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Starting a Career in Data Science: Data Science training in Delhi | Noida | NCR

Data Science can be described as a multidisciplinary tool that uses scientific methods, procedures, algorithms, and systems to derive insights from structured and unstructured data. In technical terms, Data Science is the convergence of analytics, data mining, and computer learning with the goal of comprehending and understanding real-world phenomena through data. Data Science cannot be considered a strictly scientific method since it integrates methods and ideas from a number of backgrounds, including mathematics, statistics, computer science, and information science. The three primary components of data science are data organisation, data packaging, and data delivery. Data Science is the process of analysing data and using the findings to draw conclusions and make decisions.

data science training in noida

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  • Starting a Career in Data Science
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  • About Classes of Data Science Training in Noida
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  • Data Science Training Course Content
  • 3 Best research Areas on data science training
  • Who are Data Scientists?
  • What does it mean to be a Data Scientist?
  • Data Scientist Role and Responsibilities

  • Common Data Scientist Job Titles
  • Data Science Career Outlook and Scope in India
  • Data Scientist Salaries
  • Top 15 data science certifications
  • Top Recruiters
  • Essential Data Science Skills
  • Job opportunities (Careers) in Data Science
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About Classes of Data Science Training in Noida

Data Science Components: Machine Learning
Most employers look for data science professionals with advanced degrees, such as a Master of Science in Data Science. Candidates for data science roles usually begin with a foundation in computer science or math and build on this with a master’s degree in data science, data analytics, or a related field.

Best career path for IT Graduates

In these graduate-level programs, professionals gain core competencies in skills such as predictive analytics, statistical modeling, big data, data mining applications, enterprise analytics, data-driven decision making, data visualization, and data storytelling.

Data Science Training Students Reviews, 4Achievers Data Science Training in Noida

Data Science Training in Noida
Verified User

Saurabh Mahapatra I have completed my b tech in in computer science year year 2019 address and recently I have just got the recommendation from one of my friend for 4 achievers for the data science course which is top 10 trending courses where we can get easily a good package job. 4 achievers is the best data science training institute in Noida I am having a good instructor of data science and got the good practice over live test project and completed my training at very minimum duration of an got selected in company e having good package and I can recommend 4 achievers for data science courses.

Reviewed by
Saurabh Mahapatra
01/2/2021
Data Science Training in Noida
Verified User

I am Prabhakar Saini recommending the 4 achievers for data science courses student who have just completed their BTech and looking forward trending courses which can help to get a job with good package data science is a best options I have my own just completed my data science training with 4 achievers and got placed in MLC and gain a good package which is more compatible for my skills and training facility is what I have been there with 4 achievers.

Reviewed by
Prabhakar Saini
12/2/2021
Data Science Training in Noida
Verified User

My name is Sushma Khatri I have just completed my data science training with 4 achievers trainer is a very competent for giving a good training material and complex learning models and live projects help me to understand the data science practices logic module implementations and easily convert my all the skills what I have learnt in BTech and in between of training schedule I have just be aware and confident enough for data science technology and now I have just place in a good MNC over good package so I am just recommending to all of you to join data science training with 4 achievers

Reviewed by
Sushma Khatri
1/2/2021
Data Science Training in Noida
Verified User

Sushma Bharati having a good experience over data science from last 3 year over a reputed MNCs in India and I'd like to prefer recommendation for 4 achievers because I like to continue my advanced training of data science which is more compatible and needed for the programming for complex data units. My company always insisted us to grow with the skills of programming and logical and data values and inputs so we find out the advanced training of data science and we have research in Noida and find out the 4G was is the best institute for data science training and I have completed and gain a good knowledge and practice.

Reviewed by
Sushma Bharati
3/3/2021

MS Project Training Key Features, 4Achievers MS Project Training in Noida

Data Science
180 Hours of Intensive Classroom & Online Sessions and 150+ Hours of Practical Assignments
Data Science
Certificate of Completion as candidates completes the course successfully.
Data Science
Data Science Training and Project Certificate
Data Science
Opportunity to work on live projects
Data Science
Job Placement Assistance with Top recuriters

Data Science Training Upcoming classes, 4Achievers Data Science Training in Noida

Data Science Training Batch 1

Starting Date of Registration

06, April, 2021

12:00 AM

Last Date of Registration

28, April, 2021

till 12:00 PM

Data Science Training Batch 2

Starting Date of Registration

1st, May, 2021

12:00 AM

Last Date of Registration

15th, May, 2021

till 12:00 PM

Data Science Training Batch 3

Starting Date of Registration

16th, May, 2021

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Last Date of Registration

28th, May, 2021

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Data Science Training Batch 4

Starting Date of Registration

1st, June, 2021

12:00 AM

Last Date of Registration

15th, June, 2021

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Data Science Training Batch 5

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16th, June, 2021

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Last Date of Registration

28th, June, 2021

till 12:00 PM

Data Science Training Batch 6

Starting Date of Registration

1st, July, 2021

12:00 AM

Last Date of Registration

15th, July, 2021

till 12:00 PM

Data Science Training Batch 7

Starting Date of Registration

16th, July, 2021

12:00 AM

Last Date of Registration

28th, July, 2021

till 12:00 PM

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Data Science training in Delhi | Noida | NCR

Looking for the Best Data Science training  in Delhi | Noida | Greater Noida| NCR. Data Science training in Noida provided by 4Achievers with 100% real-time, practical and placement. Our instruction help pros to successfully procure places in various MNCs. Training in Noida provides training with real-time working professional which will surely help students and trainees getting trained in practical real-time scenarios that will definitely help you to accomplish certification. 4Achievers gives the best Data Science Course at Noida as a present sector standards.
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About Data Science Course

Data Science Components: Machine Learning

Data Science Components: Machine Learning
Machine Learning involves the use of algorithms and mathematical simulations to train machines and enable them to respond to developments in the world around them. Time series forecasting, for example, is widely used in trading and financial processes these days. The computer will forecast the results for the coming months or years based on past data trends. This is an example of machine learning in action. Humans generate a massive amount of data every day in the form of clicks, requests, videos, photos, tweets, posts, RSS feeds, and so on.

Data Science Components: Big Data and Business Intelligence

Big Data is a term used to describe large amounts of unstructured data. Big Data technologies and methods specifically assist in the translation of unstructured data into structured data. Consider someone who needs to keep track of the pricing of various goods on e-commerce pages. Using Online APIs and RSS Feeds, he can get data on the same brands from various websites. Then arrange them in a formal manner.
Business Intelligence: Any business has and generates an excessive amount of data on a daily basis. When closely analysed and viewed in visual presentations of diagrams, this evidence will help people make better decisions. This will assist managers in making the right judgement possible by thoroughly delving into the themes and information brought to light by the studies.

Data Science Qualification

Data Science Required Qualifications : Tools: R knowledge

To become a data scientist, you'll need the following skills:
R knowledge: R is used for data processing, as a programming language, as a mathematical analysis environment, and for data visualisation.

Data Science Required Qualifications : Tools: Python coding

Python coding: Python is widely used to apply mathematical structures and principles since it has a large number of libraries and packages that can be used to create and execute models.

Data Science Required Qualifications : Tools: MS Excel

MS Excel: For all data entry work, Microsoft Excel is considered a must-have. It comes in handy when dealing with vast quantities of data and applying formulae, calculations, and diagrams.

Data Science Required Qualifications : Tools: Hadoop

Hadoop Platform is a distributed computing system that is open source. It's used to keep track of how large data programmes are processed and stored.

Data Science Required Qualifications : Tools: SQL database

SQL database/coding is mostly used for dataset preparation and extraction. It can also be used to solve issues such as graph and network analysis, search behaviour, fraud detection, and so on.

Data Science Required Qualifications : Tools: Technology

With so much unstructured data available, it's important to know how to use it. This can be accomplished in a multitude of ways, including by APIs and web servers.

Data Science Required Qualifications : Methodology

Data scientists also focus on machine learning algorithms like regression and classification. Clustering, time series, and other methods that are based on mathematical algorithms necessitate a high degree of mathematical understanding. Working with unstructured data: Since much of the data generated every day is unstructured, such as photographs, remarks, tweets, search history, and so on, learning how to turn this unstructured data into a standardised form and then working with it is a very useful ability in today's market.

Data Science Required Qualifications: Understanding of Business

Business Acumen: Analytics professionals work their way up the corporate ladder from mid-management to high-management. As a result, gaining market experience is a must for them.

Data Science Training Syllabus

Module 1: Python

Python is the most important and necessary topic that every data scientist should have knowledge about. In this section, our instructors will take you through the basics of Python and areas where it can be used. You will learn how to use some of the current tools such as Numpy, Pandas, and Matplotlib. Therefore, module 1 includes –
Environment set-up
Jupyter overview
Python Numpy
Python Pandas
Python Matplotlib

Module 2: R

Used for statistical and data analysis, R programming language is one of the advanced statistical languages used in data science. This module teaches you how to explore data sets using R. Here you will learn –
An introduction to R
Data structures in R
Data visualization with R
Data analysis with R

Module 3: Statistics

When working with data, the knowledge of statistics is necessary and an important skill set that you must have. In this module, you will learn –
Important statistical concepts used in data science
Difference between population and sample
Types of variables
Measures of central tendency
Measures of variability
Coefficient of variance
Skewness and Kurtosis

Module 4: Inferential statistics

Inferential statistics is used to make generalizations of populations, from which samples are drawn. This is a new branch of statistics, which helps you learn to analyze representative samples of large data sets. In this module, you will learn –
Normal distribution
Test hypotheses
Central limit theorem
Confidence interval
T-test
Type I and II errors
Student’s T distribution

Module 5: Regression and Anova

This lesson will help you understand how to establish a relationship between two or more objects. ANOVA or analysis of variance is used to analyze the differences among sample sets. Here you will learn –
Regression
ANOVA
R square
Correlation and causation

Module 6: Exploratory data analysis

In this lesson you will learn –
Data visualization
Missing value analysis
The correction matrix
Outlier detection analysis

Module 7: Supervised machine learning

This is a comprehensive module to help you understand how to make machines or computers interpret human language. You will learn –
Python Scikit tool
Neural networks
Support vector machine
Logistic and linear regression
Decision tree classifier

Module 8: Tableau

Tableau is a sophisticated business intelligence tool used for data visualization. In this lesson, you will learn –
Working with Tableau
Deep diving with data and connection
Creating charts
Mapping data in Tableau
Dashboards and stories

Data Science Training Course Content

Fundamentals of Data Science

Introduction to Big Data, Data Science, and Predictive Analytics
• Introduction to Azure ML Studio
• Fundamentals of Data Mining
• Introduction to R Programming

Fundamentals of Data Science

Data Exploration, Visualization, and Feature Engineering
• Hands-On Labs: Data Exploration, Visualization, and Feature Engineering
• Machine Learning Fundamentals

Classification Algorithms

• Introduction to Predictive Modeling
• Decision Tree Learning
• Logistic Regression
• Naïve Bayes
• Hands-On Lab: Building a Classifier
• Hands-On Activity: Determining the best split for

Classification Models, Evaluation and Cross Validation Regression Algorithms

• Linear Regression
• Regularized Regression Models
• Hands-On Lab: Building a Regression Model
• Hands-On Activity: Evaluating Performance, Finding
Maxima and Minima, Gradient Descent, Visualizing
Features and Parameters

Unsupervised Learning

• K-Means Clustering
• Hands-On Lab: Using K-Means Clustering
• Text Analytics
• Content-Based and Collaborative Filtering
• Evaluation of Recommendation Systems. DCG, nDCG
• Hands-On Lab: Analyzing a Document Collection
• Hands-On Activity: Using TF-IDF and Cosine Similarity
to Query a Document Collection

Recommender Systems

• Bootstrapping, Bagging, and Boosting
• AdaBoost
• Random Forests
• Hands-On Lab: Building a Random Forest Classifier
• Hands-On Activity: Calculating Probabilities with
Binomial Distribution, Sampling with and without Replacement Ensemble Methods

Operationalizing Machine Learning Models

• Metrics and Methods for Evaluating Classification and Regression Models
• Tuning Machine Learning Algorithm Parameters
• Hands-On Lab: Building a Classification Model in Azure
ML Studio • Hands-On Lab: Deploying a Predictive Model as a Service

Fundamentals of Big Data Engineering

• Introduction to Large-Scale Online Systems • Hive Tutorial • Hands-On Labs: Creating a Hadoop Cluster and Writing Hive Queries

Handling Real-Time and Streaming Data

• Message Queues and Real-time Analytics
• Hands-On Lab: Creating a Streaming Analytics Pipeline

Data Science Essentials

• Introduction to Online Experimentation and A/B Testing
• Hands-On Activity: Performing a t-Test

3 Best research Areas on data science training

data science training in noida

Efficient graph processing at scale

One field that needs efficient graph processing is social media analytics. The role of graph databases in big data analytics is covered extensively in research. Working on efficient graph processing on a large scale remains a fascinating problem. The research problems to handle noise and uncertainty in the data:- Identify fake news in near real-time: Fake news spreads like a virus in a bursty manner, so dealing with it in real-time and at scale is a pressing problem. The data may come from Twitter or fake URLs or WhatsApp. It could appear to be an authenticated source, but it may also be a fake, making the problem more challenging to solve.

Machine Translation to Local Languages Using Neural Networks

One can use Google translation for neural machine translation (NMT) activities. However, with government funding, there is a lot of research being done in local universities to do neural machine translation in local languages. The latest advances in Bidirectional Encoder Representations from Transformers (BERT) are changing the way of solving these problems. It is possible to join those projects in order to solve real-world problems. At a large scale, effective graph processing: Social media analytics is one field where efficient graph processing is needed. In the research work, the role of graph databases in big data analytics is extensively discussed. Working on efficient graph processing on a large scale remains a fascinating problem.

Detect fake news in near real-time

The following are the issues that need to be addressed in order to deal with data noise and uncertainty: - Detect fake news in near real-time: Managing fake news in real-time and at scale is a pressing issue, as fake news spreads like a virus in a bursty manner. The details could have come from Twitter, fake URLs, or WhatsApp. It may appear to be an authenticated source, but it could also be a fake, making the problem more difficult to solve. Google Translation for Neural Machine Translation (NMT) to Local Languages: For neural machine translation (NMT) operations, Google Translation can be used. However, with government funding, there is a lot of research being done in local universities to do neural machine translation in local languages. Bidirectional Encoder Representations from Transformers (BERT) is a recent development that is revolutionising how these problems are solved. You will participate in such programmes to help solve real-world problems.

Who are Data Scientists, and what do they do?

A Data Scientist is a person who specialises in data science in simple terms. The term "data scientist" was coined by DJ Patil and Jeff Hammerbacher and has since gained popularity. Experts in particular research areas, data scientists apply their skills to solve complex data problems.

What is a Data Scientist and what does it entail?

We now know how data science operates, at least in the tech industry. Data scientists must first build a stable data foundation before conducting rigorous analytics. They then use online experiments, among other methods, to achieve long-term growth. Finally, they build machine learning pipelines and personalised data products to obtain a deeper understanding of their business and customers and to make better decisions. In other words, in the field of technology, data science is concerned with infrastructure, testing, machine learning for decision-making, and data objects.

Data Scientist Role and Responsibilities

Data scientists work closely with business associates to identify their priorities and how data can assist them in achieving them. They create algorithms and statistical models to extract the data the organisation needs, as well as assist in data interpretation and peer exchange. Despite the fact that each project is unique, here is a general overview of the data collection and analysis process:

  1. Start the exploration process by asking the right questions.
  2. Gather information
  3. Cleanse and process the data
  4. Compile and save data
  5. Data investigation and exploratory data analysis are the first steps in the data analysis process.
  6. Choose one or more possible models and algorithms to work with.
  7. Use data science techniques like machine learning, mathematical modelling, and artificial intelligence to solve problems.
  8. Evaluate and develop outcomes
  9. Inform stakeholders about the final outcome.
  10. Make changes in response to feedback
  11. Use the same steps to solve a new problem.

data science training in noida

Common Data Scientist Job Titles

Data Scientist Job

The most common careers in data science include the following roles.

  1. Data scientists: Design data modeling processes to create algorithms and predictive models and perform custom analysis
  2. Data analysts: Manipulate large data sets and use them to identify trends and reach meaningful conclusions to inform strategic business decisions
  3. Data engineers: Clean, aggregate, and organize data from disparate sources and transfer it to data warehouses.
  4. Business intelligence specialists: Identify trends in data sets
  5. Data architects: Design, create, and manage an organization’s data architecture

Data Science Career Outlook and Scope in India

E-commerce
E-commerce and retail are some of the most important sectors that need data processing at the largest stage. The successful implementation of data analysis would allow the e-commerce organisations to forecast the sales, income, losses and even trick consumers into purchasing products by monitoring their behaviour. Retail brands analyse customer profiles and based on the findings, they market the related goods to drive the customer into buying.

Data Science Career Outlook and Scope in India

Manufacturing

Data Science is used in manufacturing for a number of purposes. The main use of data science in manufacturing is to impact efficiency, minimise risk, and increase benefit. Following are the few fields where Data Science can be used to enhance efficiency, processes and forecast the trends

Performance, quality assurance, and defect tracking

Predictive and conditional maintenance Demand and throughput forecasting Links with suppliers and the supply chain Pricing on the global market Designing new facilities and automating existing ones For product development and production techniques, new processes and materials are being developed. Greater energy production and sustainability.

Finance & Banking

The banking sector has been rapidly changing since the financial crisis of 2008. Banks were among the first to use information technology to enhance their processes and security. Banks are using technology to better understand their clients, maintain them, and attract new ones. Financial firms are using data mining to better understand their customers' transactional behaviours, enabling them to communicate with them more meaningfully. The transaction data that banks have access to is used in risk and fraud management. The implementation of data science has resulted in better control of each client's personal data. Banks are starting to realise the value of collecting and analysing not only debit and credit transactions, but also purchase histories and trends, modes of communication, Internet banking data, social media, and mobile phone use.

Health-care services

Every day, electronic medical records, billing, clinical systems, data from wearables, and other sources generate massive amounts of data. This provides a significant opportunity for healthcare providers to improve patient care by using actionable lessons from past patient records. Of course, data science is the driving force behind it. The healthcare industry is being revolutionised by data scientists all over the world. They're working to optimise every aspect of healthcare operations by unlocking the potential of data, from optimising care quality to achieving operational experience.

Data Scientist Salaries

Data Science salaries

Salary packages of data scientists depend on their qualifications, job roles, job profiles, and years of experience. The annual package of a fresher usually lies between 6 lakh to 8 lakh per annum (as per Payscale.com). The table below consists of the average salary packages offered to different job roles of a Machine Learning Professional (as per Payscale.com).

Job Profile (Avg Annual Package (In Rupees))

  1. Data Analyst: 1,97,000 - 9,12,000
  2. Data Scientist: 3,37,000 - 20,00,000
  3. Software Developer : 2,06,000 – 10,00,000
  4. Sr. Software Engineer/Developer/Programmer: 4,13,000 - 20,00,000
  5. Senior Business Analyst: 4,29,000 – 20,00,000
  6. Business Analyst, IT: 2,86,000 – 10,00,000
  7. Senior Data Analyst: 3,10,000 - 10,00,000
  8. Software Engineer/Developer/Programmer: 2,32,000 – 10,00,000

Top Recruiters

Below is the list of some renowned companies that recruit data scientists

Job Profile (Avg Annual Package (In Rupees))

  1. Amazon
  2. LinkedIn
  3. IBM
  4. Walmart Labs
  5. Busigence Technologies
  6. Fractal Analytics
  7. Sigmoid
  8. Flipkart
  9. Mate Labs
  10. Couture
  11. and many more

Data Science Career Outlook and Scope in India

Essential Data Science Skills

Data Science Career Outlook and Scope in India

Most data scientists use the following core skills in their daily work

  1. Statistical analysis: Identify patterns in data. This includes having a keen sense of pattern detection and anomaly detection.
  2. Machine learning: Implement algorithms and statistical models to enable a computer to automatically learn from data.
  3. Computer science: Apply the principles of artificial intelligence, database systems, human/computer interaction, numerical analysis, and software engineering.
  4. Programming: Write computer programs and analyze large datasets to uncover answers to complex problems. Data scientists need to be comfortable writing code working in a variety of languages such as Java, R, Python, and SQL.
  5. Data storytelling: Communicate actionable insights using data, often for a non-technical audience.
  6. Data scientists play a key role in helping organizations make sound decisions. As such, they need “soft skills” in the following areas.

Starting a Career in Data Science

Job Profile (Avg Annual Package (In Rupees))

Most employers look for data science professionals with advanced degrees, such as a Master of Science in Data Science. Candidates for data science roles usually begin with a foundation in computer science or math and build on this with a master’s degree in data science, data analytics, or a related field.
In these graduate-level programs, professionals gain core competencies in skills such as predictive analytics, statistical modeling, big data, data mining applications, enterprise analytics, data-driven decision making, data visualization, and data storytelling.

Data Science Career Outlook and Scope in India

Top 15 data science certifications

Important Certification on Data Science

  1. Certified Analytics Professional (CAP)
  2. Cloudera Certified Associate (CCA) Data Analyst
  3. Cloudera Certified Professional (CCP) Data Engineer
  4. Data Science Council of America (DASCA) Senior Data Scientist (SDS)
  5. Data Science Council of America (DASCA) Principle Data Scientist (PDS)
  6. Dell EMC Data Science Track (EMCDS)
  7. Google Professional Data Engineer Certification
  8. IBM Data Science Professional Certificate
  9. Microsoft Certified: Azure AI Fundamentals
  10. Microsoft Certified: Azure Data Scientist Associate
  11. Open Certified Data Scientist (Open CDS)
  12. SAS Certified AI & Machine Learning Professional
  13. SAS Certified Big Data Professional
  14. SAS Certified Data Scientist
  15. Tensorflow Developer Certificate
Data Science Career Outlook and Scope in India

Job opportunities (Careers) in Data Science

Data Science Career Outlook and Scope in India

Job opportunities in Data Science

Let us take a sneak peek into some of the Data Science job roles in demand. Data Science jobs for freshers may include the job of a business analyst, data scientist, statistician or data architect.

  1. Big Data Engineer: Big data engineers develop, maintain, test, and evaluate big data solutions within organizations.
  2. Machine Learning Engineer: Machine learning engineers have to design and implement machine learning applications/algorithms to address business challenges.
  3. Data Engineer/Data Architect: Data engineers/architects develop, construct, test, and maintain highly scalable data management systems.
  4. Data Scientist: Data scientists have to understand the challenges of business and offer the best solutions using data analysis and data processing.
  5. Statistician: Statistician interprets the results, along with strategic recommendations or incisive predictions, using data visualization tools or reports.
  6. Data Analysts: Data analysts are involved in data manipulations and data visualization.
  7. Business Analysts: Business analysts use predictive, prescriptive, and descriptive analyses to transform complex data into easily understood actionable insights for the users.

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Megha Kaushik

Megha is working on AWS Cloud, creation of VPC, NAT Gateways and launching instances as per requirement. She is managing Security Groups for the instances.She had worked with a company in Australia.She had developed Highly redundant WordPress Website of PO Maritime Organization over the AWS infrastructure.

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Arun Dabral

Arun is having 5+ years of experience in analytics company. Have closely worked with multiple line of businesses operations, technology etc. Now he is working as a full-time trainer.He had worked at positions like Hadoop Developer, Machine Learning, Data Scientist, Business Intelligence etc.Provide training in 20+ Corporate And Training companies and 3000+ candidates , companies like TATA CMC, Aptron, TeckStack , Madrid , Hcl etc .

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Md Tufail Alam

Experienced Business Analyst, Project Management with a demonstrated history of working in the information technology and services industry. Skilled in Management, Test Planning, Healthcare Management, Visual Basic for Applications (VBA), and QC Tools,Software Testing,Leading the complex project etc. Strong research professional with a Master of Technology - MTech focused in Computer Science Engineering with Big Data Analysis from Glocal University - Saharanpur Uttar Pradesh.

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Navin Kumar Rana

Xavient

Pass Out Year - 2019

Package - 5.35 LPA

Designation - Quality Analyst

Ankur Tyagi

Ginger Webs Pvt. Ltd.

Pass Out Year - 2018

Package - 5 LPA

Designation - Data Scientist

Mayank

Tycho Technologies Pvt Ltd

Pass Out Year - 2020

Package - 3.05 LPA

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Kamal Yadav

Apollo Munich Health Insurance

Pass Out Year - 2018

Package - 3.65 LPA

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Mindfire solutions pvt. Ltd.

Pass Out Year - 2018

Package - 5.80 LPA

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SRM Technologies

Pass Out Year - 2015

Package - 4 LPA

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Ranolia venture Pvt Ltd

Pass Out Year - 2017

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Maritech Software Chandigarh

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