Data Science Online Training Course Content

Data Science Online Training Course Content

Basics,
Installation
ControlFlow, Functions File handling
Data Structures Numpy, Pandas
Regular Expression
R-Studio Installation,Basics
Data Visualisation using R and Python
Introduction to Statistic Mean,Median,Mode,Variation,Std.Deviation,
Common Data Distributions,
Probability density function,
Probability mass function,
Conditional Probability, Bayes’
Theorem
Data Science Overview,Use cases
Introduction to Data Mining,
Data Acquisition,
Normalization,
Data Preprocessing or cleaning,
Outliers detection

Introduction to Recommender system
Content based recommendation engine
User based and item based collaborative filtering

Introduction to Machine Learning
Supervised vs Unsupervised Learning
K Fold Cross Validation
Dimension laity eduction(PCA,SVD)

Regression(Linear,Polynomial,Multi Variate, Multi Level)

Bayesian Methods
Naive Bayse Classifier
Measuring Entropy
DecisionTree,
Random Forest
Bais-Variance Trade-Off

Support Vector Machines
K-Nearest Neighbours

Reinforcement Learning
Hidden Markov Model

Ensemble Learning
K-MeansClustering

PySark- Spark Installation
Spark and Python Integration
RDD,DataFrames, Data Sets,
Ml-Lib

PySark- Spark Installation
Spark and Python Integration
RDD, DataFrames, Data Sets,
Ml-Lib

Regression(Linear, Polynomial,Multi Variate, Multi Level

Bayesian Methods
Naive Bayse Classifier
Measuring Entropy
DecisionTree, Random Forest
Bais-Variance Trade-Off

Neural Network and Deep Learning
Introduction,Theory TensorFlow Basics,
Installation,
Overview
TensorFlow With ContribLearn

Natural Language Processing
Introduction
NLP with R
NLP with Python

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