DATA SCIENCE CERTIFICATION AUTHORITIES

Data Science Course Features

DATA SCIENCE COURSE LEAD MENTORS

DATA SCIENCE COURSE FEE IN PUNE

Live Virtual

Instructor Led Live Online

110,000
65,455

  • 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
39,805

  • 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
74,955

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

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UPCOMING DATA SCIENCE ONLINE CLASSES IN PUNE

UPCOMING DATA SCIENCE CLASSROOM CLASSES IN PUNE

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 PUNE

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 PUNE

DATA SCIENCE COURSE REVIEWS

ABOUT DATA SCIENTIST TRAINING IN PUNE

In today's rapidly advancing tech world, data science is a key driver of innovation and business intelligence. The global data science platform market, poised for exceptional growth, is projected to surge from $81.47 billion in 2022 to $484.17 billion by 2029, with a CAGR of 29.0%. (Fortune Business Insights) highlighting the increasing relevance of data science across industries. DataMites delivers immersive offline data science courses in Pune, complete with practical internships and assistance in job placements, fostering a new generation of talented data science specialists.

DataMites, a globally recognized institute, excels in providing comprehensive data scientist training in Pune. The Certified Data Scientist Course, intended for both newcomers and those at an intermediate level, is structured to create a strong base in data science. It integrates important elements such as statistics, mathematics, Python, and machine learning, equipping learners with the all-around skills and knowledge vital for excelling in the dynamic world of data science.

Innovative 3-Phase Learning Methodology at DataMites 

At DataMites, we believe in a structured yet flexible learning approach, encapsulated in our unique 3-Phase Learning Methodology:

Phase 1 - Pre-Course Self-Study: We provide high-quality video materials that lay a solid foundation in data science, enabling students to start their journey with confidence.

Phase 2 - Immersive Training: This phase offers a choice between live online data science training in Pune and data science classroom training in Pune. It involves 20 hours of training per week over a three-month period, featuring a comprehensive syllabus, practical hands-on projects, and mentorship from expert trainers.

Phase 3 - Internship & Placement Assistance: This crucial phase involves participation in 20 Capstone Projects and a client project, culminating in a prestigious internship certification. The program's Placement Assistance Team (PAT) offers comprehensive career advice and support, ensuring effective career preparation. Our data science training with placement in Pune is geared towards practical application, focusing on job readiness to facilitate a smooth transition into the fields of AI and data science.

Other Top Data Science Certifications Offered by DataMites 

DataMites takes pride in offering some of the most sought-after data science certifications in Pune. These include:

Data Science for Managers: Learn to leverage data science for strategic decision-making, essential for managers leading data-driven initiatives.

Python for Data Science: Dive into Python's applications in data science, covering its libraries and tools for data analysis and machine learning.

Data Science in Marketing: Explore data-driven marketing strategies and learn to apply analytics for customer insights and campaign optimization.

Data Science with R: Focus on R for statistical analysis and data visualization, ideal for data analysts and statisticians.

Data Science in Operations: Apply data science to optimize processes and supply chain management, crucial for operations professionals.

Data Science in Finance: Tailored for finance professionals, this course covers predictive analytics and quantitative analysis for financial decision-making.

Data Science in HR: Merge data science with HR to harness data for talent management, performance analysis, and strategic HR decisions.

Data Science Associate: A beginner's guide to data science basics, perfect as an introductory course for newcomers.

Diploma in Data Science: An extensive program for in-depth knowledge and skills in data science, preparing for advanced industry roles.

Each certification is tailored to meet specific data science career goals and industry requirements, ensuring our students receive the best possible training to advance their careers.

DataMites’ Comprehensive Data Science Course Curriculum in Pune

DataMites' Certified Data Scientist Course in Pune provides an expansive and detailed curriculum, expertly structured to cover a broad spectrum of subjects in the data science domain. This thorough training is segmented into 9 distinct modules, each dedicated to a specific area of data science, ensuring a comprehensive educational journey.

  1. Python Essentials

  • Fundamentals of Python

  • Conditional Statements in Python

  • Data Structures in Python

  • Functions in Python

  • Introduction to Python's Numpy

  • Working with Python's Pandas

  • Foundations of Data Science

  1. Data Science Foundation

  • Basics of Data Engineering

  • Python Application in Data Science

  • Data Visualization using Python

  • Fundamentals of R Programming

  • Statistical Analysis

  • Overview of Machine Learning

  • Expertise in Machine Learning

  1. Machine Learning Expert

  • Machine Learning with Linear Regression

  • Logistic Regression in ML

  • K-Nearest Neighbors (Knn) Algorithm

  • K-Means Clustering Technique

  • Basics of Principle Component Analysis (PCA)

  • Decision Tree Algorithm

  • Understanding Naïve Bayes

  • Techniques in Gradient Boosting & Xgboost

  • Support Vector Machine (SVM) in ML

  • Fundamentals of Artificial Neural Networks (ANN)

  • Advanced Machine Learning Concepts

  1. Advanced Topics in Data Science

  • ARIMA for Time Series Forecasting

  • The Art of Feature Engineering

  • Techniques in Sentiment Analysis

  • Regular Expressions in Python

  • Deploying ML Models with Flask

  • Advanced Data Analysis using MS Excel

  • Utilizing AWS Cloud in Data Science

  • Data Science with Azure

  1. Version Control Using Git

  • Introduction to Git

  • Managing Git Repositories and GitHub

  • Operations: Commits, Pull, Fetch, Push

  • Git Operations: Tagging, Branching, Merging

  • Reverting Changes in Git

  • Integrating Git with GitHub and Bitbucket

  1. Foundations of Big Data

  • Introduction to Big Data

  • Understanding HDFS and MapReduce

  • Foundations of PySpark

  • Spark SQL and Integration with Hadoop Hive

  • Machine Learning with Spark ML

  • Kafka Integration with Spark

  1. Certified BI Analyst

  • Introduction to Business Intelligence

  • Getting Started with BI using Tableau

  • Connecting Data Sources with Tableau

  • Generating Business Insights with Tableau

  • Creating Dashboards, Stories, and Pages in Tableau

  • Business Intelligence with Power BI

  1. Databases: SQL and MongoDB

  • Introduction to Databases

  • Basics of SQL

  • Data Types and Constraints in SQL

  • Working with Databases and Tables in MySQL

  • SQL Joins

  • Various SQL Commands and Clauses

  • Fundamentals of Document DB/NoSQL DB

      Introduction to Artificial Intelligence

  • Overview of Artificial Intelligence

  • Introduction to Deep Learning

  • Basics of Tensorflow

  • An Introduction to Computer Vision

  • Fundamentals of Natural Language Processing (NLP)

  • Ethical Issues and Concerns in AI

DataMites Data Science Course Tools in Pune

In our Certified Data Scientist Training in Pune, we place a strong emphasis on practical skills and hands-on experience with a variety of tools essential in the field of data science. Our curriculum is designed to familiarize you with the most widely used and industry-relevant tools, ensuring you are well-equipped for real-world data science challenges. Here is a snapshot of the key data science tools that you will master during the course:

  • Flask

  • Anaconda

  • Python

  • Apache Pyspark

  • Git

  • Hadoop

  • Amazon SageMaker

  • Google Bert

  • Google Colab

  • Advanced Excel

  • Scikit Learn

  • MySQL

  • Azure Machine Learning

  • Apache Kafka

  • GitHub

  • Numpy

  • TensorFlow

  • Pandas

  • Tableau

  • Atlassian BitBucket

  • Power BI

  • Natural Language Toolkit

  • PyCharm

  • MongoDB

Why DataMites is the Go-To Institute for Data Science Training in Pune

  • Learning from expert faculty, including the globally reputed AI expert Ashok Veda.

  • Gaining internationally recognized certifications from IABAC and NASSCOM FutureSkills.

  • Accessing cutting-edge learning resources.

  • Engaging in 20 capstone and one client project for hands-on experience.

  • Benefiting from flexible learning options, with data science course online in Pune and data science offline training in Pune's Baner and Kharadi areas.

From Classroom to Career: The Value of Data Science Internships

Data science internships in Pune play a crucial role in bridging the gap between academic learning and real-world application, offering hands-on experience and exposure to practical challenges. DataMites' data science courses with internship in Pune, providing a valuable opportunity for students to apply theoretical knowledge in professional settings. 

Additionally, these courses are accompanied by a data science certification from a renowned AI company, further enhancing the practical skills and industry readiness of the participants. This combination of data science internship certification from a leading AI firm is instrumental in shaping proficient data science professionals.

From Learning to Leading: The Essential Role of Data Science Placement

Understanding the importance of placement support in the challenging job market of Pune, especially in the field of data science, DataMites has taken a significant step. We provide extensive data science courses with placement in Pune, facilitated by our dedicated Placement Assistance Team (PAT). 

These courses are designed as a comprehensive 'data science job ready' program, emphasizing both technical prowess and crucial soft skills development. This well-rounded training equips our graduates to be highly competitive and desirable candidates in the rapidly growing data science sector in Pune.

Why pursue a career in data science in Pune? 

Pune, Maharashtra's educational and cultural heart, is emerging as a key player in India's IT and tech sector. This city, where traditional culture meets modern technology, is attracting IT professionals and businesses alike. With its advanced infrastructure, skilled talent from numerous educational institutions, and supportive government initiatives, Pune is quickly becoming a prominent IT and data science hub.

The job market in Pune is vibrant, with increasing demand for various data science roles. Key positions include Data Scientist, Data Analyst, Machine Learning Engineer, and Business Intelligence Analyst. Other sought-after data science job roles in Pune are Data Engineer, Statistician, Data Science Consultant, Quantitative Analyst, AI Research Scientist, and Big Data Engineer, offering competitive salaries and opportunities for growth in Pune's evolving IT and tech sector.

Pune is emerging as a fertile ground for budding data scientists, offering a thriving career landscape. LinkedIn's listing of over 8,000 data science job opportunities in Pune underscoring the city's strong demand for data science expertise. Although the national average salary for data scientists in India is around INR ?12,00,000, data scientists salary in Pune's average of INR ?10,63,921 per year positions it as a competitive market for data science careers. (Glassdoor)

DataMites data science institute in Pune is your ideal choice for learning data science. Our hands-on learning approach prepares you for real-world data science challenges. The institute also provides a variety of courses such as data analytics, machine learning, Python programming, Artificial Intelligence, MLOps, and data engineering. These courses are designed to meet the dynamic demands of the industry, setting you on the path to a successful data science career

DESCRIPTION OF DATA SCIENCE COURSE IN PUNE

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 Pune 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.

DataMites offers the online Data Science course in Pune at Rs 88000

Data Science is a vast subject for study, it is a mix of Statistics and Computer Science. DataMites in Pune, offers quality training sessions in Data Science, Artificial Intelligence, Machine Learning etc. The data science courses provided by DataMites in Pune 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 Pune, 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.

Pune is known for with 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 Pune 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 Pune. As an acknowledgement to this rising demand, DataMites has come with the Certified Data Scientist course in Pune. 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. 

Pune, in India, has lots of business opportunities. It consists of many large companies, 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. 

 

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

 

Pune 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 Pune.

As per the reports published by Indeed.com, the average salary of Data Scientists in Pune is ₹ 7,75,483 annually. 

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. 

 

  • Globally Recognised Certification

  • Experienced Trainers

  • Industry aligned courses

  • Internship Opportunities

  • Job assistance

The mode of training offered by DataMites for Data Science course in Pune 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 PUNE

DataMites in Pune provides a range of courses in Data Science, Machine Learning, Artificial Intelligence,in Chennai with training sessions uncompromised of quality, conducted by industry experts, professional data scientists who possess intense knowledge of the subject matter. The training is conducted in the online mode. The sessions are conducted based on case studies approach, with business cases taken up for discussion.

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.

The Data Science course fee in India ranges from Rs 50000 to Rs 150000. DataMites offers three modes of training in Pune, 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.

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 Pune offers globally recognised certifications in collaboration with IABAC 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). Machine Learning, Artificial Intelligence. All the data science certifications offered by DataMites are structured based on the industry trends.

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 counselor who will guide you with the same.

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

DataMites offer three various modes of  training in Pune, 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.

DataMites offers data science sessions, in the Morning and Evening. You can opt, 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.

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

The data science course offered by DataMites in Pune includes 20 capstone projects and 3 client projects.

The training sessions provided by DataMites in Pune 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 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.

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. 

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. 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.

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 will assist you in the following areas;-

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

  • Interview Preparations- Mock Interview sessions.

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

  • Doubt clearing sessions- Live doubt clearing sessions on 

  • Job updates- Interview connects.

 

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.

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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