Data Science
Nowadays, the Customer is the king and it’s necessary to maintain good relations with them, so Data is significant. It helps in managing good relationships with customers. SevenMentor is a prominent institute, where you will learn Data Science and Machine Learning and make a profitable career in this field.
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- Regular: 2 Batches
- Weekends: 2 Batches
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About Data Science
What is Data Science?
Data Science is the analysis of both structured and unstructured data. It removes actionable insights from large and ever-increasing volumes of data created and collected by organizations. Data Science involves preparing data for processing, analysis. It indicates patterns by performing advanced data analysis and presenting the outcomes. It enables stakeholders to bring out informed conclusions.
What is Machine Learning?
Machine Learning is a part of artificial intelligence. It is the analysis of Computer algorithms that enhance automatically through experience and by the use of data. Machine Learning algorithms develop a model based on sample data. That is known as training data. This training data helps to make predictions and decisions without being explicitly programmed to do so. SevenMentor, a prominent institute, provides the best Machine Learning Course In Indore.
Why should you learn Data Science?
Helps to understand customers- Data helps to understand customers in a much empowered and enhanced manner. With Data Science, brands can relate to their customers in a personalized way. It helps to ensure better engagement and brand power.
Helps brands to communicate the story- Data Science allows brands to convey the story to their target audience. It helps in better brand connect. After all, nothing connects with consumers like a powerful story inculcates all human feelings.
Growing and evolving field- Big Data is the field that is constantly growing. With so many tools developed, big data assists brands and organizations in solving complicated problems in IT, Human resources effectively.
Accessible to almost all sectors- One of the significant aspects of Data Science is its findings and results apply to any field. It applies to healthcare, education, travel, and many more. Data Science helps sectors to analyze their problems and solve them effectively.
Recruiting the right talent for the organization- The amount of information is available through job search websites, social media, corporate databases. It helps data scientists to work through all these data points to find candidates who best fit the requirements of an organization.
Due to all these reasons, SevenMentor has formed a course. So you can learn about Data Science and Machine Learning and achieve success in this constantly growing field.
Why choose SevenMentor to learn Data Science?
SevenMentor is the Best Data Science Training Institute in Indore that provides students with an end-to-end understanding of Data Science. It has formed the course by keeping in mind the vast demand and supply gap in the Data Science field. Our Data Science Course in Indore is suitable for both technical and non-technical background students. We put them at ease while learning. SevenMentor has formed a Data Science course with placement in Indore. Our Data Science course fees are affordable for everyone. So, a person from any financial background can join this course. It is a pocket-friendly course. At Our Data Science & Machine Learning Training In Indore, we have trained more than 40000+ students and professionals with 4000 training sessions. At our Data Science & Machine Learning Classes In Indore, you will get extensive knowledge of Data Science from real-time industry experts. Our Course curriculum includes Introduction to Data Science & Analytics Techniques, Fundamentals of Excel, Introduction to Data Visualization, Data Manipulation using Advanced Excel, Data Cleaning & Working with conditions by using Excel.
At our Data Science & Machine Learning Training In Indore, you will learn about MS SQL & MS Access, SQL Queries & Views, Python Fundamentals, Python MySQL, Data Analysis. Our trainers have 15+ years of experience in the Data Science field. They will provide knowledge about Data Analysis, Pandas Data Frame, Statistical Fundamentals, Machine Learning with Python, Functions, Recommender systems. Each module of Data Science Classes In Indore features an assignment and capstone projects. It helps the students to perform their learning in a logical context. After completion of the classes, we help students to devise solutions for real-time problems in the industry. At our Data Science Training In Indore, We have morning and evening batches. Weekends and weekdays batches are also available for the beneficial learning of students. We have a curated lab facility for Data Science. In this Data Science training, you will learn with real-time examples. We provide assignments and handouts after every session. Our trainers conduct assessment tests after the end of each module. At our Machine Learning Classes in Indore, we provide 100% assured placement support. SevenMentor delivers career assistance with the help of its 50 placement partners. Moreover, it prepares students for industry interviews. Trainers of the course will assist you in resume building as per current market needs and interview preparation. Post completion of the course, you will get a globally recognized certificate from our institute. We make sure that after completing this course you become the top choice among employers.
Online Classes
There is rapid progress in Online Training. Due to its flexibility, You can learn the bulk of new things. SevenMentor delivers Online Data Science Training in Indore. This online training includes weekly assignments in Data Cleaning and Analysis by using Data visualization in Python, Pandas, Machine Learning, Exploratory Data Analytics mini-projects, and a basis of Python. It helps the learners to keep pace with their understanding. This online training builds a solid foundation in SQL, Statistics, visualization using both Tableau and Python. Another feature of this training is the Capstone projects. It allows students to apply learning in real-life scenarios. You can get extensive knowledge about Data Science. A PC or Laptop with a proper internet connection is sufficient for you. Trainers will teach you about the foundational perspective of statistics, Business intelligence, Mathematics, Probability Distribution, and Hypothesis Testing. You will learn all the necessary skills and become a proficient Data Scientist.
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
- Receive and process data
- Browse Raw Data
- Analyze and foresee data
- Demonstrate the results.
Batch Schedule
DATE | COURSE | TRAINING TYPE | BATCH | CITY | REGISTER |
---|---|---|---|---|---|
16/12/2024 |
Data Science |
Online | Regular Batch (Mon-Sat) | Indore | Book Now |
17/12/2024 |
Data Science |
Online | Regular Batch (Mon-Sat) | Indore | Book Now |
21/12/2024 |
Data Science |
Online | Weekend Batch (Sat-Sun) | Indore | Book Now |
21/12/2024 |
Data Science |
Online | Weekend Batch (Sat-Sun) | Indore | Book Now |
Students Reviews
Being a tech-savvy person, I always wanted to learn Big data. So I enrolled in a Data Science & Machine Learning Certification Course at SevenMentor. Trainers of the course train you from basics with necessary concepts. They also teach you how to face interviews along with placement security. I think it is the best Data Science course.
- Swati Sharma
After a lot of research, I joined the Data Science & Machine Learning Certification Course at SevenMentor. This course has a power-packed curriculum that enabled me to learn through real-time practical examples and business challenges. The trainers are knowledgeable and give ideas into their real-time executing challenges. I believe one must go for this course.
- Virat Kashyap
I cannot express in words my feeling after completing SevenMentor's Data Science & Machine Learning Certification Course. Now I am operating as a Data Analyst in a reputed firm. Trainers of the course helped in getting impeccable, in-depth knowledge and cleared all my doubts. It helped me grow in my career. So I understood the topic effectively. I will highly approve of this course.
- Sameer Singh
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Corporate Training
Corporate Training helps to identify employees who need extra help with specific aspects of their jobs. It grooms employees for promotions or more progressive job duties. SevenMentor delivers practical Corporate Data Science Training in Indore. With this corporate training, you can learn to identify opportunities for leveraging company data to drive business outcomes. You can learn to analyze and mine data from the company database. It assists in the improvement of product development, business strategies, and marketing techniques. We make sure that you learn to analyze the accuracy and effectiveness of new data sources and data gathering techniques. With this corporate training, you will learn to formulate custom data models and algorithms to apply to data sets. By using predictive models, you can optimize and enhance customer experience, revenue generation, and targeting other business solutions. The valuable knowledge of trainers will help you become the best Data Scientist.
Our Placement Process
Eligibility Criteria
Placements Training
Interview Q & A
Resume Preparation
Aptitude Test
Mock Interviews
Scheduling Interviews
Job Placement
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