DATA SCIENCE CERTIFICATION AUTHORITIES

Data Science Course Features

DATA SCIENCE COURSE LEAD MENTORS

DATA SCIENCE COURSE FEE IN INDIA

Live Virtual

Instructor Led Live Online

110,000
72,345

  • IABAC® & NASSCOM® Certification
  • 8-Month | 700 Learning Hours
  • 120-Hour Live Online Training
  • 25 Capstone & 1 Client Project
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

Blended Learning

Self Learning + Live Mentoring

66,000
43,995

  • Self Learning + Live Mentoring
  • IABAC® & NASSCOM® Certification
  • 1 Year Access To Elearning
  • 25 Capstone & 1 Client Project
  • Job Assistance
  • 24*7 Leaner assistance and support

Classroom

In - Person Classroom Training

110,000
82,845

  • IABAC® & NASSCOM® Certification
  • 8-Month | 700 Learning Hours
  • 120-Hour Classroom Sessions
  • 25 Capstone & 1 Client Project
  • Cloud Lab Access
  • Internship + Job Assistance

ARE YOU LOOKING TO UPSKILL YOUR TEAM ?

Enquire Now

UPCOMING DATA SCIENCE TRAINING SCHEDULES IN INDIA

BEST DATA SCIENCE CERTIFICATIONS

The entire training includes real-world projects and highly valuable case studies.

IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.

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WHY DATAMITES INSTITUTE FOR DATA SCIENCE COURSE

Why DataMites Infographic

SYLLABUS OF DATA SCIENCE COURSE IN INDIA

MODULE 1: DATA SCIENCE COURSE INTRODUCTION 

  • CDS Course Introduction
  • 3 Phase Learning
  • Learning Resources
  • Assessments & Certification Exams
  • DataMites Mobile App
  • Support Channels

MODULE 2: DATA SCIENCE ESSENTIALS 

  • Introduction to Data Science
  • Evolution of Data Science
  • Data Science Terminologies
  • Data Science vs AI/Machine Learning
  • Data Science vs Analytics

MODULE 3: DATA SCIENCE DEMO 

  • Business Requirement: Use Case
  • Data Preparation
  • Machine learning Model building
  • Prediction with ML model
  • Delivering Business Value

MODULE 4: ANALYTICS CLASSIFICATION 

  • Types of Analytics
  • Diagnostic Analytics
  • Predictive Analytics
  • Prescriptive Analytics

MODULE 5: DATA SCIENCE AND RELATED FIELDS

  • Introduction to AI
  • Introduction to Computer Vision
  • Introduction to Natural Language Processing
  • Introduction to Reinforcement Learning
  • Introduction to GAN
  • Introduction to  Generative Passive Models

MODULE 6: DATA SCIENCE ROLES & WORKFLOW

  • Data Science Project workflow
  • Roles: Data Engineer, Data Scientist, ML Engineer and MLOps Engineer
  • Data Science Project stages

MODULE 7: MACHINE LEARNING INTRODUCTION

  • What Is ML? ML Vs AI
  • ML Workflow, Popular ML Algorithms
  • Clustering, Classification And Regression
  • Supervised Vs Unsupervised

MODULE 8: DATA SCIENCE INDUSTRY APPLICATIONS 

  • Data Science in Finance and Banking
  • Data Science in Retail
  • Data Science in Health Care
  • Data Science in Logistics and Supply Chain
  • Data Science in Technology Industry
  • Data Science in Manufacturing
  • Data Science in Agriculture

MODULE 1: PYTHON BASICS 

  • Introduction of python
  • Installation of Python and IDE
  • Python objects
  • Python basic data types
  • Number & Booleans, strings
  • Arithmetic Operators
  • Comparison Operators
  • Assignment Operators
  • Operator’s precedence and associativity

MODULE 2: PYTHON CONTROL STATEMENTS 

  • IF Conditional statement
  • IF-ELSE • NESTED IF
  • Python Loops basics
  • WHILE Statement
  • FOR statements
  • BREAK and CONTINUE statements

MODULE 3: PYTHON DATA STRUCTURES 

  • Basic data structure in python
  • String object basics and inbuilt methods
  • List: Object, methods, comprehensions
  • Tuple: Object, methods, comprehensions
  • Sets: Object, methods, comprehensions
  • Dictionary: Object, methods, comprehensions

MODULE 4: PYTHON FUNCTIONS 

  • Functions basics
  • Function Parameter passing
  • Iterators
  • Generator functions
  • Lambda functions
  • Map, reduce, filter functions

MODULE 5: PYTHON NUMPY PACKAGE 

  • NumPy Introduction
  • Array – Data Structure
  • Core Numpy functions
  • Matrix Operations

MODULE 6: PYTHON PANDASPACKAGE

  • Pandasfunctions
  • Data Frame and Series – Data Structure
  • Data munging with Pandas
  • Imputation and outlier analysis

 

MODULE 1: OVERVIEW OF STATISTICS 

  • Descriptive And Inferential Statistics
  • Basic Terms Of Statistics
  • Types Of Data

MODULE 2: HARNESSING DATA 

  • Random Sampling
  • Sampling With Replacement And Without Replacement
  • Cochran's  Minimum Sample Size
  • Simple Random Sampling
  • Stratified Random Sampling
  • Cluster Random Sampling
  • Systematic Random Sampling
  • Biased Random Sampling Methods
  • Sampling Error
  • Methods Of Collecting Data

MODULE 3: EXPLORATORY DATA ANALYSIS 

  • Exploratory Data Analysis Introduction
  • Measures Of Central Tendencies: Mean, Median And Mode
  • Measures Of Central Tendencies: Range, Variance And Standard Deviation
  • Data Distribution Plot: Histogram
  • Normal Distribution
  • Z Value / Standard Value
  • Empherical Rule  and Outliers
  • Central Limit Theorem
  • Normality Testing
  • Skewness & Kurtosis
  • Measures Of Distance: Euclidean, Manhattan And MinkowskiDistance

MODULE 4: HYPOTHESIS TESTING 

  • Hypothesis Testing Introduction
  • P- Value, Confidence Interval
  • Parametric Hypothesis Testing Methods
  • Hypothesis Testing Errors : Type I And Type Ii
  • One Sample T-test
  • Two Sample Independent T-test
  • Two Sample Relation T-test
  • One Way Anova Test

MODULE 5: CORRELATION AND REGRESSION 

  • Correlation Introduction
  • Direct/Positive Correlation
  • Indirect/Negative Correlation
  • Regression
  • Choosing Right Method

 

MODULE 1: MACHINE LEARNING INTRODUCTION 

  • What Is ML? ML Vs AI
  • ML Workflow, Popular ML Algorithms
  • Clustering, Classification And Regression
  • Supervised Vs Unsupervised

MODULE 2: PYTHON NUMPY & PANDAS PACKAGE 

  • NumPy & Pandas functions
  • Array – Data Structure
  • Core Numpy functions
  • Matrix Operations
  • Data Frame and Series – Data Structure
  • Data munging with Pandas
  • Imputation and outlier analysis

MODULE 3: VISUALIZATION WITH PYTHON 

  • Visualization Packages (Matplotlib)
  • Components Of A Plot, Sub-Plots
  • Basic Plots: Line, Bar, Pie, Scatter
  • Advanced Python Data Visualizations

MODULE 4: ML ALGO: LINEAR REGRESSION

  • Introduction to Linear Regression
  • How it works: Regression and Best Fit Line
  • Modeling and Evaluation in Python

MODULE 5: ML ALGO: KNN 

  • Introduction to KNN
  • How It Works: Nearest Neighbor Concept
  • Modeling and Evaluation in Python

MODULE 6: ML ALGO: LOGISTIC REGRESSION 

  • Introduction to Logistic Regression
  • How it works: Classification & Sigmoid Curve
  • Modeling and Evaluation in Python

MODULE 7: PRINCIPLE COMPONENT ANALYSIS (PCA) 

  • Building Blocks Of PCA
  • How it works: Finding Principal Components
  • Modeling PCA in Python

MODULE 8: ML ALGO: K MEANS CLUSTERING 

  • Understanding Clustering (Unsupervised)
  • K Means Algorithm
  • How it works: K Means theory
  • Modeling in Python

MODULE 1: MACHINE LEARNING INTRODUCTION 

  • What Is ML? ML Vs AI
  • ML Workflow, Popular ML Algorithms
  • Clustering, Classification And Regression
  • Supervised Vs Unsupervised

MODULE 2: ML ALGO: LINEAR REGRESSSION 

  • Introduction to Linear Regression
  • How it works: Regression and Best Fit Line
  • Modeling and Evaluation in Python

MODULE 3: ML ALGO: LOGISTIC REGRESSION 

  • Introduction to Logistic Regression
  • How it works: Classification & Sigmoid Curve
  • Modeling and Evaluation in Python

MODULE 4: ML ALGO: KNN 

  • Introduction to KNN
  • How It Works: Nearest Neighbor Concept
  • Modeling and Evaluation in Python

MODULE 5: ML ALGO: K MEANS CLUSTERING 

  • Understanding Clustering (Unsupervised)
  • K Means Algorithm
  • How it works : K Means theory
  • Modeling in Python

MODULE 6: PRINCIPLE COMPONENT ANALYSIS (PCA) 

  • Building Blocks Of PCA
  • How it works: Finding Principal Components
  • Modeling PCA in Python

MODULE 7: ML ALGO: DECISION TREE 

  • Random Forest Ensemble technique
  • How it works: Bagging Theory
  • Modeling and Evaluation in Python

MODULE 8 : ML ALGO: NAÏVE BAYES 

  • Introduction to Naive Bayes
  • How it works: Bayes' Theorem
  • Naive Bayes For Text Classification
  • Modeling and Evaluation in Python

MODULE 9: GRADIENT BOOSTING, XGBOOST 

  • Introduction to Boosting and XGBoost
  • How it works: weak learners' concept
  • Modeling and Evaluation of in Python

MODULE 10: ML ALGO: SUPPORT VECTOR MACHINE  (SVM) 

  • Introduction to SVM
  • How It Works: SVM Concept, Kernel Trick
  • Modeling and Evaluation of SVM in Python

MODULE 11: ARTIFICIAL NEURAL NETWORK (ANN) 

  • Introduction to ANN
  • How It Works: Back prop, Gradient Descent
  • Modeling and Evaluation of ANN in Python

MODULE 12: ADVANCED ML CONCEPTS 

  • Adv Metrics (Roc_Auc, R2, Precision, Recall)
  • K-Fold Cross-validation
  • Grid And Randomized Search CV In Sklearn
  • Imbalanced Data Set: Smote Technique
  • Feature Selection Techniques

MODULE 1: TIME SERIES FORECASTING - ARIMA 

  • What is Time Series?
  • Trend, Seasonality, cyclical and random
  • Autoregressive Model (AR)
  • Moving Average Model (MA)
  • Stationarity of Time Series
  • ARIMA Model
  • Autocorrelation and AIC 

MODULE 2: FEATURE ENGINEERING 

  • Introduction to Features Engineering
  • Transforming Predictors
  • Feature Selection methods
  • Backward elimination technique
  • Feature importance from ML modeling

MODULE 3: SENTIMENT ANALYSIS 

  • Introduction to Sentiment Analysis
  • Python packages: TextBlob, NLTK
  • Case study: Twitter Live Sentiment Analysis

MODULE 4: REGULAR EXPRESSIONS WITH PYTHON 

  • Regex Introduction
  • Regex codes
  • Text extraction with Python Regex

MODULE 5: ML MODEL DEPLOYMENT WITH FLASK

  • Introduction to Flask
  • URL and App routing
  • Flask application – ML Model deployment

MODULE 6: ADVANCED DATA ANALYSIS WITH MS EXCEL 

  • MS Excel core Functions
  • Pivot Table
  • Advanced Functions (VLOOKUP, INDIRECT..)
  • Linear Regression with EXCEL
  • Goal Seek Analysis
  • Data Table
  • Solving Data Equation with EXCEL
  • Monte Carlo Simulation with MS EXCEL

MODULE 7: AWS CLOUD FOR DATA SCIENCE

  • Introduction of cloud
  • Difference between GCC, Azure,AWS
  • AWS Service ( EC2 and S3 service)
  • AWS Service (AMI), AWS Service (RDS)
  • AWS Service (IAM), AWS (Athena service)
  • AWS (EMR), AWS, AWS (Redshift)
  • ML Modeling with AWS Sage Maker 

MODULE 8: AZURE FOR DATA SCIENCE 

  • Introduction to AZURE ML studio
  • Data Pipeline and ML modeling with Azure

MODULE 1: DATABASE INTRODUCTION 

  • DATABASE Overview
  • Key concepts of database management
  • CRUD Operations
  • Relational Database Management System
  • RDBMS vs No-SQL (Document DB)

MODULE 2: SQL BASICS 

  • Introduction to Databases
  • Introduction to SQL
  • SQL Commands
  • MY SQL  workbench installation
  • Comments
  • import and export dataset

MODULE 3: DATA TYPES AND CONSTRAINTS 

  • Numeric, Character, date time data type
  • Primary key, Foreign key, Not null
  • Unique, Check, default, Auto increment

MODULE 4: DATABASES AND TABLES (MySQL) 

  • Create database
  • Delete database
  • Show and use databases
  • Create table, Rename table
  • Delete table, Delete  table records
  • Create new table from existing data types
  • Insert into, Update records
  • Alter table

MODULE 5: SQL JOINS 

  • Inner join
  • Outer join
  • Left join
  • Right join
  • Cross join
  • Self join

MODULE 6: SQL COMMANDS AND CLAUSES 

  • Select, Select distinct
  • Aliases, Where clause
  • Relational operators, Logical
  • Between, Order by, In
  • Like, Limit, null/not null, group by
  • Having, Sub queries

MODULE 7 : DOCUMENT DB/NO-SQL DB 

  • Introduction of Document DB
  • Document DB vs SQL DB
  • Popular Document DBs
  • MongoDB basics
  • Data format and Key methods
  • MongoDB data management

MODULE 1: GIT  INTRODUCTION 

  • Purpose of Version Control
  • Popular Version control tools
  • Git Distribution Version Control
  • Terminologies
  • Git Workflow
  • Git Architecture

MODULE 2: GIT REPOSITORY and GitHub 

  • Git Repo Introduction
  • Create New Repo with Init command
  • Copying existing repo
  • Git user and remote node
  • Git Status and rebase
  • Review Repo History
  • GitHub Cloud Remote Repo

MODULE 3: COMMITS, PULL, FETCH AND PUSH 

  • Code commits
  • Pull, Fetch and conflicts resolution
  • Pushing to Remote Repo

MODULE 4: TAGGING, BRANCHING AND MERGING 

  • Organize code with branches
  • Checkout branch
  • Merge branches

MODULE 5: UNDOING CHANGES 

  • Editing Commits
  • Commit command Amend flag
  • Git reset and revert

MODULE 6: GIT WITH GITHUB AND BITBUCKET 

  • Creating GitHub Account
  • Local and Remote Repo
  • Collaborating with other developers
  • Bitbucket Git account

MODULE 1: BIG DATA INTRODUCTION 

  • Big Data Overview
  • Five Vs of Big Data
  • What is Big Data and Hadoop
  • Introduction to Hadoop
  • Components of Hadoop Ecosystem
  • Big Data Analytics Introduction

MODULE 2 : HDFS AND MAP REDUCE 

  • HDFS – Big Data Storage
  • Distributed Processing with Map Reduce
  • Mapping and reducing  stages concepts
  • Key Terms: Output Format, Partitioners, Combiners, Shuffle, and Sort
  • Hands-on Map Reduce task

MODULE 3: PYSPARK FOUNDATION 

  • PySpark Introduction
  • Spark Configuration
  • Resilient distributed datasets (RDD)
  • Working with RDDs in PySpark
  • Aggregating Data with Pair RDDs

MODULE 4: SPARK SQL and HADOOP HIVE 

  • Introducing Spark SQL
  • Spark SQL vs Hadoop Hive
  • Working with Spark SQL Query Language

MODULE 5 : MACHINE LEARNING WITH SPARK ML 

  • Introduction to MLlib Various ML algorithms supported by MLib
  • ML model with Spark ML
  • Linear regression
  • logistic regression
  • Random forest

MODULE 6: KAFKA and Spark 

  • Kafka architecture
  • Kafka workflow
  • Configuring Kafka cluster
  • Operations

MODULE 1: BUSINESS INTELLIGENCE INTRODUCTION 

  • What Is Business Intelligence (BI)?
  • What Bi Is The Core Of Business Decisions?
  • BI Evolution
  • Business Intelligence Vs Business Analytics
  • Data Driven Decisions With Bi Tools
  • The Crisp-Dm Methodology

MODULE 2: BI WITH TABLEAU: INTRODUCTION

  • The Tableau Interface
  • Tableau Workbook, Sheets And Dashboards
  • Filter Shelf, Rows And Columns
  • Dimensions And Measures
  • Distributing And Publishing

MODULE 3 : TABLEAU: CONNECTING TO DATA SOURCE 

  • Connecting To Data File , Database Servers
  • Managing Fields
  • Managing Extracts
  • Saving And Publishing Data Sources
  • Data Prep With Text And Excel Files
  • Join Types With Union
  • Cross-Database Joins
  • Data Blending
  • Connecting To Pdfs

MODULE 4: TABLEAU : BUSINESS INSIGHTS 

  • Getting Started With Visual Analytics
  • Drill Down And Hierarchies
  • Sorting & Grouping
  • Creating And Working Sets
  • Using The Filter Shelf
  • Interactive Filters
  • Parameters
  • The Formatting Pane
  • Trend Lines & Reference Lines
  • Forecasting
  • Clustering

MODULE 5: DASHBOARDS, STORIES AND PAGES 

  • Dashboards And Stories Introduction
  • Building A Dashboard
  • Dashboard Objects
  • Dashboard Formatting
  • Dashboard Interactivity Using Actions
  • Story Points
  • Animation With Pages

MODULE 6: BI WITH POWER-BI 

  • Power BI basics
  • Basics Visualizations
  • Business Insights with Power BI

OFFERED DATA SCIENCE COURSES IN INDIA

DATA SCIENCE COURSE REVIEWS

ABOUT DATA SCIENTIST TRAINING IN INDIA

A Data Science course in India offers a promising opportunity to gain expertise in data analysis, machine learning, and artificial intelligence, preparing individuals for lucrative careers in diverse industries while meeting the growing demand for data-driven insights.

The data science platforms market, with a 2022 value of USD 112.12 billion, is projected to exhibit substantial growth, reaching approximately USD 501.03 billion by 2032, driven by an anticipated compound annual growth rate (CAGR) of 16.2% between 2023 and 2032.

In response to this demand, DataMites provides extensive data science training in India, including internships and job placement assistance, to nurture a new breed of skilled data science experts.

DataMites enjoys global recognition for its exceptional data science courses in India. The Certified Data Scientist Course in India is thoughtfully crafted to cater to both novice and intermediate learners, placing a strong emphasis on building a robust data science foundation. This program covers essential aspects such as statistics, mathematics, Python, and machine learning, all geared towards preparing participants for a successful career in the ever-changing field of data science.

The learning approach at DataMites in India follows a structured three-phase methodology.

DataMites follows a unique and organized three-step learning process to provide comprehensive data science courses in India.

Phase 1- Pre-Course Self-Study: We offer top-notch video content to help you build a solid understanding of fundamental data science concepts.

Phase 2- Interactive Training: Participants can choose between live online data science training or offline data science training in India. During this phase, you will engage in 20 hours of training per week for three months. The training covers a comprehensive curriculum, hands-on projects, and guidance from experienced trainers and mentors. DataMites has expanded its data science course offerings to several locations across India, including but not limited to India, Chennai, Hyderabad, Pune, Mumbai, India, Bhubaneswar, Nagpur, Kolkata and Delhi

Phase 3 - Internship & Placement Support: In this pivotal phase, participants undertake 20 capstone projects, including a project tailored to a specific client, leading to a valuable certification for data science internships. Our Placement Assistance Team (PAT) provides comprehensive career guidance and support as an integral part of our data science program. This training, which includes placement opportunities in India, is meticulously crafted to enhance practical skills, ensuring participants are well-prepared for a smooth transition into careers in AI and data science.

Prominent DataMites Data Science Certifications Available in India

DataMites takes pride in providing highly sought-after data science certifications in India:

  1. Certified Data Science 
  2. Statistics for Data Science
  3. Data Science for Managers
  4. Python Applications in Data Science
  5. Data Science Foundation
  6. Data Science for Marketing
  7. Data Science with R
  8. Data Science for Operation
  9. Data Science for Finance
  10. Data Science in Human Resources
  11. Data Science Foundation
  12. Diploma in Data Science

Every certification is strategically crafted to align with distinct career objectives and industry requirements, guaranteeing that our students in India receive top-notch training to propel their data science careers forward.

The Data Science Course Curriculum Offered by DataMites in India

DataMites Certified Data Scientist Training in India offers an extensive and well-designed curriculum that covers a wide range of topics in data science. This training program consists of 9 separate modules, each dedicated to a specific aspect of data science, ensuring a holistic and comprehensive learning experience.

Python Fundamentals

  1. Basics of Python Programming
  2. Python Control Structures
  3. Data Structures in Python
  4. Implementing Functions in Python
  5. Working with Python's Numpy Library
  6. Using Python's Pandas Library

Data Science Essentials

  1. Fundamental Concepts of Data Science
  2. Introduction to Data Engineering
  3. Applying Python to Data Science
  4. Python for Data Visualization
  5. R Programming Basics
  6. Statistical Techniques
  7. Basics of Machine Learning

Machine Learning Expert

  1. Introduction to Machine Learning
  2. Techniques in Linear Regression
  3. Logistic Regression Implementation
  4. K-nearest Neighbors (KNN) Algorithm
  5. Cluster Analysis with K Means
  6. Principal Component Analysis (PCA) Exploration
  7. Decision Trees Techniques
  8. Naïve Bayes Methods
  9. Gradient Boosting & Xgboost Techniques
  10. Support Vector Machines (SVM) Applications
  11. Introduction to Artificial Neural Networks (ANN)
  12. Advanced Machine Learning Topics

Data Science Advanced Topics

  1. ARIMA for Time Series Analysis
  2. Feature Engineering Methods
  3. Sentiment Analysis Process
  4. Python Regular Expressions
  5. Deploying ML Models with Flask
  6. Advanced-Data Analysis in MS Excel
  7. Data Science with AWS Cloud
  8. Exploring Data Science with Azure

Git for Version Control

  1. Git Basics
  2. Managing Repositories on GitHub
  3. Operations in Git: Commit, Pull, Fetch, Push
  4. Tagging, Branching, and Merging in Git
  5. Undoing Changes in Git
  6. Git Integration with GitHub and Bitbucket

Big Data Fundamentals

  1. Big Data Introduction
  2. Understanding HDFS & MapReduce
  3. PySpark Basics
  4. Integration of Spark SQL and Hadoop Hive
  5. Implementing Machine Learning with Spark ML
  6. Kafka and Spark Exploration

Certified Business Intelligence Analyst

  1. Business Intelligence Introduction
  2. Tableau Basics for Business Intelligence
  3. Connecting Data in Tableau
  4. Insights Generation Using Tableau
  5. Creating Tableau Dashboards, Stories, and Pages
  6. Power BI for Business Intelligence

SQL and MongoDB Database Training

  1. Database Basics
  2. Introduction to SQL for Beginners
  3. Data Types and Constraints in Databases
  4. MySQL Database and Table Management
  5. SQL Joins
  6. Using SQL Commands and Clauses
  7. NoSQL and Document-Oriented Databases

Artificial Intelligence Basics

  1. Artificial Intelligence Overview
  2. Deep Learning Introduction
  3. Basics of TensorFlow
  4. Fundamentals of Computer Vision
  5. Introductory Natural Language Processing (NLP)
  6. Ethical Aspects in AI

DataMites Data Science Course Tools in India

Within the Certified Data Scientist Course in India, we provide in-depth coverage of a diverse set of data science tools. These tools are essential for hands-on applications in data analysis, machine learning, and large-scale data processing. The course encompasses data science tools such as:

  1. Anaconda
  2. Python
  3. Git
  4. Hadoop
  5. MongoDB
  6. Amazon SageMaker
  7. Apache Pyspark
  8. Google Bert
  9. Google Colab
  10. Advanced Excel
  11. Scikit Learn
  12. Azure Machine Learning
  13. Flask
  14. Apache Kafka
  15. GitHub
  16. Numpy
  17. MySQL
  18. TensorFlow
  19. Pandas
  20. Tableau
  21. PyCharm
  22. Atlassian BitBucket
  23. Power BI
  24. Natural Language Toolkit

What Sets DataMites Apart as Your Choice for Data Science Training in India?

Opting for DataMites for data science training in India provides:

Expert Instructors: Taught by industry veterans like Ashok Veda, a renowned AI expert with 19 years of experience, providing students with invaluable insights and practical skills.

Globally Recognized Certifications: DataMites certifications, accredited by IABAC and NASSCOM FutureSkills, boost your professional profile and employability worldwide, showcasing your expertise in data science.

Cutting-Edge Learning Resources: Access to the latest software, modern data science tools, and industry-relevant case studies ensures that students stay up-to-date with current industry trends.

Hands-On Learning: Emphasis on practical, hands-on experience through real-world projects, including 20 capstone projects and a client project, equips students for real data science challenges.

Flexible Learning Options: Choose between online and offline data science training in India, providing flexibility to balance education with personal and professional commitments.

The Importance of Data Science Courses with Internships in India

Data science courses with internships in India are crucial as they offer practical, real-world experience, bridging the gap between academic theories and industry practices. These programs enhance employability by providing hands-on exposure to data analysis, machine learning, and other key areas in a live environment. Internships facilitate networking with professionals and understanding workplace dynamics, vital for budding data scientists. 

DataMites data science courses in India skillfully combine theoretical classroom instruction with essential practical training. This integration is further enhanced by a data science internship certification from a top AI company. This comprehensive approach greatly enhances our students abilities and employment opportunities in the ever-evolving data science sector of India.

The Importance of Data Science Courses with Placement in India

Data science courses with placement in India are pivotal in equipping students with industry-relevant skills, thereby bridging the educational and professional divide. They offer crucial exposure to real-world applications, enhancing job readiness in the rapidly growing field of data science. Additionally, these courses often provide vital networking opportunities and a direct pathway to employment in a competitive job market.

DataMites tackles this need by offering extensive data science courses in India, complete with placement services through our skilled Placement Assistance Team (PAT). Our curriculum is meticulously crafted to ensure students are 'job-ready' in data science, concentrating on both technical prowess and vital soft skills. This approach prepares our graduates to be not only well-informed but also highly sought-after in India's flourishing data science industry.

India, a vibrant and diverse nation, has experienced a significant boom in its Information Technology (IT) sector, becoming a global hub for technological innovation and services. The country's IT industry is renowned for its expertise in software development, outsourcing, and IT-enabled services. 

Among the top companies hiring data scientists in India are Tata Consultancy Services (TCS), Infosys, and Wipro, which are recognized for their cutting-edge work in data analytics, machine learning, and artificial intelligence. These companies not only contribute significantly to India's economy but also play a crucial role in shaping the future of global IT trends. Their demand for skilled data scientists reflects India's growing influence and leadership in the technology sector.

The scope for data scientists in India is rapidly expanding, driven by the country's burgeoning IT sector and digital transformation across various industries. With a growing emphasis on big data, AI, and machine learning, Indian companies across sectors like finance, healthcare, and e-commerce are actively seeking skilled data scientists. This demand is fostering a dynamic job market with lucrative opportunities and a strong focus on innovation. 

Pursuing a career as a data scientist in India offers a promising pathway filled with opportunities for innovation and growth, with average data science salaries ranging from INR13,72,000 per year according to a Glassdoor report, depending on experience and expertise. This field is rapidly evolving, attracting professionals to a landscape where data-driven decision-making is pivotal to business and technological advancements.

DataMites presents an all-encompassing journey for mastering data science in India. Our extensive range of courses extends past the fundamental data science subjects to include data analytics, machine learning, Python coding, AI, MLOps, and data engineering. This well-rounded educational strategy ensures a thorough learning process, preparing you comprehensively to emerge as a proficient data science professional in India.

DESCRIPTION OF DATA SCIENCE COURSE IN INDIA

Data Science is the art of collecting, classifying, summarizing data sets, and deriving valuable insights from these data sets. These insights are used to take further decisions. Data Science has become instrumental in adding value to the business.

There are no mandatory prerequisites. However, basic knowledge of Statistics would be an added advantage.

  • Analytical skills

  • Basic knowledge of Mathematics and Statistics 

  • Knowledge of coding

  • Skills of working with programming languages like ‘R’ and Python.

 

The various business skills required, to become a Data Scientist are as follows:-

  • Industry Knowledge

  • Problem Solving Skills

  • Communication Skills 

  • Curiosity  

Industry Knowledge:- A Data Scientist should have a clear understanding of the areas that need to be paid attention and the areas that need to be ignored. This is possible only if the Data Scientist has sound knowledge of the industry.

Problem Solving Skills:- A Data Scientist is known for finding solutions to problems. For doing so, a Data Scientist must understand the problem, which can be achieved only after a deep study of the scenario.

Communication Skills:- A Data Scientist often needs to communicate the findings arrived at, with regards to analytics and business insights. A Data Scientist should be a good conversationalist. 

Curiosity:- A Data Scientist should always be curious enough while approaching a problem. Finding out the root of the problem depends upon the curiosity of a Data Scientist.

As far as Data Scientist is concerned Python is the most effective programming language, with a lot of libraries available. Python can be deployed at every phase of data science functions. It is beneficial in capturing data and importing it into SQL. Python can also be used to create data sets.

Data Science is all about managing a set of information received from various sources, to arrive at conclusions. The data that is acquired needs to be analysed and decisions need to be taken. Statistics makes it easier to work on data. Various statistical techniques such as Classification, Regression, Hypothesis Testing, Time Series Analysis is used to construct data models. With the help of Statistics, a Data Scientist can gain better insights, which enables to effectively streamline the decision-making process.

  • The different roles, Data Science is subjected to, in an organisation.

  • Analysing and managing projects.

  • Employing various data models.

  • Making use of sampling techniques

  • Prediction and Analysis

  • Segmentation through clustering technique

  • Making use of Linear and Logistics regression methods

The duration of the Data Science course in India is 6 months,  a total of 120 hours of training. The training sessions are provided on weekdays and weekends. You can opt between the two, as per your convenience.

The Data Science course fee in India ranges from Rs 50000 to Rs 150000. DataMites offers three modes of training in India, namely Online, Classroom and Self Learning. Data Science courses in India are offered at an affordable price of Rs 88000 for Online and Classroom sessions and Self Learning at Rs 62000.

Data Science is a vast subject for study, it is a mix of Statistics and Computer Science. DataMites in India, offers quality training sessions in Data Science, Artificial Intelligence, Machine Learning, etc. The data science courses provided by DataMites in India are exclusively designed in tune with the current industry requirements. Also with many projects to work on, under the mentoring of industry experts.

Whether you need a P.G degree to pursue a data science certification can be better understood, based on your knowledge in the Science & Technology, Engineering, and Management domain. If you have a strong knowledge base in any of the mentioned areas.

After completing the  Certified Data Scientist Course in India, an individual will be well equipped with the following:-

  • Intense knowledge of the workflow, of a Data Science project.

  • Learn the basics of the use of Statistics in Data Science.

  • Gain knowledge of the various Machine Learning Algorithms.

  • Knowledge of Data Forecasting, Data Mining, and Data Visualization.

  • Ways to deliver end to end Data Science projects.

India is known for lots of business opportunities and large corporate houses adorning the city. This, in turn, contributes to new employment opportunities being created. Hence opting for a Data Science course in India will help an individual to leverage the available possibilities in the best manner, to land a career in Data Science.

Data Scientists have been in great demand in India. As an acknowledgement to this rising demand, DataMites has come with the Certified Data Scientist course in India. The course covers all the areas of Data Science, Machine Learning, basics of Mathematics and Statistics, etc. Also, the Certified Data Scientist course, covers all the practical aspects of the knowledge required to become a Data Scientist.

India has a lot of opportunities. It consists of large corporates, business houses, with large amounts of transactions happening every day, as a result of which there is an equally large amount of data generated daily. Also, India. is known for many recognised universities. Learning Data Science in India will be a great opportunity for students as well as professionals. Graduates freshers and employees working in organisations can leverage these opportunities to easily land a Data Science job.

India has several large companies, Banking, and Financial institutions, Insurance companies, Automobile companies, Manufacturing enterprises, as a result, India happens to be the most sought after city when it comes to career opportunities in Data Science.

India is a city that is always bustling with business activities, financial transactions happening in huge volumes. Hence it serves to be a great opportunity for starting a Data Science Career in India.

According to the salary estimates shown in Linkedin.com, the average salary of  Data Scientist in India comes upto Rs 900000 per annum.

A large amount of data is being generated through various activities daily. For instance, data of investments done in the stock market, data of the financial transactions, data with regards to the browsing history. The company which you are associated with records and maintains your data. For example, when you make regular online purchases, the provider collects all the information on your activity and stores it securely. It then makes use of the same data to make further product recommendations. Different companies use data in different ways.

  • Small-sized companies employ Google Analytics for analyzing the small size of data.

  • Medium-sized companies have data that will need a Machine Learning Expert to work on it.

  • Big sized companies may need data science professionals who are experts in Machine Learning and Data Visualization.

Data Science is all about the collection and classification of information and using the same to derive insights. Python and R are the two programming languages that are used in the data science process. Some of the reasons, for python being the most preferred programming language in comparison to R:-

  • Easy to learn: Python is easier to understand and master, in comparison to R 

  • Flexible: The flexibility offered by Python offers is better when compared to the R programming language.

  • Availability of libraries: Python has a wide range of libraries available, such as pandas, scikit-learn, etc. This makes it easier in handling machine learning projects.

  • Data visualization: By using matplotlib in Python, you can do the plotting of complex data representations into 2D plots. Data visualization is a significant process in the job of a data scientist. Python can be used for Data Visualisation.

  • Dual Certification

  • Experienced Trainers

  • Industry aligned courses

  • Internship Opportunities

  • Job assistance

The mode of training offered by DataMites for Data Science course in India is online training.

  • Graduate Freshers 

  • Individuals looking to switch their career into Data Science.

  • Professionals who have experience in the Data Science domain.

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FAQ’S OF DATA SCIENCE TRAINING IN INDIA

DataMites provides a range of courses in Data Science, Machine Learning, Artificial Intelligence, with training sessions uncompromised of quality, conducted by industry experts, who possess intense knowledge of the subject matter. DataMites provides 3 different modes of training in India, namely Online, Classroom, and Self Learning. The sessions are conducted by experienced industry professionals.

DataMites is a training provider that imparts quality training and upskilling in Data Science, for freshers who are data enthusiasts and professionals who wish to enhance their career possibilities. Above all DataMites offers the following;-

  • Industry aligned courses 

  • Online sessions that ensure good engagement.

  • Expert Trainers, who possess a vast knowledge of the subject matter.

  • Case studies approach, which delved deep into the practical application of the concepts.

  • Opportunity to get connected with a network of Data Science professionals.

  • Career Guidance

  • Opportunity to work on projects

DataMites has a faculty of trainers who possess deep subject matter expertise and significant years of experience in the field of Data Science.

DataMites offers three modes of training in India, namely Online, Classroom, and Self Learning. Data Science course in India at an affordable price of Rs 88000 for Online and Classroom sessions and Self Learning at Rs 62000.

Enrolling for online training online is very simple. The payment can be done using your debit/credit card that includes Visa Card, MasterCard; American Express or via PayPal. You will receive the receipt after the payment is successful. In case of more queries you can get in touch with our educational educational counselor who will guide you with the same.

DataMites offer various modes of training in India, namely Online, Classroom Self Learning mode.

DataMites offers data science sessions, both on weekdays and weekends. You can opt between the two, based on your convenience.

Yes. DataMites does provide an online lab facility. You can visit prolab.datamites.com. When you visit the site, it asks for the password, you must enter the password given to you, to access the facility.

The data science course offered by DataMites in India includes 25  capstone projects and 1 client project.

DataMites provides Flexi Pass, which gives you the privilege to attend unlimited batches in a year. The Flexi Pass is specific to one particular course. Therefore if you have a Flexi Pass for one particular course of your choice, you will be able to attend any number of sessions of that course. It is to be noted that a Flexi Pass is valid for a particular period.

All the online sessions are recorded and will be shared with the candidates. If you miss any of the online sessions, you can still have access to the recordings later.

Yes. DataMites offers internship opportunities along with the course. You will be mentored by industry experts through the internship. Once the internship is completed, DataMites provides you with the internship certificate along with the experience certificate.

The DataMites Placement Assistance Team(PAT)  helps the candidates to have an easy start in his/her career. The team offers services like Resume Building, Interview Preparation. The team will assist you in the following areas;-

  1. Project Mentoring- 100 hrs Live mentoring in industry projects.

  2. Interview Preparations- Mock Interview sessions.

  3. Resume Support- Personal guidance in resume creation by professionals.

  4. Doubt clearing sessions- Live doubt clearing sessions on 

  5. Job updates- Interview connects.

The registrations cancelled within 48 hrs of enrollment will be refunded in full. The processing time of the refund is within 30 days, from the date of the receipt of  cancellation request.

Yes. You will receive a certificate from DataMites after the completion of the course.

DataMites in India offers dual certifications in collaboration with IABAC and IBM for courses in Data Science, Artificial Intelligence and Machine Learning. IABAC is a global body, which offers certifications in Business Analytics and Data Science. IABAC is founded on the principles of EDISON Data Science Framework (EDSF). IBM provides the best in class industry certifications.  Machine Learning, Artificial Intelligence. All the data science certifications offered by DataMites are structured based on the industry trends.

You have access to the online study materials from 6 months upto 1 year.

DataMites offers data science sessions, in the Morning and Evening. You can opt, based on your convenience.

Yes. DataMites do provide live data science projects, which are done under the guidance of industry experts.

The training sessions provided by DataMites in India are primarily online. However, classroom training can be made available if there is adequate demand.

DataMites is a training provider that imparts quality training and upskilling in Data Science, for freshers who are data enthusiasts and professionals who wish to enhance their career possibilities. Above all DataMites offers the following;-

  • Industry aligned courses 

  • Online sessions that ensure good engagement.

  • Expert Trainers, who possess a vast knowledge of the subject matter.

  • Case studies approach, which delved deep into the practical application of the concepts.

  • Opportunity to get connected with a network of Data Science professionals.

  • Career Guidance

  • Opportunity to work on projects

DataMites accepts all the online payments(Debit/Credit) through Razor pay. If you opt to pay through your credit card there will be an EMI option. DataMites collects token advance during the time of registration and the remaining payment should be settled in full before the completion of the course.

Yes. The Datamites certification exam fee is included in the total course fee. Therefore once you are registered for a course, you are also eligible to attend the exam.

No, DataMites doesn’t guarantee a job, but it will provide all the support and guidance needed, in getting a job, Resume Building, Interview preparations. DataMites internships offer a candidate to work with industry experts, which helps in knowing the corporate way of working. This proves as a stepping stone to an individual’s professional life.

DataMites internship programs are exclusively designed for a candidate to enable him/her to get a practical experience of working on live projects. The candidate gets an opportunity to work under the guidance of industry experts.

DataMites provides data science classroom training in Bangalore, Chennai, Hyderabad, and Pune. For other Indian cities, classroom training can be made available if there is adequate demand for the same.

The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -

  • 1. Job connect
  • 2. Resume Building
  • 3. Mock interview with industry experts
  • 4. Interview questions

The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.

No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.

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