Data Analytics
Data Analysis where dealing with unstructured and structured data, Data Science is a field that encompasses anything related to data cleansing, preparation, and analysis. Put simply, Data Science is an umbrella term for techniques used when trying to extract insights and information from data.
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About Data Analytics
Regardless of whether it is India or elsewhere in the world, the requirement of Data Analyst is very high and will remain significant for quite a while. Each of the verticals from the IT industry is growing like anything, so is the requirement for different types of data. Thus, one can envision the rising demand for Data Analyst in the near future, and the need for Best Data Analytics Training in Pune is required, where We provide you with an opportunity to master the trademarks of Data Analyst, through our intensive training program!
For Pursuing Best Data Analytics Courses in Pune it doesn’t need a previous qualitative or math background. It starts by introducing basic concepts like the mean, median mode etc. and eventually covers all elements of an analytics (or) data science profession from assessing and preparing raw information to visualize your findings. If you are a programmer or a new graduate looking to switch to an exciting new career track, or a data analyst seeking to make the transition into the technology sector. This class will teach you the basic advanced techniques utilized by real-world industry data scientists.
Analytics: Utilizing Spark and Scala you are able to examine and research your data in an interactive environment with quick feedback. Data Analytics Classes in Pune will illustrate how to leverage the power of RDDs and Dataframes to manipulate data. It’s functional the availability of REPL surroundings and character makes it suited for a distributed computing framework like Spark. It covers the theoretical aspects of Statistical concepts and the implementation using Python and R. If you are new to Python, don’t worry — Data Analytics Courses in Pune begins with a crash course. If you have done some programming before or you’re new in Programming, you should pick this. This class shows you how to get set up on Microsoft Windows-based PCs; the sample code will run on Linux or macOS desktop systems.
Machine Learning along with Data Science: The core functionality of Spark and its built-in libraries assists to implement complex algorithms like Recommendations with very few lines of code. We’ll cover different types of calculations and datasets such as MapReduce, PageRank and Graph datasets.
What’s Spark? If you are an analyst or a data scientist, then you’re utilized to have multiple systems for working with information. SQL, Python, R, Java, etc.. With Spark, you’ve got an engine where you use the identical method to productionize your own code, conduct machine learning algorithms then can play and explore with large amounts of information.
Best Data Analytics Training in Pune providing exposure to Data Science, Big Data, Machine Learning, and Data Analytics. Defour Analytics has experienced and professional college. We have designed a specialized training program in Data Analytics Course in Pune, Data Science Courses, machine learning courses from Pune, python courses in Pune, SAS Training in Pune. At Sevenmentor, we have designed a specialized training and placement program in Data Analytics. Our corporate office offers state of the art infrastructure and training facilities. Our experienced and professional in house faculty, train and mentor candidates based on the requirements of the industry. We provide our candidates with unlimited interview calls until they get placed. Candidates just need to concentrate on their training, as we provide guaranteed placement. Our aim is to make sure that each and every candidate of ours is a finished product and job-ready before setting out. All these factors contribute to making SevenMentor a niche and best training institute in Pune. When you pass the Checkpoint certification exams, it opens a range of career opportunities for the network security professionals. Our instructor-led class, as well as training for Best Data Analytics Certification in Pune , are tailored in such a manner that every candidate can make the best. Students can look and pass their exams in the first effort.
What are the business sectors that are utilizing data analytics and machine learning?
They perform a variety of tasks related to organizing data, collecting and obtaining statistical data from them. They are also responsible for using the same to develop relational databases and to present the data in the form of graphs, charts, and tables. Data Science is a blend of various tools, algorithms, and machine learning principles with the wish to discover patterns that are hidden from the information. Data science, which is a concoction of machine learning principles, algorithms, and various tools are utilized to figure hidden patterns in data out. It is that data may be used to add value. The future of intelligence is based in science.Data Science is primarily used to make decisions and forecasts making use of predictive causal analytics and machine learning, the need for Information Analyst/Data Scientist is high and will remain important for some time. Information analytics is the process of examining data collections in order to draw conclusions about the information they contain with the assistance of specialized systems and applications. Techniques and data analytics technologies are utilized in industries. Organizations analyze and gather data associated with business processes, clients, market economics or experience. Data stored is categorized and analyzed to examine patterns and trends. Bachelor’s degree in related discipline or equivalent from a recognized college. Best Data Analytics Classes in Pune, our Data Analytics covers the whole data lifecycle starting from the extraction of cleaning, information, structuring, Data Mining, Forecasting, and reporting.Online Classes
Joining the Data Analytics Online Training program enhances your skills in data evaluation and visualization which will be helpful for making decisions related to the business expansion and product development. SevenMentor Online Data Analytics Training you'll learn different analytics tools and techniques, how to use SQL databases, the languages of R and Python, the way to generate data visualizations, and how to apply data and predictive analytics within a company environment. Learn perform machine learning utilizing scikit-learn, manipulate DataFrames from pandas, use the SciPy library of mathematical patterns, and how to analyze data in Python using multi-dimensional arrays in NumPy. Upon completion of the Best Data Analytics Courses Online, you are ready to crack the Data Analytics Certification Exam which will help you to get hired in top MNC’s.
Course Eligibility
- Freshers
- BE/ Bsc Candidate
- Any Engineers
- Any Graduate
- Any Post-Graduate
- Working Professionals
Syllabus Data Analytics
- 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 Analytics Training in Pune
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 Analytics 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 the all aspects of Data Analytics
- proficient in HIVE, R, Scala, and SQL, or Structured Query Language
- Understand the ecosystem of Data Analytics
- Practicals on Pig Hive Hbase
- Practicals on commercial distributions
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.
Assignments Duration
50 Hours
Trainers will provide you the assignments according to your skill sets and needs. Assignment duration will be 50 hrs to 60 hrs.
Support
24 / 7 Support
We are having 24/7 Support team to clear students’ needs and doubts. And special doubt clearing sessions every week.
Frequently Asked Questions
- Learn Data Analysis from Beginning
- Complete Data Science Bootcamp
- Data Analysis with Pandas and Python
- Advanced Excel Formulas and Functions
- College Data Analysis Courses
- Learn Python for Data Analysis and Visualization
- SQL for Data Analysis, etc.
Batch Schedule
DATE | COURSE | TRAINING TYPE | BATCH | CITY | REGISTER |
---|---|---|---|---|---|
23/12/2024 |
Data Analytics |
Classroom / Online | Regular Batch (Mon-Sat) | Pune | Book Now |
24/12/2024 |
Data Analytics |
Classroom / Online | Regular Batch (Mon-Sat) | Pune | Book Now |
28/12/2024 |
Data Analytics |
Classroom / Online | Weekend Batch (Sat-Sun) | Pune | Book Now |
28/12/2024 |
Data Analytics |
Classroom / Online | Weekend Batch (Sat-Sun) | Pune | Book Now |
Students Reviews
Completed Data Analytics Training from Sevenmentor after completing my Graduation. It was very nice experience to learn from here. Good infrastructure good teaching staff , n it is worth in fees they charge
- Dhiraj Bhosale
I have done Data Analytics claasses from SevenMentor. It was a nice experience. All the topics were done theoritically & practically on real devices. Trainers are also very knowledgeable & helpful. Availability of lab 24*7 also helped a lot. Would love to refer everyone who wanna make career in Development….
- Mrunal Sawankar
completed Data Analytcis classes From Sevenmentor, the experience, trainers are best and working professionals. Best institute for Hadoop training in pune. Go for SevenMentor.
- shubham somkuwar
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Corporate Training
Corporate Data Analytics Training is designed to provide extensive knowledge of Data Analysis like Data Collection, Extraction, Cleansing, Data Integration with high accuracy so your existing employee will help in constructing Prediction Models for Information Visualization and deploying the solution. Our highly experienced trainers are constantly there to handle the new Generation programs with newest versions and enable your workforce to handle complex situations. As Part of the Corporate Data Analytics Training, your entire workforce will be introduced with Statistical Evaluation, Text Mining, Regression Modelling, Hypothesis Testing, Predictive Analytics, Machine Programming languages such as R and Python. Be ready to match footsteps with the ongoing trend and transformation towards AI and see the growth of your organization with empowered employees.
Our Placement Process
Eligibility Criteria
Placements Training
Interview Q & A
Resume Preparation
Aptitude Test
Mock Interviews
Scheduling Interviews
Job Placement
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