Data Science

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Digital Marketing
1 hour 27 min
01 August 2020
197 MB
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Debasis Chatterjee

I currently have 70 Courses with 20,280+ Minutes of Content (338 hours in total) with 100,000+ Satisfied Students enrolled. That’s 14+ days of learning material!


Data Science Course Coverage

Duration – 120 Hours

BIG DATA ANALYTICS AND THE DATA SCIENTIST ROLE

  • The characteristics of Big Data
  • The practice of analytics
  • The role and required skills of a Data Scientist

DATA ANALYTICS LIFECYCLE

  • Discovery
  • Data preparation
  • Model planning and building
  • Communicating results
  • Operationalizing a data analytics project

INITIAL ANALYSIS OF THE DATA

  • Using basic R commands to analyze data
  • Using statistical measures and visualization (Box, Scatter, Histogram, Bubble Charts) to understand data
  • The theory, process, and analysis of results to evaluate a model

ADVANCED ANALYTICS – THEORY AND METHODS

  • Hypothesis Tests (ANOVA, T Test, HoV, Chi-Sq, Logistic, Median tests)
  • Linear regression
  • Machine Learning
  • Classification using Nearest Neighbours
  • K-means clustering
  • Market Basket Analysis using Association rules
  • Naïve Bayesian classifiers
  • Decision trees
  • Random Forest
  • Neural Networks and Support Vector Machines
  • Time Series Analysis
  • Re-sampling Method
  • Discriminant Analysis
  • Text Analytics
  • Vector Space model
  • Term-Document Matrix
  • Word Cloud
  • Stop Word Removal
  • Latent Semantic Indexing
  • Hierarchical Agglomerative Clustering
  • Sentiment Analysis

ADVANCED ANALYTICS FOR BIG DATA – TECHNOLOGY AND TOOLS

  • Hadoop Ecosystems, HDFS
  • MapReduce, PIG, HIVE
  • RHadoop for Advanced Analytics

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