Why Choose Data Science Job Oriented Training & Certification Program?

Data Science Job Oriented Certification And Training Course

Become Experts In Data Science Job Oriented Training And Certification Course

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Advantages of Data Science Job Oriented Certification Training Course

1,00,000 +

Job vacancies across the world


Data Science Experts in the world and the demand is increasing day by day


Jobs In India

6 Lac Pa- 13 Lac Pa

Salary In India

Why Choose Data Science Job Oriented Training & Certification Program?

Data Science helps you in mastering the notions of Python programming. Once you start with the course, you will find yourself getting not only acquainted. but also gaining specialized knowledge and skills in Machine Learning (ML), web scraping, data analysis, data visualization as well as Natural Language Processing. Python, as well as Data Science, are popular and are amongst the highest recruited job positions in the world. Here are some benefits of getting trained and certified in Python with Data Science:• Faster Processing and Development • Easy to Learn • Excellent Community Support for Python • Powerful Packages and Libraries • Incredible Compatibility with Hadoop • Better Data Visualization • Amazing Career Support

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Hiring Partners

We are globally connected with the top IT companies

We are connected with companies with different industries across the nation. Our dedicated placement cell is constantly striving to get more companies on-board

About Data Science Job Oriented Course

Data Science is basically a mixture of multiple algorithms, principles of machine learning, and tools with the end goal of discovering concealed patterns in the raw data available at hand. Thus, after a Data Scientist has decoded the concealed patterns, it is used by the company to make decisions on the basis of the predictions, as concluded by the Data Scientist. A data scientist makes these predictions and come to such conclusions with the aid of tools like prescriptive analytics, machine learning, and predictive casual analytics. Data Science follows a life cycle including six steps. These are the main phrases of the lifecycle of Data Science.•Discovery Data preparation•Model planning Model building•Operationalise •Communicate results regards to the integral tools of Python with Data Science

Data Science Job Oriented Certification Overview

Tracks Regular Track
Duration 500Hrs
Training Days 180 Days


    • All About Python & Python Introduction
    • Python Installation and Environment Setup
    • Syntax of python
    • Data type and Data Structures
    • Advance Containers from collection module
    • Control Statements, Looping in Python
    • Functions in Python
    • Closures and Decorators in Python
    • OOPS & Advanced OOPS
    • Implementation of Data Structures in Python
    • Generators & Iterators in Python
    • Exception Handling&File Handling
    • Data Serialization
    • Installing Third Party Modules in Python
    • Database Connectivity
    • Debugging and Standard Coding in Python
    • Modules and Packages in Python
    • Standard Library in Python
    • Concurrent Execution in Python
    • Socket Programming
    • Mailing in Python
    • Graphical User Interface using Tk
    • Virtual Environment
    • Text Processing
    • APIs
    • Web Scraping
    • GitHub
    • Web Designing
    • Web Development using Django & Flask
    • Flask & Django Web Framework of Python
    • Installing and setting up a Django virtual environment
    • Introduction & Installation of R
    • R Basics
    • Finding Help
    • Code Editors for R
    • Command Packages
    • Manipulating and Processing Data in R
    • Reading & Getting Data into R
    • Exporting Data From R
    • Data Objects-Data Types & Data Structure
    • Viewing Named Objects
    • Structure of Data Items,
    • Manipulating and Processing Data in R (Creating, Accessing , Sorting data frames, Extracting, Combining, Merging, reshaping data frames)
    • Control Structures, Functions in R (numeric, character, statistical)
    • Working with objects
    • Constructing Data Objects
    • Building R Packages
    • Running and Manipulating Packages
    • Nonparametric Tests- ANOVA, chi-Square, t-Test, U-Test
    • Introduction to Graphical Analysis,
    • Using Plots (Box Plots, Scatter plot, Pie Charts, Bar charts, Line Chart)
    • Plotting variables
    • Designing Special Plots
    • Simple Liner & Multiple Regression
    • Introduction to Statistics
    • Descriptive Statistics
    • Summary Statistics
    • Basic probability theory
    • Statistical Concepts (uni-variate and bi-variate sampling, distributions, re-sampling, statistical Inference, prediction error)
    • Probability Distribution (Continuous and discrete- Normal, Bernoulli, Binomial, Negative Binomial, Geometric and Poisson distribution)
    • Bayes’ Theorem
    • Central Limit theorem
    • Data Exploration & preparation
    • Concepts of Correlation,
    • Regression,
    • Covariance
    • Outliers etc.


    • Database Concepts (File System and DBMS)
    • Database Storage Structures (Tablespace, Control files, Data files)
    • Structured and Unstructured data
    • SQL Commands (DDL, DML & DCL),
    • Data ware Housing concept
    • No-SQL
    • Data Models - XML, working with MongoDB),
    • Tools - OLTP and OLAP
    • data preparation and cleaning techniques
    • What is Cloud
    • Public, Private, Hybrid Cloud functionalities and Examples
    • Different Cloud Services IAAS, SAAS, PAAS
    • Understanding Public Cloud Platforms AWS, AZURE, GCP etc.
    • Signing up for AWS account
    • IAM (Identity Access Management)
    • Amazon EC2 (Elastic Compute Cloud) Service
    • Amazon S3 (Simple Storage Service)
    • Amazon RDS (Relational Database Service)
    • Amazon ROUTE-53 (DNS)
    • Amazon Lambda Serverless Computing
    • Launching Instances on AWS
    • Deploying Project Live on AWS servers
    • Introduction to Big Data-
    • Hadoop: 
    • Hadoop ETL: 
    • Hadoop Reporting Tools: 
    • Introduction to Pig and HIVE- Programming
    • HDFS –
    • Hadoop Environment: 
    • Introduction to Apache Spark and Use Cases
    • Apache Spark APIs for large-scale data processing
    • Information Visualization
    • Data analytics Life Cycle
    • Analytic Processes and Tools
    • Analysis vs. Reporting
    • Modern Data Analytic Tools
    • Visualization Techniques
    • Visual Encodings
    • Visualization algorithms
    • Data collection and binding
    • Cognitive issues
    • Interactive visualization
    • Visualizing big data – structured vs unstructured
    • Visual Analytics
    • Geo-mapping
    • Dashboard Design 
    • Introduction to Business Analytics using some case studies
    • Making Right Business Decisions based on data
    • Exploratory Data Analysis –
    • Visualization and Exploring Data
    • Descriptive Statistical Measures
    • Probability Distribution and Data
    • Sampling and Estimation
    • Statistical Interfaces
    • Predictive modeling and analysis
    • Regression Analysis
    • Forecasting Techniques
    • Simulation and Risk Analysis
    • Optimization Linear, Nonlinear, Integer
    • Decision Analysis
    • Strategy and Analytics
    • Overview of Factor Analysis
    • Directional Data Analytics
    • Functional Data Analysis
    • Supervised and Unsupervised Learning
    • Uses of Machine learning
    • Clustering
    • K means
    • Hierarchical Clustering,
    • Decision Trees
    • Oblique trees
    • Classification problems,
    • Bayesian analysis and Naïve bayes classifier
    • Random forest
    • Gradient boosting Machines
    • Association rules learning
    • Apriori and FP-growth algorithms
    • Support vector Machines
    • Linear and Non liner classification
    • Neural Networks and its application
    • Tableau
    • Data Preparation using Tableau Prep
    • Data Connection with Tableau Desktop
    • Basic Visual Analytics
    • Calculations in Tableau
    • Advanced Visual Analytics
    • Level Of Detail (LOD) Expressions in Tableau
    • Geographic Visualizations in Tableau
    • Advanced Charts in Tableau
    • Dashboards and Stories
    • Get Industry Ready
    • Exploring Tableau Online
    • Introduction to Power BI
    • Power BI Desktop
    • Data Analysis Expressions (DAX)
    • Data Visualization
    • Introduction to Power BI Q&A and Data Insights
    • Direct Connectivity
    • Power BI Report Servers
    • Advanced Analytics in Power BI using R & Python

    1.Overview of work environment according to the industry Standard

    • Make them Understand how Companies work, Role & Responsibility of Candidates.
    • How to Build a Data Science Framework designed to handle large volume data sets.
    • How to Developed customized data models and algorithms to apply to data sets.
    • How to Manage and monitor Hadoop log file.
    • We Assign our Customer projects to Candidate they can Solve Live issues relevant to projects.
    • We Train our Candidate how to deploy code on various cloud platform so candidate get enough knowledge about production environments
    • Analysis of Live Server Log Data
    • Building and Deploying Machine Learning Models Live on Servers
    • Case Studies of Various Successfully and Unsuccessful projects & products
    • Deploying a Hadoop Cluster using Industry Ready Environment and Configurations

    1.About Yourself Introductions.

    • Grammar & Vocabulary
    • Interview & Types of the Interview.
    • Different Rounds of Interview.
    • Preparation of personal Interview.
    • Group Discussions.
    • Report & Business Email Writings.
    • Creating Presentations & Presenting Skills.
    • Resume Writing

  • Microsoft Certified Python Programming


Data Analyst :

 An analyst  who collects the data, processes it and performs statistical analysis. According to which he translates the figures into simpler language and helps the organisations and companies to understand how to make better business . 

Docker Engineer:

An engineer who looks for the design, development and implementation of containers and also making the container strategy with infrastructure.

Software Developer / Engineer :

 A software developer or en engineer who have the knowledge of Machine learning and can handle data science roles . People who are skilled in R, Python, Java or other relevant languages and having experts in knowledge graph mining or text mining.

Research Analyst:

A research analyst is a professional who prepares investigative reports on securities or assets for  a client use and is responsible for researching, analyzing, interpreting, and presenting data related to markets, operations, finance/accounting, economics, customers, and other information related to the field they work in.

Data Scientist:

 Data scientists are those who crack complex data problems with their strong expertise in data science which includes python programming concept, data analysis and interpretation. Their work is to work with  various mathematics, statistics, computer science-related problems and provide a  growth solution to the organization.

  • 100% Job Guarantee
  • Live Project Assessment
  • Weekly analysis and reports
  • Live industry training in our company
  • Communication skills preparation
  • Lifetime Career support

Enrollment For Data Science Job Oriented Course


What world is talking about us

Job Oriented Program

Our Job Oriented Program is one of a kind and a unique program that offers you 100% job guarantee right after completing the certification program and training with us. It is one of our renowned programs for producing job ready and experienced candidates with apt technical and soft skill knowledge demanded in the prompt evolving IT and digital industries.

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Our Team

Mr Akhilesh Jain G

Akhilesh Jain

10+ Years Experience B.Tech, AWS-CSA, RHCE & RHCSS Expertise in Network Security & AWS

Mr. Rajat Goyal

Rajat Goyal

10+ Years Experience B.Tech, RHCE, RHCSS, Cloud Certified Expertise in Linux, Cloud & Scripting

Ravi Sarswat

10+ Years Experience MCA, RHCE, RHCVAExpertise in Linux & Virtualization

Mr . Gaurav Saluja

Gaurav Saluja

10+ Years Experience B.Tech, RHCA-Level5, RHCDS, RHCSS, RHCVA, RHCE Expertise in Linux Troubleshooting & Tuning

Sachin Yadav

Sachin Yadav

5+ Years Experience B.Tech, RHCE, Python Certified Expertise in R & Python ,Data science & Artificial Intelligence


Nidhi Sharma

4+ Years ExperienceMBA, Career CounselorExpertise in Career Counselling  

Mr. Pawan Khatri

Pawan Khatri

4+ Years Experience MCA, Career Counselor Expertise in Soft Skills Training

Nikhil Maheshwari

2.5 + years ExperienceB.Tech, RHCSA ,RHCEExpertise in Redhat Linux &Cloud computing(AWS)

Nidhi Singh Choudhary

4+Years Experience B.Tech , BDM , Softskills TrainerExpertise in Career Counselling and Softskills

Kushal Samota

3+years ExperienceB.Tech. Expertise in Redhat Linux, Ansible,DevOps,Docker ,Cloud

Shahrukh Khan

2+ years experienceB.Tech, Rhcsa,Rhce, Ansible,AWSExpertise in Linux,AWS And Ansible

Naveen Singh

15+ years experienceExpertise in Softskill and communication training,BPO training,IELTS &TOEFLManager-Placement and company tie ups

Vijender Kumawat

9+ years experienceM.tech, B.techExpertise in Digital Marketing

Ravi Swami

2+ years experienceB.Tech, Rhcsa,Rhce, Ansible,AWSExpertise in Linux,AWS And Ansible, Python MySQL

Rupesh Saini

BCA RHCSA, RHCE, Experties in Ansible Automation, RHCVA, Red Hat Enterprise Linux Diagnostics and Troubleshooting, Docker, Kubernetes, OpenShift, Server Security, CompTIA A+,CompTIA N+, CSCU

Jyoti Gautam

3 years experienceMCA Expertise in RHCSA, RHCE, AWS, Azure, GCP, Docker & container, K8, Openstack

Simran Grover

3 Years ExperienceB.TechExpertise in Python, Web Design(html,css,bs), Web Development, Data Science, Machine Learning, Data Analytics, Big Data

Mayank Sharma

1.5 Years ExperienceB.TechExpertise in AWS, Azure, RHCSA, RHCE,  Sys-Admin, Office365, Logic Monitor

1 Year Diploma Program

Absolutely FREE & 100% JOB GUARANTEE

Get training on Linux, Ansible, Devops ,Python , Networking , AWS and Openstack Cloud by Certified Trainers at GRRAS. You would be able to get the best training along with the interview preparation in this course module .

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