Data Science
The significance of Data Science unites the area of aptitude. It is from programming, math, measurements to make bits of knowledge and figure out information. When we ponder why Data science is progressively becoming significant, the appropriate response lies in the way that the worth of Data is taking off statues.
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About Data Science
Data science is a highly sought-after space. It clarifies how advanced information is changing organizations. Data science is assisting them with settling on more keen choices. So computerized information is pervasive for individuals who are hoping to function as Data scientists.
Data scientists are in constant demand because it is a world full of data! Data scientists are a growing new generation of professionals who are in great demand today. This term was introduced a few years ago by data contacts at LinkedIn and Facebook companies. This demand arose from the sudden need to find brains that wrestle with data and help make discoveries. Those ultimately enable companies to make data-driven decisions. The dawn of digital transformation. Of those companies that tried to meddle on petabytes of data. The role of a data scientist was to help them seize this opportunity to gain insights from this data set. You will use your computing, statistics, and math skills to analyze, process, interpret and store data. It's not just about analytical skills, but the field of activity of a data scientist combines the best soft skills to uncover trends. Role of the data scientist in today's data-driven startups, data scientists play critical business roles. Typically, the role of a data scientist is to process huge amounts of data. Then analyze it using data-driven methods. Communicate it to IT leadership teams and understand patterns and trends through visualizations. Data scientists also use machine learning and artificial intelligence. They use their programming skills in Java, Python, SQL, big data Hadoop, and data mining. Communication skills to effectively bring your data discovery knowledge to the business.
Advantages of Data Science Course
Why is the Data Science Course significant as an establishment for taking organizations to a higher level?
Information is significant, as is the science in translating it. Zillions of bytes of Data are being created. The job of the Data Scientist is and will be of vital significance for associations across many verticals.
Data without science isn't anything
Data should be perused and examined. It calls out for the prerequisite of having a nature of the information. By seeing how to understand it and make information-driven revelations the Best Data Science Course in Kolkata helps to upgrade your skills.
Data will assist with making better client encounters
For merchandise and items, Data science will use the force of Machine Learning. It is to empower organizations to make and create items; that client will love. For instance, for an eCommerce organization, an incredible suggestion framework can assist them. For finding their client personas by taking a gander at their buy history.
Data will be utilized across verticals
Data science isn't restricted to just buying products or tech or medical care. It will be popular to enhance business measures utilizing Data science from banking and transport to assembling. So any individual who needs to be an information researcher will have a different universe of chances open. What's to come is Data.
Why Choose SevenMentor?
Learning Outcomes of Data Science Course in Kolkata.
This information-driven climate certificate in Data Science sets you up. It is for the flooding interest of Big Data abilities and innovation in every one of the enterprises. There is a gigantic professional prospect accessible in the field of Data Science. The Machine Learning course in Kolkata is exceptionally intended to suit the two information experts and fledglings. Candidates who need to make a vocation in this quickly developing trend can join us. This training will furnish the students with coherent and pertinent programming capacities to construct data set models. They will want to make basic AI calculations like K-Means Clustering, Decision Trees. In 90 days, students will likewise investigate the key strategies like Statistical Analysis, Regression Analysis, Data Mining, Machine Learning. Comprehend the critical ideas of Neural Networks and study Deep Learning Black Box procedures like SVM.
Progressed Learning
We perfectly created modules for your inside and out learning and comprehension in the Machine Learning Classes in Kolkata.
Outfit yourself with in-pattern and impending business sector prepared instruments and strategies.
Go to Data Science classes at your solace through the classroom and web-based instructional meetings.
Effectively conveyed long stretches of value instructing to support your schooling.
Go to tests and assessments through our got checking stage.
Gain limitless admittance to each recorded meeting during the affordable Data Science Training with job placement.
Progressed Understanding
The SevenMentor customize meetings to help your learning with live classes and video instructional exercises.
Look for help from our specialists who are promptly accessible to help you whenever.
Upgrade your insight through studios, workshops, and online Data Science and Machine Learning courses held routinely.
We assist with expanding your abilities to allow you to extend your aptitude in your picked field.
Excel with our novel projects which open an expanse of chances.
Grow your points of view by going to our visitor personnel teachers who are highly experienced.
Progressed Results
Get computerized grounds preparing getting installed with specialists at SevenMentor.
Profit of confirmed endorsements just get-togethers consummation of your specific course.
Receive the rewards from our position cell with 100% Job Guarantee.
Join SevenMentor Institute and meet similar tutors for your direction.
Upskill your insight using customary tasks and evaluations.
On consummation, you will act naturally dependent, to work in an association or be a specialist.
Profession Support
Our very much associated position group is committed to giving you the best chances from the top associations.
Advantages of Machine Learning in Big Data Research
Unlimited Data Analysis in limited time
Machine Learning can deal with a limitless measure of Data. It can check them and give a legitimate examination to the equal; this factor empowers organizations to target clients with applicable messages. It depends on client exercises and cooperation. Machine Learning can pinpoint related factors whenever it has fashioned a model from many wellsprings of information. This aids in staying away from joining entanglements. It clears a path for more exact information results.
Real-time information expectation for investigators to explore
Huge Data experts are seeing Machine Learning as the best hotspot for exact Data forecasts. It devours a humongous measure of Data, completely goes over every one of the connected patterns. And it exercises, lastly furnishes compact and exact conjectures with constant information. This correct nature of information engages examiners to delve further into their exploration. It can comprehend information better and use it for the advancement of various ventures.
Online Classes
Industry verticals are utilizing the force of information. Data science is significant for organizations since it has been divulging arrangements and keen choices across many industry verticals, hence Online Data Science Course in Kolkata is necessary. The epic method of utilizing insightful machines to stir tremendous measures of Data to comprehend. And investigating the conduct and examples is essentially incredible. It is the reason Data science has been getting all the spotlight.SevenMentor Institute provides the best Online Data Science Training in Kolkata.For instance, Big Data assists them with understanding their client personas. Data helps to work on their encounters by gaining from verifiable buy information. For instance, the medication vertical could use Data science to incorporate the patient's set of experiences and assist with figuring out their prosperity status, and recommend right cures now and again.
Course Eligibility
- Freshers
- BE/ Bsc Candidate
- Any Engineers
- Any Graduate
- Any Post-Graduate
- Working Professionals
Syllabus of Data Science
- 1. Installation Of Vmware
- 2. MYSQL Database
- 3. Core Java
- 1.1 Types of Variable
- 1.2 Types of Datatype
- 1.3 Types of Modifiers
- 1.4 Types of constructors
- 1.5 Introduction to OOPS concept
- 1.6 Types of OOPS concept
- 4. Advance Java
- 1.1 Introduction to Java Server Pages
- 1.2 Introduction to Servlet
- 1.3 Introduction to Java Database Connectivity
- 1.4 How to create Login Page
- 1.5 How to create Register Page
- 5. Bigdata
- 1.1 Introduction to Big Data
- 1.2 Characteristics of Big Data
- 1.3 Big data examples
- 6. Hadoop
- i) BigData Inroduction,Hadoop Introduction and HDFS Introduction
- 1.1. Hadoop Architecture
- 1.2. Installing Ubuntu with Java on VM Workstation 11
- 1.3. Hadoop Versioning and Configuration
- 1.4. Single Node Hadoop installation on Ubuntu
- 1.5. Multi Node Hadoop installation on Ubuntu
- 1.6. Hadoop commands
- Cluster architecture and block placement
- 1.8. Modes in Hadoop
- Local Mode
- Pseudo Distributed Mode
- Fully Distributed Mode
- 1.9. Hadoop components
- Master components(Name Node, Secondary Name Node, Job Tracker)
- Slave components(Job tracker, Task tracker)
- 1.10. Task Instance
- 1.11. Hadoop HDFS Commands
- 1.12. HDFS Access
- Java Approach
- ii) MapReduce Introduction
- 1.1 Understanding Map Reduce Framework
- 1.2 What is MapReduceBase?
- 1.3 Mapper Class and its Methods
- 1.4 What is Partitioner and types
- 1.5 Relationship between Input Splits and HDFS Blocks
- 1.6 MapReduce: Combiner & Partitioner
- 1.7 Hadoop specific Data types
- 1.8 Working on Unstructured Data Analytics
- 1.9 Types of Mappers and Reducers
- 1.10 WordCount Example
- 1.11 Developing Map-Reduce Program using Eclipse
- 1.12 Analysing dataset using Map-Reduce
- 11.13 Running Map-Reduce in Local Mode.
- 1.14 MapReduce Internals -1 (In Detail) :
- How MapReduce Works
- Anatomy of MapReduce Job (MR-1)
- Submission & Initialization of MapReduce Job (What Happen ?)
- Assigning & Execution of Tasks
- Monitoring & Progress of MapReduce Job
- Completion of Job
- Handling of MapReduce Job
- Task Failure
- TaskTracker Failure
- JobTracker Failure
- 1.15 Advanced Topic for MapReduce (Performance and Optimization) :
- Job Sceduling
- In Depth Shuffle and Sorting
- 1.16 Speculative Execution
- 1.17 Output Committers
- 1.18 JVM Reuse in MR1
- 1.19 Configuration and Performance Tuning
- 1.20 Advanced MapReduce Algorithm :
- 1.21 File Based Data Structure
- Sequence File
- MapFile
- 1.22 Default Sorting In MapReduce
- Data Filtering (Map-only jobs)
- Partial Sorting
- 1.23 Data Lookup Stratgies
- In MapFiles
- 1.24 Sorting Algorithm
- Total Sort (Globally Sorted Data)
- InputSampler
- Secondary Sort
- 1.25 MapReduce DataTypes and Formats :
- 1.26 Serialization In Hadoop
- 1.27 Hadoop Writable and Comparable
- 1.28 Hadoop RawComparator and Custom Writable
- 1.29 MapReduce Types and Formats
- 1.30 Understand Difference Between Block and InputSplit
- 1.31 Role of RecordReader
- 1.32 FileInputFormat
- 1.33 ComineFileInputFormat and Processing whole file Single Mapper
- 1.34 Each input File as a record
- 1.35 Text/KeyValue/NLine InputFormat
- 1.36 BinaryInput processing
- 1.37 MultipleInputs Format
- 1.38 DatabaseInput and Output
- 1.39 Text/Biinary/Multiple/Lazy OutputFormat MapReduce Types
- iii)TOOLS:
- 1.1 Apache Sqoop
- Sqoop Tutorial
- How does Sqoop Work
- Sqoop JDBCDriver and Connectors
- Sqoop Importing Data
- Various Options to Import Data
- Table Import
- Binary Data Import
- SpeedUp the Import
- Filtering Import
- Full DataBase Import Introduction to Sqoope
- 1.2 Apache Hive
- 1.2 Apache Hive
- What is Hive ?
- Architecture of Hive
- Hive Services
- Hive Clients
- How Hive Differs from Traditional RDBMS
- Introduction to HiveQL
- Data Types and File Formats in Hive
- File Encoding
- Common problems while working with Hive
- Introduction to HiveQL
- Managed and External Tables
- Understand Storage Formats
- Querying Data
- 1.3 Apache Pig :
- What is Pig ?
- Introduction to Pig Data Flow Engine
- Pig and MapReduce in Detail
- When should Pig Used ?
- Pig and Hadoop Cluster
- Pig Interpreter and MapReduce
- Pig Relations and Data Types
- PigLatin Example in Detail
- Debugging and Generating Example in Apache Pig
- 1.4 HBase:
- Fundamentals of HBase
- Usage Scenerio of HBase
- Use of HBase in Search Engine
- HBase DataModel
- Table and Row
- Column Family and Column Qualifier
- Cell and its Versioning
- Regions and Region Server
- HBase Designing Tables
- HBase Data Coordinates
- Versions and HBase Operation
- Get/Scan
- Put
- Delete
- 1.5 Apache Flume:
- Flume Architecture
- Installation of Flume
- Apache Flume Dataflow
- Apache Flume Environment
- Fetching Twitter Data
- 1.6 Apache Kafka:
- Introduction to Kafka
- Cluster Architecture
- Installation of kafka
- Work Flow
- Basic Operations
- Real time application(Twitter)
- 4)HADOOP ADMIN:
- Introduction to Big Data and Hadoop
- Types Of Data
- Characteristics Of Big Data
- Hadoop And Traditional Rdbms
- Hadoop Core Services
- Hadoop single node cluster(HADOOP-1.2.1)
- Tools installation for hadoop1x.
- Sqoop,Hive,Pig,Hbase,Zookeeper.
- Analyze the cluster using
- a)NameNode UI
- b)JobTracker UI
- SettingUp Replication Factor
- Hadoop Distributed File System:
- Introduction to Hadoop Distributed File System
- Goals of HDFS
- HDFS Architecture
- Design of HDFS
- Hadoop Storage Mechanism
- Measures of Capacity Execution
- HDFS Commands
- The MapReduce Framework:
- Understanding MapReduce
- The Map and Reduce Phase
- WordCount in MapReduce
- Running MapReduce Job
- WordCount in MapReduce
- Running MapReduce Job
- Hadoop single node Cluster
- Hadoop single node Cluster Setup :
- Hadoop single node cluster(HADOOP-2.7.3)
- Tools installation for hadoop2x
- Sqoop,Hive,Pig,Hbase,Zookeeper
- Hadoop single node Cluster Setup :
- Hadoop single node cluster(HADOOP-2.7.3)
- Tools installation for hadoop2x
- Sqoop,Hive,Pig,Hbase,Zookeeper.
- Yarn:
- Introduction to YARN
- Need for YARN
- YARN Architecture
- YARN Installation and Configuration
- Hadoop Multinode cluster setup:
- hadoop multinode cluster
- Checking HDFS Status
- Breaking the cluster
- Copying Data Between Clusters
- Adding and Removing Cluster Node
- Name Node Metadata Backup
- Cluster Upgrading
- Hadoop ecosystem:
- Sqoop
- Hive
- Pig
- HBase
- zookeeper
- >7. MONGODB
- 8. SCALA
- 1.1 Introduction to scala
- 1.2 Programming writing Modes i.e. Interactive Mode,Script Mode
- 1.3 Types of Variable
- 1.4 Types of Datatype
- 1.5 Function Declaration
- 1.6 OOPS concepts
- 9. APACHE SPARK
- 1.1 Introduction to Spark
- 1.2 Spark Installation
- 1.3 Spark Architecture
- 1.4 Spark SQL
- Dataframes: RDDs + Tables
- Dataframes and Spark SQL
- 1.5 Spark Streaming
- Introduction to streaming
- Implement stream processing in Spark using Dstreams
- Stateful transformations using sliding windows
- 1.6 Introduction to Machine Learning
- 1.7 Introduction to Graphx
- Hadoop ecosystem:
- Sqoop
- Hive
- Pig
- HBase
- zookeeper
- 10. TABLEAU
- 11. DATAIKU
- 12. Product Based Web Application Demo based on java(EcommerceApplication)
- 13. Data deduplication Project
- 14. PYTHON
- 1.Introduction to Python
- What is Python and history of Python?
- Unique features of Python
- Python-2 and Python-3 differences
- Install Python and Environment Setup
- First Python Program
- Python Identifiers, Keywords and Indentation
- Comments and document interlude in Python
- Command line arguments
- Getting User Input
- Python Data Types
- What are variables?
- Python Core objects and Functions
- Number and Maths
- Week 1 Assignments
- 2.List, Ranges & Tuples in Python
- Introduction
- Lists in Python
- More About Lists
- Understanding Iterators
- Generators , Comprehensions and Lambda Expressions
- Introduction
- Generators and Yield
- Next and Ranges
- Understanding and using Ranges
- More About Ranges
- Ordered Sets with tuples
- 3.Python Dictionaries and Sets
- Introduction to the section
- Python Dictionaries
- More on Dictionaries
- Sets
- Python Sets Examples
- 4. Python built in function
- Python user defined functions
- Python packages functions
- Defining and calling Function
- The anonymous Functions
- Loops and statement in Python
- Python Modules & Packages
- 5.Python Object Oriented
- Overview of OOP
- Creating Classes and Objects
- Accessing attributes
- Built-In Class Attributes
- Destroying Objects
- 6. Python Object Oriented
- Overview of OOP
- Creating Classes and Objects
- Accessing attributes
- Built-In Class Attributes
- Destroying Objects
- 7. Python Exceptions Handling
- What is Exception?
- Handling an exception
- try….except…else
- try-finally clause
- Argument of an Exception
- Python Standard Exceptions
- Raising an exceptions
- User-Defined Exceptions
- 8. Python Regular Expressions
- What are regular expressions?
- The match Function
- The search Function
- Matching vs searching
- Search and Replace
- Extended Regular Expressions
- Wildcard
- 9. Python Multithreaded Programming
- What is multithreading?
- Starting a New Thread
- The Threading Module
- Synchronizing Threads
- Multithreaded Priority Queue
- Python Spreadsheet Interfaces
- Python XML interfaces
- 10. Using Databases in Python
- Python MySQL Database Access
- Install the MySQLdb and other Packages
- Create Database Connection
- CREATE, INSERT, READ, UPDATE and DELETE Operation
- DML and DDL Oepration with Databases
- Performing Transactions
- Handling Database Errors
- Web Scraping in Python
- 11.Python For Data Analysis –
- Numpy:
- Introduction to numpy
- Creating arrays
- Using arrays and Scalars
- Indexing Arrays
- Array Transposition
- Universal Array Function
- Array Processing
- Arrary Input and Output
- 12. Pandas:
- What is pandas?
- Where it is used?
- Series in pandas
- Index objects
- Reindex
- Drop Entry
- Selecting Entries
- Data Alignment
- Rank and Sort
- Summary Statics
- Missing Data
- Index Heirarchy
- 13. Matplotlib: Python For Data Visualization
- 14. Welcome to the Data Visualiztion Section
- 15. Introduction to Matplotlib
- 16. Django Web Framework in Python
- 17. Introduction to Django and Full Stack Web Development
- 15. R Programming
- 1.1 Introduction to R
- 1.2 Installation of R
- 1.3 Types of Datatype
- 1.4 Types of Variables
- 1.5 Types of Operators
- 1.6 Types of Loops
- 1.7 Function Declaration
- 1.8 R Data Interface
- 1.9 R Charts and Graphs
- 1.10 R statistics
- 16) Advance Tool for Analysis
- 1.1 git
- 1.2 nmpy
- 1.3 scipy
- 1.4 github
- 1.5 matplotlib
- 1.6 Pandas
- 1.7 PyQT
- 1.8Theano
- 1.9 Tkinter
- 1.10 Scikit-learn
- 1.11 NPL
- 17. Algorithm
- 1.naive bayes
- 2.Linear Regression
- 3.K-nn
- 4.C-nn
Trainer Profile of Data Science
Our Trainers explains concepts in very basic and easy to understand language, so the students can learn in a very effective way. We provide students, complete freedom to explore the subject. We teach you concepts based on real-time examples. Our trainers help the candidates in completing their projects and even prepare them for interview questions and answers. Candidates can learn in our one to one coaching sessions and are free to ask any questions at any time.
- Certified Professionals with more than 8+ Years of Experience
- Trained more than 2000+ students in a year
- Strong Theoretical & Practical Knowledge in their domains
- Expert level Subject Knowledge and fully up-to-date on real-world industry applications
Data Science Exams & Certification
SevenMentor Certification is Accredited by all major Global Companies around the world. We provide after completion of the theoretical and practical sessions to fresher’s as well as corporate trainees.
Our certification at SevenMentor is accredited worldwide. It increases the value of your resume and you can attain leading job posts with the help of this certification in leading MNC’s of the world. The certification is only provided after successful completion of our training and practical based projects.
Proficiency After Training
- Learn all new aspects of Data Science.
- You will have a good understanding of Data Science Algorithms.
- You will be able to work on real time projects.
- You will be able to work on file formats on different data.
Key Features
Skill Level
Beginner, Intermediate, Advance
We are providing Training to the needs from Beginners level to Experts level.
Course Duration
90 Hours
Course will be 90 hrs to 110 hrs duration with real-time projects and covers both teaching and practical sessions.
Total Learners
2000+ Learners
We have already finished 100+ Batches with 100% course completion record.
Frequently Asked Questions
Batch Schedule
DATE | COURSE | TRAINING TYPE | BATCH | CITY | REGISTER |
---|---|---|---|---|---|
14/10/2024 |
Data Science |
Online | Regular Batch (Mon-Sat) | Kolkata | Book Now |
15/10/2024 |
Data Science |
Online | Regular Batch (Mon-Sat) | Kolkata | Book Now |
19/10/2024 |
Data Science |
Online | Weekend Batch (Sat-Sun) | Kolkata | Book Now |
19/10/2024 |
Data Science |
Online | Weekend Batch (Sat-Sun) | Kolkata | Book Now |
Students Reviews
Anybody hoping to begin with Data science without any preparation can undoubtedly admire SevenMentor Institute. They give an extraordinary learning experience. I'm a novice in DS, yet the educators of this Academy improved on the course substance.
- Monika Naidu
My involvement with SevenMentor was uncommon. I had opted for enough information about DS in a month. The coaches at SevenMentor are amazingly useful and show the whole course content top to bottom.
- Sakshi Tambe
From the beginning, I was reluctant to join as I didn't know I would have the option to adapt to the climate or not. Be that as it may, soon, it began to feel more like a family concentrating here.
- Suyash Tatke
Course video & Images
Corporate Training
Corporate training is the process of improving the job skills and knowledge of employees. It is through an organized method of instruction. Corporate Data Science courses in Kolkata always take the shape of online or offline instructional content, online or face-to-face lectures, and mentorship. SevenMentor's Corporate Data Science Training in Kolkata includes actual or virtual group interaction. Our Corporate training benefits organizations and employees; it ensures the swift acquisition of the capabilities needed to do corporate goals and success. Corporate training also improves teamwork, employee satisfaction, and retention. Corporate training also improves each employee's skill set, job value, and career development. By adding high-value skills and certifications to their staff, corporate training has even enabled some organizations to get quite 200% more revenue from each upskilled employee. Corporate Machine Learning training in Kolkata also improves employer reputation and, therefore, the ability to draw in new talent.
Our Placement Process
Eligibility Criteria
Placements Training
Interview Q & A
Resume Preparation
Aptitude Test
Mock Interviews
Scheduling Interviews
Job Placement
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