Data Science with Machine & Deep Learning using Python - Traning and Placement 

Data Science with Machine & Deep Learning using Python - Traning and Placement 

Introduction to Analytics

Introduction to NumPy, Pandas, Matplotlib 

Data Exploration and Preparation 

Introduction to Statistics in Python 

Central limit theorem and confidence interval

Hypothesis Testing

Regression 1

Regression 2

Regression 3

Logistic Regression

Introduction to machine learning KNN algorithm Naive Bayes algorithm Ensemble and Random Forest ANN  SVM XgBoost Data Mining- Cluster Analysis Data Mining - Factor Analysis and PCA Additional Topics Forecasting and technique Natural Language Processing (NLP) Convolution Neural Network (CNN) Python  IDE  

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