Data Science
In today’s fast-paced and tech-driven world, data is crucial. Data improves decision-making, market trends, and predicts consumer behavior. So, there is a considerable demand for Data Scientists. SevenMentor, a recognized institute, has formed a course, where you will learn about Data Science and Machine learning. Data Science and Machine learning courses in Delhi will help you make a successful career.
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- Regular: 2 Batches
- Weekends: 2 Batches
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About Data Science
Data Science combines artificial intelligence (AI), data analysis, multiple fields, including statistics, scientific methods. Then it extracts value from data. Data Science includes formulating data for analysis, cleansing, aggregating, and managing data to perform improved data analysis. Those who exercise data science are called Data Scientists. They have the necessary skills to assess data collected from the web, smartphones, and other sources to conclude actionable knowledge.
What is Machine Learning?
Machine Learning is a type of artificial intelligence. It permits software applications to become more careful at foreseeing outcomes without being explicitly programmed to do so. Machine Learning algorithms practice historical data as input to anticipate new output values. Machine learning is significant because it gives opinions on customer behavior and business patterns. It also helps in the development of new products. SevenMentor delivers valuable Machine Learning Classes In Delhi.
Why should you learn Data Science?
Data Science for better marketing- Companies are using data to assess their marketing policies. It helps them to create better advertisements. They study and analyze customer feedback. So it supports them to get better marketing insights.
Data Science for Customer Acquisition- Data Scientists assist the company to reach customers by assessing their needs. It permits companies to make products best suited for the needs of their potential customers. Data is essential to know their clients.
Data Science for innovation- Companies create better innovations with a quantity of data. The Data Scientists assist in product innovation by creating and analyzing insights within the conventional designs. They assess customer reviews and assist companies in making products as per the feedback and reviews.
Data Science enhancing lives- Customer data is significant in making their lives better. Healthcare industries use data accessible to them to support their customers in their everyday life. In these types of industries, Data Scientists have the purpose of assessing personal data, health history and invent products. It helps them to tackle problems faced by customers.
Due to all these reasons, SevenMentor has designed Data Science Classes In Delhi. So by learning Data Science, you can achieve success in this field.
Why choose SevenMentor to learn Data Science?
SevenMentor is the best training institute in Delhi. It provides training on Data Science and Machine Learning. Our institute helps students to gain knowledge and professional skills as per the current standards of various industries.
SevenMentor provides data science training with placement. We have made our data science course fees reasonable for everyone. So a person from any walk of life can join this course.
- At our Data Science & Machine Learning Training In Delhi, we have corporate professionals with 10+ years of experience. They train you by applying a unique blend of academic learning with practical sessions. So you can get industry knowledge and make you a skilled professional.
- The course syllabus of Data Science & Machine Learning Classes In Delhi includes Introduction to Data Science, Machine learning overview, Basic Data Manipulation using R, roles played by a Data Scientist, Understanding K means clustering. You will get Understanding the process flow of the supervised learning technique, subscripting, Algorithm Implementation.
- At our Data Science & Machine learning Classes In Delhi, we prefer the process of teaching that is “Learning by Doing” It encourages students to enhance their working skills by exercising hands-on experience on live Data Science projects. With these classes, you can become a valuable asset to the company and the preferred choice of potential employers.
- The course content of Data Science & Machine Learning Training In Delhi is as per recent advancements and the needs of the industry. Whether you are a beginner or a professional, it supports you to achieve your respective career goals.
- At our best Data Science & Machine Learning Classes In Delhi, we have morning and evening batches. Weekends and weekdays batches are also available. SevenMentor also delivers fast-track Data Science training classes in Delhi to those running out of time.
- At our Data Science & Machine Learning Training In Delhi, you get valuable knowledge with highly advanced and well-equipped infrastructure. We offer advanced lab facilities with 24*7 access and the latest equipment. So a student can practice anytime. We have smart classrooms with wi-fi connections, live racks, projectors, and digital pads.
- At our Data Science & Machine Learning Classes In Delhi, we offer a variety of study materials. You can learn through books, video lectures, PDFs, Sample questions, interview questions (HR and Technical), exam preparation, and lab guides.
- Mentors of Data Science & Machine Learning Training In Delhi help live project preparation, interview preparation, resume building according to current industry standards, and placement assistance.
- At our Best Data Science & Machine Learning Classes In Delhi, we conduct Personality Development sessions involving group discussions, spoken English, presentation skills, and Mock interviews to prepare students. So they can face interviews with ease.
SevenMentor delivers Data Science & Machine Learning Certification Course. After finishing the training, you will get our globally recognized certificate.
Online Classes
Online Training is flexible. It allows you to fit your training around your work schedules and lifestyle. SevenMentor delivers Online Data Science Course In Delhi with placement. You only need a PC or Laptop with a proper internet connection. With our efficient online training, you will learn about all the essential data science tools and techniques. Trainers will train you to use them on real-time industry projects. These projects will offer you practical experience on all the theories that you will learn in this course. You will gain an understanding of data structure and data manipulation. Trainers will make you understand and use linear and non-linear regression models and classification techniques for data analysis. In this online training, you will learn supervised and unsupervised learning models. They are logistic regression, linear regression, clustering, dimensionality reduction, K-NN, pipeline. With this Online training, you will get knowledge about machine learning, Algorithm implementation, and subscripting.
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 |
---|---|---|---|---|---|
21/10/2024 |
Data Science |
Online | Regular Batch (Mon-Sat) | Delhi | Book Now |
15/10/2024 |
Data Science |
Online | Regular Batch (Mon-Sat) | Delhi | Book Now |
19/10/2024 |
Data Science |
Online | Weekend Batch (Sat-Sun) | Delhi | Book Now |
19/10/2024 |
Data Science |
Online | Weekend Batch (Sat-Sun) | Delhi | Book Now |
Students Reviews
I enrolled in SevenMentor for a Data Science & Machine Learning Certification Course. The trainers of the course have considerable industry experience. They are very supportive. Their teaching style and study resources give a comprehensive approach to learning through projects and case studies. I will highly recommend this course.
- Sujit Panwar
I joined SevenMentor for Data Science & Machine Learning Certification Course. Their online study material, quality of teaching, management staff, and support from faculty has been excellent. They also support placement. With their assistance, I got placed in a reputed firm. I will surely recommend this course to my friends also.
- Disha Talwar
It was the right decision to join SevenMentor for the Data Science & Machine Learning Certification Course. Trainers of the course are knowledgeable. They shared a lot of new terms which are easy to understand. Experienced trainers have the patience to answer any query raised in the classroom. I am satisfied with the course.
- Maaya Kashyap
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Corporate Training
Corporate Training provides employees with valuable resources and information. So they can carry out their jobs more effectively and efficiently. SevenMentor delivers practical Corporate Training at Data Science & Machine Learning Classes In Delhi. In this training, you will learn to identify valuable data sources and automate collection processes. Trainers will help you in analyzing large amounts of information to discover patterns and trends. You will learn to Undertake to preprocess structured and unstructured data. You will learn to build predictive models and machine-learning algorithms. Trainers will impart essential knowledge about Python, R, SQL, and business intelligence tools ( Tableau). With this Corporate Training, you will learn to present information using data visualization techniques. Trainers will help you find solutions and strategies to business challenges. With this Corporate Training, you will work together with engineering and product development teams. Data Science & Machine Learning Corporate Training will make you a successful Data Science professional.
Our Placement Process
Eligibility Criteria
Placements Training
Interview Q & A
Resume Preparation
Aptitude Test
Mock Interviews
Scheduling Interviews
Job Placement
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