Data Science with Python

Data science has emerged as an attractive career option for freshers as well as experienced professionals. The demand for data engineers is very high in sectors like information technology, telecom, manufacturing, finance and insurance, retail and many more.

  • Introduction of Datascience and data Analysis
  • Python Basics and statistical Package setup
  • Exploratory Data Analysis
  • Array data manipulation
  • Data Wrangling and Manipulation
  • Statistical Methods for Decision Making
  • Linear regression and regularization
  • Model selection and evaluation
  • Web scrapping, Text summarization, Lex Rank algorithm
  • Introduction of Datascience and data Analysis
  • Python Basics and statistical Package setup
  • Exploratory Data Analysis
  • Array data manipulation
  • Data Wrangling and Manipulation
  • Statistical Methods for Decision Making
  • Linear regression and regularization
  • Model selection and evaluation
  • Classification: kNN & decisiontrees
  • Intro to probability:Na├»veBayes and logisticregression
  • Time Series Analysis
  • ADF, Random walk and Auto Arima
  • AR, Lag Series, ACF, PACF
  • Web scrapping, Text summarization, Lex Rank algorithm
  • Text Mining,Text cleaning, regular expressions, Stemming, Lemmatization
  • Latent Dirichlet Allocation (LDA) Technique
  • Text classification, Document vectors, Text classification using Doc2vec
  • Word cloud, Principal Component Analysis, Bigrams & Trigram
  • capstone project
  • Introduction of Datascience and data Analysis
  • Python Basics and statistical Package setup
  • Exploratory Data Analysis
  • Array data manipulation
  • Data Wrangling and Manipulation
  • Statistical Methods for Decision Making
  • Linear regression and regularization
  • Model selection and evaluation
  • Classification: kNN & decisiontrees
  • Intro to probability:Na├»veBayes and logisticregression
  • Time Series Analysis
  • ADF, Random walk and Auto Arima
  • AR, Lag Series, ACF, PACF
  • Web scrapping, Text summarization, Lex Rank algorithm
  • Text Mining,Text cleaning, regular expressions, Stemming, Lemmatization
  • Latent Dirichlet Allocation (LDA) Technique
  • Text classification, Document vectors, Text classification using Doc2vec
  • Word cloud, Principal Component Analysis, Bigrams & Trigram
  • interactive dashboards using Tableau
  • NetworkAnalysis
  • Recommender systems
  • Relational databases,SQL
  • Big data storage and retrieval:noSQL,GraphDB
  • capstone Project

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