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Data science Training Institutes in Noida, Delhi- Fee Is 14000 Rs (Self Practice Video 1500 Rs only)

Best Data science Training Institute In Noida
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Webtrackker Training Centre


Best Data science Training Institute In Noida & Data science Training Institute In Noida

Data science Training Institute in Noida- with 100% placement support - Data science, also known as data-driven science, is an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, structured or unstructured, similar to data mining. Data science is a "concept to unify statistics, data analysis, machine learning and their related methods" in order to "understand and analyze actual phenomena" with data.

WEBTRACKKER is the pioneer of education providing the best data science training in Noida as per the current industry requirement that enables candidates to land on their dream jobs in companies worldwide. WEBTRACKKER Provides best data science training course in Noida. WEBTRACKKER is a renowned training company providing the best training service and also being the best data science training institute in Noida rendering practical knowledge through training on projects and dedicated placement assistance for all. The course curriculum for data science training course is designed to provide in-depth knowledge that covers all the modules for the training ranging from basic to advanced level. At WEBTRACKKER data science training in Noida is supervised and managed by industrial experts having more than 10 years of experience in handling Data Science projects. WEBTRACKKER training comprises of both classroom as well as practical sessions to deliver an ideal environment for students that will enable them to handle difficult and complex situation when they would step into the reality of IT sector.

WEBTRACKKER is the best data science training center in Noida with high tech infrastructure aspirants learn the skills for data science that comprises of Overview of data science and, data science on real time projects along with data science placement training. data science certification training in Noida has been planned out under the guidance of the leaders of MNC’s to provide the best extensive knowledge of data science with the advanced data science course content and syllabus. The course structure is constructed by the technology experts that will help in facilitating professionalism in students and also further down the line , the data science training program will help them achieve their goal and to get placed in MNC and Big corporations.

WEBTRACKKER is an excellent data science training center in Noida with superior integrated infrastructure and newly designed labs for students to practice and pursue training for multiple courses at Noida. WEBTRACKKER institute in Noida train thousands of students around the globe every year for the data science training at an affordable price which is customized as per each candidate’s requirement of modules and content.

Data science training course involves "Hands-on experience", we believe in practice what you preach and therefore each candidate is encouraged to practically conduct each topic that is discussed for better understanding of real-world scenario Data Science. This practice of comprehensive training allows candidate to gain all the concepts and skills effectively and to later efficiently apply on their field of work.

WEBTRACKKER is one of the best data science training institutes in Noida with 100% placement assistance. WEBTRACKKER has well structure modules and training program designed for both students and working professionals separately. At WEBTRACKKER data science training is conducted during all 5 days, and special weekend classes. Can also be arranged and scheduled. We also provide fast track training programs for students and professionals looking to upgrade themselves instantly.

Top 20 Reasons to Choose WEBTRACKKER for Data science Training in Noida

  • Data science training in Noida is designed according to current IT market.
  • Offer the best Data science training and placement in Noida with well defined training modules and course sessions.
  • Facilitate regular, weekend and customized Data science training in Noida..
  • One of the biggest team of Certified Expert Trainers with 5 to 15 years of Real Industry Experience.
  • Mentors of Data science training in Noida helps in major project training, minor project training, live project preparation, interview preparation and job placement support.
  • Smart Labs with Real Latest Equipments.
  • 24x7 Lab Facilities. Students are free to access the labs for unlimited number of hours as per their own preferred timings.
  • Smart classrooms fully equipped with projectors, live racks, Wi-Fi connectivity, Digital Pads.
  • Silent and Discussion Zone areas in Labs to enhance Self Study and Group Discussions.
  • Free of Cost Personality Development sessions including Spoken English, Group Discussions, Mock Interviews, Presentation skills.
  • Free of Cost Seminars for Personality Development & Personal Presentation.
  • Varity of Study Material: Books, PDF’s, Video Lectures, Sample questions, Interview Questions (Technical and HR), and Projects.
  • Hostel Facilities available at Rs 5,500/month for Data science Training in Noida students.
  • Free Study Material, PDFs, Video Trainings, Sample Questions, Exam Preparation, Interview Questions, Lab Guides.
  • Globally Recognized Course Completion Certificate.
  • Extra Time Slots (E.T.S.) for Practical's(Unlimited), Absolutely Free.
  • The ability to retake the class at no-charge as often as desired.
  • One-on-One attention by instructors.
  • Helps students to take knowledge of complex technical concepts.
  • Payment options: Cheque, Cash, Credit Card, Debit card, Net Banking.

WEBTRACKKER Trainer's Profile for Data science Training in Noida

WEBTRACKKER'S Data science Trainers are:

  • Are truly expert and fully up-to-date in the subjects they teach because they continue to spend time working on real-world industry applications.
  • Have received awards and recognition from our partners and various recognized IT Organizations.
  • Are working professionals working in multinational companies such as HCL Technologies, Birlasoft, TCS, IBM, Sapient, Agilent Technologies etc.
  • Are certified Professionals with 7+ years of experience.
  • Are Well connected with Hiring HRs in multinational companies.

Placement Assistance after Data science Training in Noida

WEBTRACKKER'S Placement Assistance

  • WEBTRACKKER is the leader in offering placement to the students, as it has a dedicated placement wing which caters to the needs of the students during placements.
  • WEBTRACKKER helps the students in the development of their RESUME as per current industry standards.
  • WEBTRACKKER conducts Personality Development sessions including Spoken English, Group Discussions, Mock Interviews, Presentation skills to prepare students to face challenging interview situation with ease.
  • WEBTRACKKER has prepared its students to get placed in top IT FIRMS like HCL, TCS, Infosys, Wipro, Accenture and many more.

webtrackker Course duration for Data science Training in Noida

  • Fast Track Training Program (4+ hours Saturday And Sunday)
  • Demo Classes (Free Demo Class Time 1 pm Saturday And Sunday)
  • Weekend Training Classes (Saturday, Sunday & Holidays)
Webtrackker Projects

Webtrackker is IT based company in many countries. Webtrackker will provide you a real time projects based traning on big data

Modules About Modules
Introduction to Data Science Introduction to Big Data, Roles played by a Data Scientist, Analyzing Big Data using Hadoop and R, Methodologies used for analysis, The Architecture and Methodologies used to solve the Big Data problems
Basic Data Manipulation using R Understanding vectors in R, Reading Data, Combining Data, Sub setting data Sorting data and some basic data generation functions
Machine Learning Techniques Using R Part-1 Machine Learning Overview, ML Common Use Cases, Understanding Supervised and Unsupervised Learning Techniques, Clustering, Similarity Metrics, Distance Measure Types: Euclidean, Cosine Measures, Creating predictive models
Machine Learning Techniques Using R Part-2 Understanding K-Means Clustering, Understanding TF-IDF and Cosine Similarity and their application to Vector Space Model, Implementing Association rule mining in R
Machine Learning Techniques Using R Part-3 Understanding Process flow of Supervised Learning Techniques, Decision Tree Classifier, How to build Decision trees, Random Forest Classifier, What is Random Forests, Features of Random Forest, Out of Box Error Estimate and Variable Importance, Naive Bayes Classifier
Introduction to Hadoop Architecture Understanding K-Means Clustering, Understanding TF-IDF and Cosine Similarity and their application to Vector Space Model, Implementing Association rule mining in R
Integrating R with Hadoop Integrating R with Hadoop using RHadoop and RMR package, Exploring RHIPE (R Hadoop Integrated Programming Environment), Writing MapReduce Jobs in R and executing them on Hadoop
Mahout Introduction and Algorithm Implementation Implementing Machine Learning Algorithms on larger Data Sets with Apache Mahout
Additional Mahout Algorithms and Parallel Processing using R Implementation of different Mahout algorithms, Random Forest Classifier with parallel processing Library in R


Cloudera Admin Certification Program





Cloudera Certified Administrator for Data science100% Clearance Guaranty

(CCAH) Exam Code: CCA-410

Data science_Certification

Cloudera Certified Administrator for Apache Data science Exam :

  • Number of Questions: 60
  • Item Types: multiple-choice & short-answer questions
  • Exam time: 90 Mins.
  • Passing score: 70%
  • Price: $295 USD

Syllabus Cloudera Administrator Certification Exam

HDFS 38%
  • Describe the function of all Data science Daemons
  • Describe the normal operation of an Apache Data science cluster, both in data storage and in data processing.
  • Identify current features of computing systems that motivate a system like Apache Data science.
  • Classify major goals of HDFS Design
  • Given a scenario, identify appropriate use case for HDFS Federation
  • Identify components and daemon of an HDFS HA-Quorum cluster
  • Analyze the role of HDFS security (Kerberos)
  • Determine the best data serialization choice for a given scenario
  • Describe file read and write paths
  • Identify the commands to manipulate files in the Data science File System Shell.
MapReduce 10%
  • Understand how to deploy MapReduce MapReduce v1 (MRv1)
  • Understand how to deploy MapReduce v2 (MRv2 / YARN)
  • Understand basic design strategy for MapReduce v2 (MRv2)
Data science Cluster Planning 12%
  • Principal points to consider in choosing the hardware and operating systems to host an Apache Data science cluster.
  • Analyze the choices in selecting an OS
  • Understand kernel tuning and disk swapping
  • Given a scenario and workload pattern, identify a hardware configuration appropriate to the scenario
  • Cluster sizing: given a scenario and frequency of execution, identify the specifics for the workload, including CPU, memory, storage, disk I/O
  • Disk Sizing and Configuration, including JBOD versus RAID, SANs, virtualization, and disk sizing requirements in a cluster
  • Network Topologies: understand network usage in Data science (for both HDFS and MapReduce) and propose or identify key network design components for a given scenario
Data science Cluster Installation and Administration 17%
  • Given a scenario, identify how the cluster will handle disk and machine failures.
  • Analyze a logging configuration and logging configuration file format.
  • Understand the basics of Data science metrics and cluster health monitoring.
  • Identify the function and purpose of available tools for cluster monitoring.
  • Identify the function and purpose of available tools for managing the Apache Data science file system.
Resource Management 06%
  • Understand the overall design goals of each of Data science schedulers.
  • Given a scenario, determine how the FIFO Scheduler allocates cluster resources.
  • Given a scenario, determine how the Fair Scheduler allocates cluster resources.
  • Given a scenario, determine how the Capacity Scheduler allocates cluster resources
Monitoring and Logging 12%
  • Understand the functions and features of Data science’s metric collection abilities
  • Analyze the NameNode and JobTracker Web UIs
  • Interpret a log4j configuration
  • Understand how to monitor the Data science Daemons
  • Identify and monitor CPU usage on master nodes
  • Describe how to monitor swap and memory allocation on all nodes
  • Identify how to view and manage Data science’s log files
  • Interpret a log file
The Data science Ecosystem 05%
  • Understand Ecosystem projects and what you need to do to deploy them on a cluster.


Cloudera Certified Developer for Data science100% Clearance Guaranty

(CCDH) Exam Code: CCD-410

Data science_Certification

Cloudera Certified Developer for Apache Data science Exam:

  • Number of Questions: 50 – 55 live questions
  • Item Types: multiple-choice & short-answer questions
  • Exam time: 90 Mins.
  • Passing score: 70%
  • Price: $295 USD

Syllabus Cloudera Develpoer Certification Exam

Infrastructure Objectives 25%
  • Recognize and identify Apache Data science daemons and how they function both in data storage and processing.
  • Understand how Apache Data science exploits data locality.
  • Identify the role and use of both MapReduce v1 (MRv1) and MapReduce v2 (MRv2 / YARN) daemons.
  • Analyze the benefits and challenges of the HDFS architecture.
  • Analyze how HDFS implements file sizes, block sizes, and block abstraction.
  • Understand default replication values and storage requirements for replication.
  • Determine how HDFS stores, reads, and writes files.
  • Identify the role of Apache Data science Classes, Interfaces, and Methods.
  • Understand how Data science Streaming might apply to a job workflow
Data Management Objectives 30%
  • Import a database table into Hive using Sqoop.
  • Create a table using Hive (during Sqoop import).Successfully use key and value types to write functional MapReduce jobs.
  • Given a MapReduce job, determine the lifecycle of a Mapper and the lifecycle of a Reducer.
  • Analyze and determine the relationship of input keys to output keys in terms of both type and number, the sorting of keys, and the sorting of values.
  • Given sample input data, identify the number, type, and value of emitted keys and values from the Mappers as well as the emitted data from each Reducer and the number and contents of the output file(s).
  • Understand implementation and limitations and strategies for joining datasets in MapReduce.
  • Understand how partitioners and combiners function, and recognize appropriate use cases for each.
  • Recognize the processes and role of the the sort and shuffle process.
  • Understand common key and value types in the MapReduce framework and the interfaces they implement.
  • Use key and value types to write functional MapReduce jobs.
Job Mechanics Objectives 25%
  • Construct proper job configuration parameters and the commands used in job submission.
  • Analyze a MapReduce job and determine how input and output data paths are handled.
  • Given a sample job, analyze and determine the correct InputFormat and OutputFormat to select based on job requirements.
  • Analyze the order of operations in a MapReduce job.
  • Understand the role of the RecordReader, and of sequence files and compression.
  • Use the distributed cache to distribute data to MapReduce job tasks.
    Build and orchestrate a workflow with Oozie.
Querying Objectives 20%
  • Write a MapReduce job to implement a HiveQL statement.
  • Write a MapReduce job to query data stored in HDFS.

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