Data-Science-Training-Institute-Bangalore

Most of the business sectors today are coping with huge amounts of data for which they need reliable management and storage facilities. Since, the amount of data is constantly increasing the demand for Data Science experts for processing the data has grown up considerably.

If you are considering taking up Data Science training institute near me then it can help you in shaping a successful career. Today, there isn’t any business sector which is untouched by the data scientist. So, be it the eCommerce sector, IT sector or the Medical sector, each sector is embraced with qualified data scientists who help in processing huge amount of data into valuable information.

There are ample Data science training in Bangalor which claim to offer Data Science certification within few days and further make endless promises. It is always suggested to the students to only trust upon a well established institute like Trishana Technologies which believes in offering brilliance to the students.

Trishana Technologies has a strong team of professional and experienced trainers who not only focus on clearing concepts but also help them in attaining practical and real time training. The hands on training helps the students in being industry ready and help the students in understanding the roles & responsibilities of a Data Scientist.Our syllabus is prepared after examining the issues faced by the recruiters and the professionals in the data science domain. It is a wide-ranging one to cover the maximum number of concepts and methods used in data science and to prepare the students to be ready for the new and completely different methods. It is updated before the start of every batch to include the latest developments in the data science domain.Data Analytics with RINTRODUCTION

• What is R?
• Why R?
• Installing R
• R environment
• How to get help in R
• R console and Editor
• Packages in R
• CRAN
• How to check package by date
• Variables
• Data Types
• Data structure
• Factors
• Converting variable types
• Missing values

IMPORTING AND EXPORTING IN R

• Loading data from file(Text,Csv,Excel)
• Loading data from clipboard
• Connecting MySQL in R
• How to remove lines while importing
• Saving R data format
• Exporting in R(Excel,Text)

DATA CLEANING PROCESS

• Concentrating strings
• Find and replace
• How to split string
• Position based splitting
• Semi matching condition
• Condition based row/column selection
• Renaming column names
• Trim
• Data sorting
• Find and remove duplicates record
• Recoding data
• Merging data
• Data aggregation
• User defined functions
• Local and global variables
• Date and Time format in R
• Table function
LOOPS
• For
• If else
• While
• Break
• Next
• Return
VISUALIZATION IN R
• Bar, stacked bar chart
• Pie chart
• Line chart
• Scatter plot
• Histogram
• Column chart
• Doughnut chart
• Trending visualization charts in R
ADVANCED CONCEPT
• Social media analysis(Twitter) through API
• Web apps in R
STATISTICS AND MACHINE LEARNING:
• Standard deviation
• Outlier
• Linear regression
• Multiple regression
• Logistic regressions
• Chi square
• Anova
• Clustering
• Correlation
• Decision tree
• K-NN Algorithm
Data Analytics with PythonDATA ANALYSIS AND VISUALIZATION: PART 2
• Sentiment Analysis
• Word Cloud
• Text analysis
• Topic Modelling
ANALYSIS OF NETWORKS
• Introduction to Network Analysis
• Construct a simple Network
• Graph Drawing
• Network Analysis Algorithm
MACHINE LEARNING WITH PYTHON I
• Classification algorithm
• Regression
• Assignment
MACHINE LEARNING WITH PYTHON II
• K NN Algorithm
• Construct a simple Network
• Clustering
• Assignment
Data Analytics with SASGENERATING STATISTICAL REPORTS USING
• Regression proc
• Uni/Multivariate proc
• Anova proc
GENERATING GRAPHICAL REPORTS USING
• Producing Bar and Pie charts (GCHART Proc)
• Producing plots (GPLOT Proc)
• Presenting Output Report result in:
• PDF
• Text files
• Excel
• HTML Files
SAS/SQL PROGRAMMING
• Introduction and overview to SQL procedure
• Proc SQL and Data step comparisons
BASICS QUERIES
• Proc SQL syntax overview
• Specifying columns/creating new columns
• Specifying rows/subsetting on rows
• Ordering or sorting data
• Formatting output results
• Presenting detailed data
• Presenting summarized data
SUB QUERIES
• Non correlated sub queries
• Correlated sub queries
SQL JOINS (COMBINING SAS DATA SETS USING SQL JOINS)
• Introduction to SQL joins
• Types of joins with examples
• Simple to complex joins
• Choosing between data step merges and SQL joins
SET OPERATORS
• Introduction to set operations
• Except/Intersect/Union/Outer union operator
ADDITIONAL SQL PROCEDURES FEATURES
• Creating views with SQL procedure
• Dictionary tables and views
• Interfacing Proc SQL with the macro programming language
• Creating and maintaining indexes
• SQL Pass-Through facility

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