Data Science & Data Analytics

by Big Learn Claim Listing

Data Science is about utilizing different branches to come up with an effective way to develop creative ideas that help in building business and daily useable product values by utilizing the data.

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img Duration

3/6/12 Months

Course Details

Data Science is about utilizing different branches to come up with an effective way to develop creative ideas that help in building business and daily useable product values by utilizing the data.

Python is the market’s most popular language nowadays and it works maturely with Data Science to achieve the goal of Data Scientist, who is responsible for processing raw information to extract insights and understand the advanced capabilities we can build.

Data analytics is a systematic process of transforming an organization’s data into statistical form and these data are analyzed with analytic tools to extract some information.

Understanding the implementation of Data Analytics in E-government, Banking sectors, Healthcare R&D, Financial sectors, Retail sectors, Supply chain, etc.

To introduce the proficiency to understand the implementation of Data analytics in different divisions to solve numerous complex problems related to the data. Get trained to be a skilled analyst from BIGLEARN.

 

Key Topics Covered:

  • Data Science
  • Using Python
  • Introduction to Data Science
  • Overview of Python Programming
  • Exploratory Data Analysis(EDA)
  • Data Visualization
  • Data Distribution & Correlation
  • Regression Analysis
  • Clustering – Hierarchical &K- means
  • Classification – KNN, Naive Bayes
  • Decision Tree, Random Forest
  • Text Mining, Word Cloud
  • Dimension Reduction, Association
  • Rule mining
  • Forecasting/ Time Series
  • Using R
  • Introduction to Data Science
  • Basics of R programming
  • Interpret Dataset with packages
  • Fundamentals of statistics and probability
  • Data Visualization
  • Data Distribution & Correlation
  • Regression Analysis
  • Clustering – Hierarchical & K-means
  • Classification – KNN, Naïve Bayes
  • Decision Tree, Random Forest
  • Text Mining, WordCloud
  • Forecasting/ Time Series
  • API & Libraries
  • Scikit-learn, Numpy, Pandas, Matplotlib,
  • XIrd, Random, Time, StatsModel, APYORI
  • Data Analytics
  • Basic Details
  • Introduction to Tableau
  • Installing desktop Tableau
  • Tableau help and online resources
  • Tableau user interface
  • Features
  • File types and data types in Tableau
  • Green pills and Blue pills in Tableau
  • Import/Export files in Tableau
  • Live and Extracts Connections in Tableau
  • Working with Excel interpreter
  • Pills Conversion
  • Processing Data
  • Converting data into ideal format
  • Mapping Data
  • Data Filtration and sorting
  • Excluding data
  • Splitting data fields
  • Understanding metadata
  • Dealing with missing values
  • Visualization
  • Scatter plot
  • Bar plot
  • Pie Charts
  • Line and Area charts
  • Heap Maps
  • Crosstabs
  • Maps
  • Treemaps
  • Packed bubble
  • Polygon Maps
     
  • Data Analytics
  • Calculations
  • Table calculations
  • String and Number
  • Date and time
  • Spatial
  • Logical
  • Aggregate
  • R expression
  • Type
  • Visualization
  • Scatter plot
  • Bar plot
  • Pie Charts
  • Line and Area charts
  • Advance Features
  • Aggregate and Disaggregate
  • Combining multiple data sources
  • using join, blend, union
  • Creating Sets
  • Formatting pane
  • Tooltips
  • For example mapping of data in
  • tableau
  • Making Map view and error sorting
  • Customizing maps, use of filters
  • in maps
  • Trichy Branch

    No:122/5, Second Floor, Premier Plaza, Bharathiar Salai, opp. to RC School, Trichy

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