Mastering in Data Science


The following technical blogs are coming to be covered in Data Science, Machine Learning & Analysis , visualization track. Be an enterprise Data Scientist by following the Data Scientist fast track modules: STAY TUNED!!

A lap around MACHINE LEARNING
Supervised and unsupervised learning
Kernel based methods
Text mining techniques
Performance evaluation

Exploring CATEGORICAL DATA ANALYSIS
Types of categorical data
Generalized linear models
Contingency tables
Simple and multinomial logistic regression models

Evaluation of STOCHASTIC PROCESSES AND SIMULATION
Random Variables and Distributions
Monte Carlo Simulation
Discrete Event Simulation
Variance Reduction Techniques

Data OPTIMIZATION Techniques
Linear Programming
Integer Programming
Multi-criteria Optimization
Goal Programming
AHP (Analytic Hierarchy Process)
Data Envelopment Analysis (DEA)

ECONOMETRIC METHODS in Data Science
Time Series Analysis
GARCH Models
Fixed Effects Estimation
Random Effects Estimation

STATISTICS for DATA SCIENCE
Probability Theory
Statistical Inference
Sampling Theory
Hypothesis Testing
Regression Analysis

Real World Case Studies in Data Science

  • Social Media Mining with R & Microsoft PowerBI
  • Experimentation interactive R based visuals with Shiny apps
  • What’s next with Julia
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About Anindita
Anindita Basak is working as Big Data Cloud Consultant in Microsoft. Worked in multiple MNCs as Developer & Senior Developer on Microsoft Azure, Data Platform, IoT & BI , Data Visualization, Data warehousing & ETL & of course in Hadoop platform.She played both as FTE & v- employee in Azure platform teams of Microsoft.Passionate about .NET , Java, Python & Data Science. She is also an active Big Data & Cloud Trainer & would love share her experience in IT Training Industry. She is an author, forum contributor, blogger & technical reviewer of various books on Big Data Hadoop, HDInsight, IoT & Data Science, SQL Server PDW & PowerBI.

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