Data Science
The digital era has revolutionized our consumer behaviour, we generate tremendous amounts of data right from our personal preferences to recent shopping choices. Such data is very important for the companies as this holds valuable information that they can use to make better decisions, provide great offers and help enhance the company’s business growth.
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- Regular: 2 Batches
- Weekends: 2 Batches
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About Data Science
Our consumer buying behavior has been transformed by the digital era; we generate massive volumes of data, ranging from personal preferences to recent purchase decisions. Such data is critical for businesses since it contains useful information that can be used to make better decisions, provide better offerings, and aid in the company's growth. The task of acquiring such data, finding clear trends, and making statistically relevant decisions from it is known as data science. The data scientist has become a key role in companies and provides all the required stats and data for the management to make perfect decisions. It has been suggested by NASSCOM that by the year 2024 around 1.3 lakh new Data Science professionals will be required in India alone. The Data Scientist job has tremendous career opportunities in the current market and the job of data analytics is proliferating in all the major business and IT sectors. Since this job has gained huge relevance in the current job market, the p[ackages offered to Data Scientists have been consistently rising and now can be as high as 50L per annum.
Machine Learning
Machine learning is a term used informally to describe the use of computers to analyze data and extract useful information from it. It is now possible to teach a Machine (computer) to hunt for useful information in vast datasets and provide statistical and business significance from it, thanks to new-age software development. The ML programs are written in Python; Google has developed TensorFlow for ML and AI programs, while Oracle has its own proprietary coding format. Machine Learning and AI-based data mining are expected to be the next big thing, as machines can process infinitely more information than humans. Thus an ML programmer is the hottest position in the Data Science field and has been highly sought after by many.
We at SevenMentor have developed a perfect Data Science with Machine Learning training in Ahmedabad for all the IT aspirants, who wish to be Data scientists.
Data Science course at SevenMentor
As said above, Data Science along with Machine Learning has become the largest recruiter in the IT world. A Data Science course at SevenMentor will surely land you a job in many major corporations in India. SevenMentor has started the best Data Science and Machine Learning course in Ahmedabad. We offer the best training and skill development program in Ahmedabad and our Data Science course has been rated as the best in the city. The utilization of Machine learning for the management of a huge data set requires a person to understand complex systems and dynamic layered processes. This has resulted in a niche market in which Data Scientists can be paid a good salary. Due to the high level of technical understanding and real-world skills required to undertake the job of a Data Scientist, they are an important part of the organization. We at SevenMentor take pride in our thoroughly developed training protocols and highly experienced trainers. We provide training for around 45+ IT, software and language courses, and have more than 10 years of experience in this field. SevenMentor has garnered tremendous experience as an organization and thus has been influential in developing our versatile courses.
We have developed a training methodology that has been designed by slowly improving on our existing ideas. Our Data Science course in Ahmedabad is one of the prominent courses provided by the institute and thus has been one of the most neatly organized and designed training courses. We also have highly experienced trainers that have been handpicked for their expertise in the field, they have years of real-world experience and have been placed in high positions at prominent organizations. The experienced staff that we have provides students with industry-oriented knowledge of Data Science methods. Our students receive first-hand knowledge and industry-relevant skills from the trainers. So join the SevenMentor Institute for Data Science and Machine Learning course in Ahmedabad to get a quality education and up-skill yourself in the hottest career option in the IT sector. Our Ahmedabad center has the best teaching infrastructure in India. We have a large number of computers, so students have individual access to high-end hardware and the most up-to-date software. Our training facilities are the most modern teaching arenas in India, and we have projection-based teaching platforms, high-quality animation videos and remote logging-in of equipment. We also have a large library of traditional as well as electronic reading materials. The best-in-class infrastructure will surely help in understanding concepts and smoothen the learning process for students. So enroll now at SevenMentor in Ahmedabad to have a top-quality Data Science course in the city.
Certification: We provide industry-accepted certification for all the courses. Our DataScience certificate course adheres to the relevant requirements set up by the world’s top companies and is thus accepted by them. The certification is tremendously helpful for your job placements in major MNCs. Our rigorous training and certification will surely make you industry-worthy by the end of the course. So get certified for the Data Science skills by joining SevenMentor at Ahmedabad.
Job-Placements: SevenMentor institute also has an in-house job placement scheme and we are proud to announce that more than 1000 students have got positions in leading multinational companies all over India. Apart from core Data Science and Machine Learning concepts, our trainers also prepare the students for interviews, personality development, and provide English language courses offered at our institute. Training at SevenMentor is an efficient and affordable way to up-skill your portfolio and receive significant placements for Data Science jobs in Ahmedabad and all over the world.
Online Classes
Our online training methodology at SevenMentor stands out from the rest as we offer personalized teaching modules and individual attention to students even in an online setting. The online Data Science course in Ahmedabad offers you the best, right at your home. We have pre-recorded as well as live sessions for the Data Science and Machine learning Our trainers are available for you to provide tips and solve problems for the entire duration of your course. The pre-recorded sessions provide the flexibility to learn at your own pace and time and live sessions help in real time problem solving and handling of queries by our expert trainers. The online training also ensures you have practical application knowledge as our trainers hold test sessions and hands-on approach is substituted by remote monitoring of work by our trainers. Overall the online Data Science training in Ahmedabad is also effective in imparting the required knowledge to students on par with our offline training at SevenMentor.
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 |
---|---|---|---|---|---|
16/12/2024 |
Data Science |
Online | Regular Batch (Mon-Sat) | Ahmedabad | Book Now |
10/12/2024 |
Data Science |
Online | Regular Batch (Mon-Sat) | Ahmedabad | Book Now |
14/12/2024 |
Data Science |
Online | Weekend Batch (Sat-Sun) | Ahmedabad | Book Now |
14/12/2024 |
Data Science |
Online | Weekend Batch (Sat-Sun) | Ahmedabad | Book Now |
Students Reviews
SevenMentor is the best training institute in Ahmedabad, they have really great trainers and teaching facilities. I have understood major concepts from the Machine learning course and I have got confidence in myself.
- Minal Thapa
Thank you very much SevenMentor. I am happy to have completed the Data Science course and receive a good job opportunity from Sevenmentor. This has been a really good start to my career.
- Shruiti Parchand
SevenMentor is one of the best training institutes for IT related training. I had joined them for a DSML course and I am quite happy with the training I received. I will surely recommend to all of you that you join this course in Ahmedabad. Thank you .
- Ritesh Navle
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Corporate Training
SevenMentor has a contingent of trainers with experience of training and working in the technology sector for many years. The trainers are industry experts and have several years of operating experience and tremendous knowledge of business development and use of IT in the upgrading of business. We have partnered with many small and large corporations and routinely provide them with various IT, software, and hardware maintenance, server maintenance courses, and business development training. SevenMentor undertakes specialized training and on-the-job training for corporate employees. It is a very fast and effective training, and surely helps companies in upgrading their employees' knowledge and skills. We also have joint sessions with multiple companies, this helps in knowledge and skills sharing between different sectors. Our corporate clients have rated us best in the industry for many software-related training. We have provided the best corporate Data Science course in Ahmedabad and have been highly rated by many companies.
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Eligibility Criteria
Placements Training
Interview Q & A
Resume Preparation
Aptitude Test
Mock Interviews
Scheduling Interviews
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