Data Science Courses in Bangalore

About the Course

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 Bangalore then we 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 Bangalore 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.

We have branches in Marathahalli and Kalyan Nagar in Bangalore.Contact us our data science training in Marathahalli, or data science training in Kalyan Nagar according to your preferences

Data science Courses in Bangalore

Key Features

Live Demo

Hands on Practicals/Project
Hands on

One year
Course Validity

100% Placement Assistance
Placement Assistance

Individual attention

24 X 7 Expert Support
24 X 7
Expert Support

Training from Industrial Experts
Training from
Industrial Experts

Certification for Course
for Course


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 Science with Python

1) Introductory Sessions of python

  • • History of Python
  • • Introduction about Python
  • • Starting with Python
  • • Execute python script

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 manipulation

  • 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


  • 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 Python

Data 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 SAS

Generating 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

SAS Macro Language

  • Introduction to macro facility
  • Generate SAS code using macros
  • Macro compilation
  • Creating macro variables
  • Scope or macro variables
  • Global/Local Macro variables
  • User defined /Automatic Macro variables
  • Macro variables references
  • Combing macro variables references with text
  • Macro functions
  • Quoting (Masking)
  • Creating macro variables in Data step (Call SYMPUT Routine)
  • Obtaining variable value during macro execution (SYMGET function)
  • Creating macro variables during PROC SQL execution (INTO Clause)
  • Creating a delimited list of values
  • Macro parameters
  • Strong Macro using Autocall Features
  • Permanently storing and using stored compiled macro program
  • SAS Macro debugging options to track problems

Basics Statistics

  • Standard deviation
  • Correlation Coefficients
  • Outliers
  • Linear regressions
  • Clustering
  • Chi Square

Career opportunities in Data Analytics with SAS

  • SAS Analyst
  • Business Analyst
  • Analyst – Data Management
  • Data Analyst
  • SAS programmer
  • Staff Accountant

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    Data Science Courses in Bangalore - Upcoming Batches

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    Data Science Certification

    About more than 1000 top companies has recognized Trishana Technologies certifications globally.
    Download the certificate once you,

    • Complete our Data Science courses in Bangalore
    • After successfully Completing the Realtime Industry projects
    • Successful completion of given assignments
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