Certification Course in Data Science from Bangalore

Data is everywhere—from e-commerce sales, app downloads to a smartphone, to supply chain management or bioinformatics or connected devices. And that massive increase in the amount and variety of data being collected is translating to an exponential growth in the computer power needed to process that data.

PrwaTech’s data-science courses teach you the most powerful tools and techniques.

If you’re interested in developing competitive data science skills to solve complex challenges in business or elsewhere, you might be considering a master’s in data science. It’s important to consider learning in a region — like Bangalore — that boasts innovation, where you will have access to people and places that are involved in the field of data science. Bangalore offers a wide range of quality programs that are conveniently located and can help you develop the skills you need to pursue your career goals.

Learn more on how to earn your online and classroom training in data science, Bangalore from Prwatech.


Why Data Science certification courses in Bangalore are worth taking

In the sphere of technology-related training, Data Science is one of the biggest and most popular aspects. Owing to this, many Data Science certification courses in Bangalore are available for aspiring developers. There are, of course, many reasons why getting this certification would further improve your career graph. They are as follows.

  1. Higher demand for professionals

To be specific, many organizations require the help of experienced and certified data analysts. This is due to the fact that Big Data is a powerhouse programming framework that implements analytics for technological advancement. Because so many companies prefer this technique currently, the demand for these professionals is more. If you get the Data Science certification Bangalore, you can join this list.

  1. Salary

Given the high-intensity programming process and higher profitable returns, skill and expertise are a priority in a data analyst. Companies who need their services know their importance and they pay more for that. Therefore, the salary you would get at the end of each month would show a big number too. The average pay for a Data Science professional is more compared to most other developers.

  1. Job opportunities

Where there is demand, there is profit. This is the case here too, as the need for Data analysts is high in many industries globally. Hence, if you get a data science certification in Bangalore, you would get more job opportunities in the future.

  1. Practical knowledge

When you are learning about data processing and analytics in these courses, you would train under industry professionals. What they teach you is what they exercise every day in real projects. Thus, you would get to work with verified and experienced analysts and gain knowledge in real-life, not just the classroom.

  1. Work in different sectors

To put it simply, in the technological field, most of the developers are stuck in one particular industry. Thus, they cannot look for jobs in other professional fields later and utilize their skills there. If you want to work as a programmer but not stay limited, opt for the Data Science certification course in Bangalore.

There is a need for such experts in a variety of different fields, like logistics, healthcare, finance, retail, etc. Thus, you can apply to any of these industries as a data analyst and they would accept. Data analysts do not have a lack of options in this regard, and you would enjoy this situation.

  1. No prerequisite certification necessary

If you have no knowledge or training in programming but want to work as a programmer, data analytics is fine. You do not need to have a lot of beforehand training or certifications. Simply join the Best Data Science Certification Course in Bangalore, and you can learn about data processing directly.

Yet, you must put in the effort and time during the training process itself to better understand it. There is a level of complexity to it, and when you improve your skills, you can perform well.

  1. Structured learning

One of the best parts of a data science course is the way that the learning approach is structured. The material and training points are organized and presented in a logical and systematic manner. Since there is essentially a lot to learn, having a deeply detailed learning experience is important.

So, these course structures are more complex but explanatory and give you more specified knowledge. When you start working in a company in the future as a data analyst, you can tackle any issue easily.

Not only does learning about Data Science gives you more paths in career, but also a better skillset. Therefore, if you take this certification course, you would enjoy a lot of perks in your professional life.


Who should do Data Science certification?

This Certification is

  • For Managers
  • For Java developers
  • For Testers
  • For Business analyst
  • For Project managers
  • For Beginners

Contact Us +91 8147111254


Rs. 16000/-Enroll Now



Rs. 16000/-Enroll Now


Rs. 16000/-Enroll Now


Rs. 16000/-Enroll Now

Why Data Science Course?


Data Scientist is a person who Usually analyses entire accumulated data from various sources, across various machines concerned with the subject or a product in order to provide suitable insights to his company. The growth of the company depends upon the strategically plans drawn Particularly by forecasting marketing changes depending upon the insights provided by their data science.

To summarize Dial Now 8147111254 for any queries regarding data science course fee & Job Assistance

Who can take Data Science Certification Course in Bangalore?

  • IT professionals
  • Business Analysts
  • Data Analysts
  • Warehouse managers
  • Application Developers
  • Job seekers in the IT industry
  • Business operators


Data Science Training Modules

Module 1: Python Essentials

Learning Objective: To understand why Python is a useful scripting language for developers. To learn how to design and program Python applications.


  • What is Python..?
  • A Brief history of Python
  • Why Should I learn Python..?
  • Installing Python
  • How to execute Python program
  • Write your first program

Variables & Data Types

  • Variables
  • Numbers
  • String
  • Lists, Tuples & Dictionary

Conditional Statements & Loops

  • If…statement
  • If…else statement
  • elif…statement
  • The while…Loop
  • The for….Loop

Control Statements

  • Continue statement
  • Break statement
  • Pass statement


  • Define function
  • Calling a function
  • Function arguments
  • Built-in functions

Modules & Packages

  • Modules
  • How to import a module…?
  • Packages
  • How to create packages
  • Classes & Objects

Introduction about classes & objects

  • Creating a class & object
  • Inheritance
  • Methods Overriding
  • Data hiding

Files & Exception Handling

  • Writing data to a file
  • Reading data from a file
  • Read and Write data from CSV file
  • Try…except
  • Try…except…else
  • Finally
  • OS module

Module 2: Statistics

Learning Objective: Demonstrate knowledge of statistical data analysis techniques utilized in decision making. Apply principles of Data Science to the analysis of problems. Be able to restate an investigative question in terms of a statistical model or algorithm.

Inferential statistics

  • Standard error
  • Confidence interval
  • Hypothesis testing
  • p-value

Sample vs. population mean

  • Variance of population

Probability and statistics

  • Probability density functions
  • Poisson Process
  • Law of large numbers
  • Normal distribution
  • Sampling distribution
  • Mean
  • Variance of Bernoulli
  • Regression

Module 3: Introduction to Machine Learning (ML)

Learning Objective: The purpose of machine learning is to discover patterns in your data and then make predictions based on those often, complex patterns to answer business questions, and help solve problems. Machine learning helps analyze your data and identify trends.


  • What is Machine learning?
  • Overview about sci-kit learn and tensorflow
  • Types of ML
  • Some complementing fields of ML
  • ML algorithms
  • Machine learning examples

NumPy Arrays

  • Creating multidimensional array
  • NumPy-Data types
  • Array attributes
  • Indexing and Slicing
  • Creating array views and copies
  • Manipulating array shapes
  • I/O with NumPy

Working with Pandas

  • Installing pandas
  • Pandas data frames
  • Pandas Series
  • Data aggregation with Pandas Data Frames
  • Concatenating and appending Data Frames
  • Joining Data Frames
  • Handling missing data

Python Regular Expressions

  • What are regular expressions?
  • The match Function
  • The search Function
  • Matching vs searching
  • Search and Replace
  • Extended Regular Expressions
  • Wildcard

Python Oracle Database Access

  • Install the cx_Oracle and other Packages
  • Create Database Connection
  • DML and DDL Operation with Databases
  • Performing Transactions
  • Handling Database Errors
  • Disconnecting Database

Regression based learning

  • Simple regression
  • Multiple regression
  • Logistic regression
  • Predicting house prices with regression

Clustering based learning

  • Definition
  • Types of clustering
  • The k-means clustering algorithm

Data mining

  • Introducing data mining
  • Decision Tree
  • Affiity Analysis
  • Clustering

Introducing matplotlib

  • Bar Charts
  • Line Charts
  • Scatter plots
  • Bubble charts

Working with openCV

  • Setting up opencv
  • Loading and displaying images
  • Applying image filters
  • Tracking faces
  • Face recognition

Module 4: Performing predictions with Linear Regression

Learning Objective: The basic objective of this course is to learn How to calculate a simple linear regression step-by-step, How to perform all of the calculations using a spreadsheet, How to make predictions on new data using your model, A shortcut that greatly simplifies the calculation.

Simple linear regression

  • Multiple regression
  • Training and testing model

Introduction to Python

  • Installation of Python framework and packages: Anaconda & pip Writing/
  • Running python programs using Spyder Command Prompt Working with Jupyter
  • Creating Python variables
  • Numeric, string and logical operations
  • Data containers: Lists, Dictionaries, Tuples & sets Practice assignment

Iterative Operations & Functions in Python

  • Writing for loops in Python
  • While loops and conditional blocks List/Dictionary comprehensions with loops
  • Writing your own functions in Python Writing your own classes and functions

Data Handling in Python using NumPy & Pandas

  • Introduction to NumPy arrays, functions & properties Introduction to Pandas &
    Data frames
  • Importing and exporting external data in Python Feature engineering using

Data Science & Machine Learning in Python

  • Converting business problems to data problems
  • Understanding supervised and unsupervised learning with examples
  • Understanding biases associated with any machine learning algorithm Ways of
  • Reducing bias and increasing generalization capabilities Drivers of machine
  • Learning algorithms
  • Cost functions
  • Brief introduction to gradient descent
  • Importance of model validation
  • Methods of model validation
  • Cross validation & average error

Generalized Linear Models in Python

  • Linear Regression
  • Regularization of Generalized Linear Models
  • Ridge and Lasso Regression
  • Logistic Regression
  • Methods of threshold determination and performance measures for Classification score models

Tree Models using Python

  • Introduction to decision trees
  • Tuning tree size with cross validation Introduction to bagging algorithm Random
  • Grid search and randomized grid search ExtraTrees (Extremely Randomised
    Trees) Partial dependence plots
  • Support Vector Machines (SVM) & kNN in Python
  • Introduction to idea of observation based learning Distances and similarities
    k Nearest Neighbors (kNN) for classification Brief mathematical background on
    SVM Regression with kNN & SVM

Unsupervised learning in Python

  • Need for dimensionality reduction
  • Principal Component Analysis (PCA) Difference between PCAs and Latent
  • Factors Factor Analysis
  • Hierarchical, K-means & DBSCAN Clustering

Text Mining in Python

  • Gathering text data using web scraping with urllib
  • Processing raw web data with BeautifulSoup
  • Interacting with Google search using urllib with custom user agent collecting twitter data with
  • Twitter API
  • Naive Bayes Algorithm
  • Feature Engineering with text data
  • Sentiment analysis

Frequently Asked Questions

  • What are the types of training available?
    Answer: Prwatech Offering 2 Types of training modes to the candidates, one can choose Wither classroom training or online classes depends on candidate flexibility.


  • Does watch offer placement assistance after the course completion?
    Answer: Yes! We do provide the 100% Placement assistance as a part of our advanced Data Science Certification  program once the candidate has done the course with us.


  • What is the companies’ watch tie-up with?
    Answer: we tie-up with Flipkart, Capgemini, Syntel, Synchron, SunGard, HCl & Other Top MNC companies.


  • What are the payment options?
    Answer: We accept Payments from Cash, Card, GooglePay, UPI, and PayPal.


  • Who can take Data Scientist Certification course
    Answer: Working Professionals, Job Hunters, IT professionals Fresher’s, Students & Students who are about to complete the degree.


Best Data Science Certification Course in Bangalore Reviews


  • Ravi: Prwatech training institute was very much helpful to clear the interview with their advanced Data Scientist Courses Programs; I got proper Hands-on Practice exposure during Certification.


  • Praveen: Trainers of Prwatech are very experienced, as well as their teaching as well, It is so good that we need not revise again and again. The best thing is that the teaching methodology they’re using is fantastic which helps to understand the technology easier.


  • Sumedha Nigudkar: I am very happy with the data scientist training and placement Program from Prwatech offering to the candidates which will definitely an ideal option to any kind of candidates who are willing to join the training institite.


  • Gaurav: Prwatech has well-equipped world-class training facilities which make feel learning the technology from world-class trainers. i can say this is one of the best training institute for data science in Bangalore


Learning Objectives – Data scientist certification course  module one starts with the basics of Business Analytics, R basic, R programming, R’s role in solving analytical problems, R’s popularity in tech giants like- Facebook, Google, Finance, etc.

Topics: Business Analytics, R, R language and programming, Ecosystem, Uses of R, Data types in R, subsetting methods, R comparison with other software’s, R installation, operations in R, useful packages, IDER, GUI, using functions like- length(), str(), ncol() etc, summarize data.

Learning Objectives – In this module, we will discuss dirty data set, data cleaning, which results in data set, and ready for analysis, exploring functions, the versatility of R, the robustness of R. This module helps you to understand various importing techniques in R

Topics: Data Cleaning, Data Inspection, Troubleshooting the problems, Function uses, grepl(), sub(), grep(), Data coerce, apply() functions use, Import data from spreadsheets into R, Importing text files into R, import data, installation of packages. RDBMS from R, using ODBC, SQL queries, Web Scraping

Learning Objectives – Data scientist certification module 3 includes information about exploratory data analysis, EDA- for observing what data tell us beyond the formal hypothesis. Typical EDA process.

Topics: Exploratory Data Analysis, Implementing EDA on datasets, Box plots, cor() in R, EDA functions, list(), summarize(), Multiple packages in R, various plots, Segment plot, HC plot in R.

Learning Objectives – In this module, you will learn about- visualization in USP of R, creating simple visualization in R, complex visualization in R.

Topics: Data Visualization, Graphical representations, Functions in R, Plotting graphs like box plot, table plot and histogram, Improvising plots, GUIs, Deducer, R Commander and Spatial Analysis.

Learning Objectives – In this module, we will discuss various Machine Learning algorithms, Machine Learning types- Unsupervised Learning and Supervised Learning, Difference between Unsupervised Learning and Supervised Learning. We will also learn about K-means Clustering and implementing them, Concepts of Decision trees and Random forest, Algorithm creation of forests and trees, LMS.

Topics: Data Mining, Machine Learning algorithms, Unsupervised and Supervised Machine, K-means clustering, Decision Trees, Random forest Algorithm creation, Entropy, features, and working of Random forest.

HQL and Hive with Analytics

Learning Objectives – Data science training in Bangalore, module 6, we will introduce- Regression Techniques, Linear and logistic regression basics, implementation in R.

Topics: Simple and Multiple Linear Regressions, Simple and Multiple Logistic Regression, Log-Linear Model.

Learning Objectives – In this module, we will discuss the Analysis of Variance, ANOVA Technique, Predictive Analysis.

Topics: Anova Technique, Sample testing, One and Two-way ANOVA, Predictive Analysis.

You will be given a problem statement and in this module, our qualified professionals will help you with that statement.

Perform Exploratory Data Analysis


Establish a hypothesis of data
Handle outliers
Troubleshooting missing data.
Validation datasets.
Logistic Regression
Confusion Matrix
Final model

In this world where data is becoming the base of every decision, Data Science is becoming the need of the hour. Prwatech has always been known for understanding the market gap and come up with courses that are in alignment with the industry need. Data Scientist course at Prwatech is a 40-hour practical based along with with 35-course classes program. After completion of which you will be able to understand business intelligence and business analytics with the power of analyzing large data junks. Along with that, you will be able to debug and understand all aspects of Big Data Technology. Some key topics that you would be covering with Prwatech are Business Analytics, R, R language and programming, Ecosystem, Uses of R, Data types in R, subsetting methods, R comparison with other software’s, and many more

Prwatech offers various modes of training, from classroom to online (self-learning and instructor-led). We understand that each student is different so does his needs. Therefore, we believe in teaching with different modes so that each student can start his learning journey on his own. With the various modes of study, a student can select which fits best to him. In case of query, our team of experts is always available for help.

At Prwatech we take each student very seriously and believe in providing 100% support throughout their learning journey. We have 24/7 contact support. Where in a student can raise in their query and within no time email support will be provided. A student can avail this support even after the completion of the course.

The only pre-requisite for this course is to have an aptitude for analytical thinking. You need not be a programmer, never the less if you have programming skills that would be an added benefit.

Our Data Science course has a nice blend of real-life cases as a part of the training curriculum. We believe in preparing students for industry. These cases will help you to test your skills at all levels. As these are a real-life problem they will help you to build a greater understanding of the problems that you might face at work.

It does not matter which mode of education you chose to take with Prwatech. We offer placements for all the modes of the course. Prwatech has tie-ups with more than 80+ organization within various industries.

Spark Course Bangalore

Rs. 14,000 + Tax

per 2 weeks

35 Hours
Practical 40 Hours
15 Seats
Course Badge
Course Certificate

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