 00:00:00
Different Activation Functions Details 00:00:00
Different Loss Functions Details 00:00:00
Coding Feed Forward NN in R Details 00:00:00
Deep Learning Script Files Details 00:00:00
1.9 Text Mining
Introduction to Text Mining Details 00:00:00
NLP Processing Deep Dive Details 00:00:00
NLP Classification Coding Details 00:00:00
Language Identification using R Details 00:00:00
Phrase Extraction Details 00:00:00
Text Mining Script Files Details 00:00:00

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