Project Description


About Data Science

Data Science is a blend of various tools, algorithms, and machine learning principles with the goal to discover hidden patterns from the raw data.It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science, in particular from the subdomains of machine learning, classification, cluster analysis, data mining, databases, and visualization.

Either it is structured or unstructured data, Data Science is a field that encompasses anything related to data cleansing, preparation, and analysis.

Job Responsibilities of Data Science

  • Collecting large amounts of unruly data and transforming it into a more usable format.
  • Solving business-related problems using data-driven techniques.
  • Working with a variety of programming languages, including SAS, R and Python.
  • Having a solid grasp of statistics, including statistical tests and distributions.
  • Staying on top of analytical techniques such as machine learning, deep learning and text analytics.
  • Communicating and collaborating with both IT and business.
  • Looking for order and patterns in data, as well as spotting trends that can help a business’s bottom line


Data visualization:

The presentation of data in a pictorial or graphical format so it can be easily analyzed.

Machine learning

A branch of artificial intelligence based on mathematical algorithms and automation.

Deep learning

An area of machine learning research that uses data to model complex abstractions.

Pattern recognition

Technology that recognizes patterns in data (often used interchangeably with machine learning)

Data preparation

The process of converting raw data into another format so it can be more easily consumed.

Text analytics

The process of examining unstructured data to glean key business insights.

Database Querying Language

SQL, or Structured Query Language, is a special-purpose programming language for managing data held in relational database management systems. Almost all structured data is stored in such databases, so, if you want to play with data, chances are you’ll want to know some SQL

Database management systems
  • Hadoop
  • MongoDB
  • SQL Server
  • Oracle
  • MySQL
Statistical Programming Languages:
  • Python
  • Java
  • C++
  • PERL
  • Ruby
  • C#
Statistical Analysis Tools
  • R Tool
  • SAS
  • Matlab
  • SPSS
  • STtata
  • Minitab

DataScience Course

This data science course will provide you a strong foundation to understand Machine Learning Algorithms like Clustering, Random Forest, Decision Trees, Naive Bayes using R and Concepts of Statistics, Time Series, Text Mining.

At the end of this Data Science training, you should be prepared to take up an exciting job opportunity in the field of Data Science

On successful completion of the course, candidates will be able to:

  • Analyze Big Data using R, Hadoop and Machine Learning.
  • Understand the responsibilities of a Data Scientist
  • Understand the use of machine learning algorithms in R
  • Learn about the processes involved in the Data Analysis Life Cycle
  • Learn how to use data formats including XML, CSV and SAS, SPSS
  • Transform data using best practices and tools
  • Learn to implement various Data Mining techniques
  • Analyse data using Hadoop Mappers and Reducers
  • Follow best practices in data visualization and optimization techniques

Following Professionals are recommended for Data Science Training.

  • Systems Analysts and programmers interested in expanding their role as a Data Scientist
  • ‘R’ professionals who want to captivate and analyze Big Data
  • Hadoop Professionals who want to learn R and ML techniques
  • Entry-level Data Analysts wanting to understand Data Science methodologies
  • Hadoop Professionals who want to learn R and ML techniques
  • Non-IT professionals aspiring to get into Data Analytics.
  • SAS/SPSS Professionals looking to gain understanding in Big Data Analytics
  • Business and data analysts looking to add big data analytics skills, & to understand Machine Learning (ML) Techniques
  • Managers of business intelligence, analytics, or big data groups
  • College graduates considering data science as a career field
  • Information Architects who want to gain expertise in Predictive Analytics

Data Science is a booming demand for skill across industries, which is suited for all individuals at all levels of experience.


Numaware Trainings provide completely practical and real time DataScience Training starts from basics to advanced modules. Get an introduction to the fundamentals of DataScience and gain proficiency in identifying terminologies and concepts in the DataScience environment

Give Miss Call to +91-9916-566-300 for further more details on DataScience Training

Detailed Course Content

What is R Tool Programming Language?
R is an open source programming language and software environment for statistical computing and graphics that is supported by the R Foundation for Statistical Computing.[6] The R language is widely used among statisticians and data miners for developing statistical software and data analysis.  Polls, surveys of data miners, and studies of scholarly literature databases show that R’s popularity has increased substantially in recent years

R is an interpreted language; users typically access it through a command-line interpreter.

Indexing a data structure(dataset)

  • Getting a subset of a data structure
  • Making a vector filled with values
  • Information about variables
  • Working with NULL, NA, and NaN
  • Generating random numbers
  • Generating repeatable sequences of random numbers
  • Saving the state of the random number
  • Saving the state of the random number
  • Rounding numbers
  • Comparing floating point numbers

Data Input and output

  • Loading data from a file
  • Loading and storing data with the keyboard
  • Running a script
  • Writing data to a file
  • Writing text and output from analyses to a file

Data manipulation

  • Sorting
  • Randomizing order
  • Converting between vector types
  • Finding and removing duplicate records
  • Comparing vectors or factors with NA
  • Recoding data
  • Mapping vector values
  • Renaming levels of a factor
  • Re-computing the levels of factor
  • Changing the order of levels of a factor
  • Renaming columns in a data frame
  • Adding and removing columns from a data
  • Reordering the columns in a data frame
  • Merging data frames
  • Comparing data frames
  • Re-computing the levels of all factor
  • Converting data between wide and long
  • Summarizing data
  • Converting between data frames and
  • Calculating a moving average
  • Averaging a sequence in blocks
  • Finding sequences of identical values
  • Filling in NAs with last non-NA values

Basic statistics

  • Summarizing data
  • Descriptive statistics
  • Frequencies

Advance statistics

  • t-test
  • Frequency tests
  • Logistic regression
  • Survival analysis
  • Robust and time series models
  • Regression and correlation
  • Multiple regression
  • Homogeneity of variance
  • Inter-rater reliability
  • Power Analysis
  • Nonparametric Statistics


  • Bar Plots
  • Line Charts
  • Boxplots
  • Scatterplots
  • Density Plots
  • Dot Plots

Advanced graphs

  • ggplot2 full package


Role : Data Science Solution lead
Experience : 15+ Yrs of IT Experience across MNC Companies
Technologies : Data Science, SAS, R , Python, Machine Learning, Advanced Analytics, Bigdata..etc.
About Trainer :

Data scientist solution lead with a demonstrated history in leading development of data science solutions and nearly 15 years of experience in Solution Architecture, Business Analysis, Data Analysis, Software Design, Analysis & Development. Skilled in Machine Learning statistical data analysis, predictive modeling, neural networks and text mining. Plays key role in Analytics team to help the business in improving customer satisfaction and reduce operation costs through data driven techniques.

Certifications : SAS Certified Data Scientist
Certified R Programmer from Advancer

Role : Senior Technical Analyst
Experience : 9+ Yrs of IT Experience across MNC Companies
Technologies : Data Analytics, Data Science, R, SQL, Hive SharePoint Server, Azure Machine Learning
About Trainer : Data Scientist with 8 years of hands on experience in Machine Learning and data analytics tools SAS, R, MySQL, Python, Hadoop and  Tableau. Currently working with various data owners and data stewards from Finance, Healthcare Quality, Customer Quality, Markets and IT to understand and drive delivery of data management objectives. Training on Various intermediate and advanced levels topics in data science analytics using R for corporate Companies and Clients. Passion about data analytics and solving the complex issues in business using advanced data analytics.
Certifications : MCSA Machine Learning
MCTS- Microsoft Office SharePoint Server 2007 Application Development
Microsoft Office Specialist – Excel 2010


We support! You Certify

Numaware Technologies provides certification trainings and also support you with getting certified in desired skill sets.

Imp Note: There are no universally required or accepted certifications in the world of data science and/or analytics. 

Data Science is a combination of technical skill and Soft Skill to turn data in to actionable sight. Data science is a “concept to unify statistics, data analysis and their related methods” in order to “understand and analyze actual phenomena” with data. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science, in particular from the subdomains of machine learning, classification, cluster analysis, data mining, databases, and visualization. The best way to become a data scientist or analyst is to gain the requisite skills and develop a history of showing how you added value with those skills.

Languages or skills like SQL, Python, R, SAS are elementary to become a data analyst or data scientist and below are the few some data science certifications that are widely recognized by industry:

Cloudera Certified Professional Data Scientist

The CCP Data Scientist is geared toward data scientists who can design and develop scalable and robust solutions for production environments. Candidates need to pass three exams: Descriptive and Inferential Statistics on Big Data, Advanced Analytical Techniques on Big Data, and Machine Learning at Scale. Each exam is a challenge scenario, and you are given eight hours to complete it. All three exams must be taken within 365 days of each other.,

CCP certifications are valid for three years.

For more info, click on following link

SAS Certified Data Scientist

The following list of exams are srerequisite to complete the SAS Certified Data Scientist.

  • SAS Certified Big Data Professional
  • SAS Certified Advanced Analytics Professional

Candidates for the Data Scientist certification should have deep knowledge of and skills in manipulating big data using SAS and open source tools, using complex machine learning models, making business recommendations, and deploying models. Candidates must pass five exams to earn the SAS Certified Data Scientist credential. The data science certification program comprises the focus areas of both the SAS Certified Big Data Professional and the SAS Certified Advanced Analytics Professional programs, including:

SAS “versioned” Certificates, such as the SAS Certified Data Scientist Using SAS 9, do not expire.

Dell EMC Data Science Associate

The Dell EMC Data Scientist Associate (EMCDSA) is a foundational certification that exposes you to the basics of big data and data analytics. Topics for this certification include an introduction to data analytics, characteristics of big data and the role of data scientists. Also covered are a variety of big data theories and methods, including linear regression, time-series analysis and decision trees.

This exam focuses on the practice of data analytics, the role of the Data Scientist, the main phases of the Data Analytics Lifecycle, analyzing and exploring data with R, statistics for model building and evaluation, the theory and methods of advanced analytics and statistical modeling, the technology and tools that can be used for advanced analytics, operationalizing an analytics project, and data visualization techniques. Successful candidates will achieve the EMC Proven Professional – Data Science Associate credential.

Trainings and Batches

Mode of Training

Numaware provides the following list of trainings according to Trainee or Colleges or Organization preference

  • Classroom Training
  • Online Training
  • Corporate Training
  • Campus Training
  • University Training
  • Virtual Instructor-Led Training
  • Instructor-led Live Classroom Training

Batches Available

We are Flexible with following list of batches as per the student requirements and availability.

  • Regular Batch
  • Weekend Batch
  • Weekday Batch
  • Fast-Track Batch
  • One to One Batch
  • Customized Batch

Flexible Timings

Numaware providing Flexible timings to schedule the Batches according to student-preferred timings at either Morning or Evening

  • Morning : 6.00 AM to 12.00PM
  • Evening : 3.00 PM to 10.00PM

Affordable Fees

We Charge very nominal, least and best price for all trainings when compared to Market or any other institutes with good quality standards and no compromise on commitment of providing Quality of Training.

Digital and Flexible Payment Options are available with Numaware Technologies Pvt. Ltd

  • Cash with Invoice
  • Credit-Card Pay
  • Debit-Card Pay
  • Any Digital-Pay
  • Account Transfer
  • Pay-Tm Transfer

Note: Fee will be finalized after demo session as per the Trainer suggestions and Student requirement.

Numaware Benefits

Numaware Technologies Pvt. Ltd is one of the best training institutes in Bangalore, offering Job demanding IT courses, Niche skills for working professionals, fresher’s, and students to ensure a successful future. We offer 100% placement support, cost-effective courses, real-time project experience, resume support, interview support and more. Our courses will equip you to get jobs in top MNCs and launch a successful career.

TRAINING BENEFITS in Numaware Technologies :

  • Training with IT Industry experts and Certified professional s working in MNC Companies.
  • Importance given to both theory and practice
  • Hands-on experience in real-time projects
  • Assistance in all stages of getting a job
  • Proven track record
  • Limited students in a batch
  • Flexible timings
  • Certification support

STUDENT BENEFITS in Numaware Technologies:

  • Post-training and on-job support
  • Backup classes for missed sessions
  • Remote lab facility, Wi-Fi access and LED TV projection
  • Mock exams and interviews for real-life simulation experience
  • Affordable fees with 2 easy installments

PLACEMENT BENEFITS in Numaware Technologies:

  • Our recruitment team will send you for interviews till you get placed
  • Frequently asked interview Q & A will be shared
  • Resume build support from industry professionals
  • We train you with real cases studies for interviews
  • Emphasis on practical knowledge in everything

Job Demanding Courses

Numaware Trainings is a Platform for Learning Technologies

Learn what really matters

Just work hard and focus on your job… because luck truly favors the prepared!!
All the best for your career

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