Data Science Training Institute in Bangalore

 

Data Science Training institute in Bangalore, We’re India’s Leading E-Learning Platform for data science offering advanced Data science course to all the Data Science Enthusiasts who are hunger to explore the technology under Certified Industry Experts. Thus we help Enthusiasts to Learn Advanced Concepts in Tableau, R-Programming, Python, SAS With our Industry certified professionals as a part of our Data Science Training institute in Bangalore. As a result we understand the Gap between IT Industry and student skill, so we tailored Our Data science Training on the basis of the current trend which is helping data scientist enthusiasts to crack any kind of challenges in an easier manner.

 

Best Data Science training in Bangalore

 

As a result our Data Science Training Institute in Bangalore offering Flexible Training facilities to all of our students and technology enthusiasts, so one can take the Data Science training without worrying about the Timings. Therefore we designed our Data Science Training Institute in Bangalore Course Structure based on the current IT Industry standards & trends which are gaining huge demand. In short Are you the one who is hunting for the for Best data science training institutes? Or the one who is locally searching for training institute? Don’t just hunt for the best training place hunt for the Data Science training institute in Bangalore who can share advanced concepts of Data Science , Certification , skills, Online Training & 100% placement assistance.

 

Then what are you waiting for Enroll now for our Data science Training Institute in Bangalore and get the training under 20+ Years experienced Certified Professionals? So you can Access our data science training institute easily to the Prwatech Nearest Hub.

 

Best Data Science Training Institute in Bangalore

 

Best Data scientist Certification Course, Anyone can easily dream to become the certified pro data scientist but only desired & Passionate candidates can achieve the dreams. Are you also dreaming to become a certified Professional? Then Step into Our certification Course, We make your dreams come true with our Advanced Data scientist certification Programs.

 

Therefore this technology is said to be one of the trending technology in the Current IT market which is Creating Huge Buzz and Massive Job opportunities. To begin with we understand the Industry requirements of the Data Science Training in Bangalore and we stand out among other Competitors with Our Advanced-Data scientist Certification Course.

So then it is necessary to learn the course under Experienced Professionals of Data science Training Institute in Bangalore is more than ever in the present business scenario. The need to fill the void for an able data scientist is necessary ever than before. Gone are the days of brick and mortar business. The present business needs to have powerful tools to meet global competition. Unknown challenges, unexpected changes in political and economic status in the global market need to be met suitably by effective business strategies.

 

Likewise choosing Training for the following reasons explained below for the benefit of those who wish to take up this courses. Connect with consumers effectively, knowing them directly help to develop higher-end products that are beneficial both the ways.

Contact Us +91 8147111254

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Why Data Science Training In Bangalore at Prwatech,

We’re India’s Leading Training institute for Python offering world classes Courses with 100% Job assistance.

  • Wi-Fi Class Rooms
  • Get trained by the finest qualified professionals
  • 100% practical training
  • Flexible timings
  • Real-Time Projects
  • Resume Writing Preparation
  • Mock Tests & interviews
  • Access to Our Learning Management System Platform
  • Access to 1000+ Online Video Tutorials
  • Weekend and Weekdays batches
  • Affordable Fees
  • Complete course support
  • Guidance till you reaches your goal.

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 Training 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.

Introduction

  • 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

Functions

  • 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.

Introduction

  • 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
  • CREATE, INSERT, READ, UPDATE and DELETE Operation
  • 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
    Notebooks.
  • 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
    Python

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
    Forests
  • 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 training  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 Training institutes 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 the world-class trainers. i can say this is one of the best training institute for data science in Bangalore

 

Introduction:

 

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

Topics:

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.

INR  16000

35 Hours
Practical 40 Hours
15 Seats
Course Badge
Course Certificate

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