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
