DATA SCIENCE CERTIFICATION AUTHORITIES

Data Science Course Features

DATA SCIENCE COURSE LEAD MENTORS

DATA SCIENCE COURSE FEE IN HYDERABAD

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 ONLINE CLASSES IN HYDERABAD

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 HYDERABAD

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 HYDERABAD

DATA SCIENCE COURSE REVIEWS

ABOUT DATA SCIENTIST TRAINING IN HYDERABAD

In the rapidly advancing technological landscape, data science emerges as a key innovator and driver of business intelligence. With the global data science platforms market expected to reach USD 501.03 billion by 2032, growing at a 16.2% CAGR, Hyderabad positions itself as a central hub in this growth. DataMites offers comprehensive offline training in data science in Hyderabad, complemented by internships and career placement opportunities, nurturing the next generation of skilled data science practitioners.

DataMites, as a globally renowned institute, offers a comprehensive suite of data science courses in Hyderabad. Designed for both novice and intermediate students, the Certified Data Scientist Course lays a solid groundwork in data science through key topics like statistics, mathematics, python, and machine learning. Its goal is to furnish learners with a comprehensive skillset for success in the rapidly changing data science sector.

Innovative 3-Phase Learning Methodology at DataMites 
DataMites embraces a unique and structured 3-Phase Learning Methodology to ensure comprehensive education in data science:

Phase 1 - Pre-Course Self-Study: Students begin their journey with access to high-quality videos, laying a solid foundational understanding of key concepts.

Phase 2 - Immersive Training: This phase offers options for live online data science training in Hyderabad or in-person data science classroom training in Hyderabad. It includes 20 hours of weekly training for three months, featuring an extensive syllabus, practical hands-on projects, and mentorship from experienced trainers.

Phase 3 - Internship and Placement Assistance: This vital stage involves engaging in 20 capstone projects and a client project, leading to an esteemed internship certification. The Placement Assistance Team (PAT) in our data science program offers extensive career support and advice. The data science training with placement emphasizes practical skills through its job-ready focus, equipping students to seamlessly transition into AI and data science careers.

The Rising Demand for Data Scientists

The burgeoning field of data science offers lucrative opportunities, with soaring demand for skilled professionals capable of extracting meaningful insights from complex data. In Hyderabad, the need for data scientists is particularly pronounced due to the city's robust IT sector. DataMites’ data science training in Hyderabad are meticulously designed to prepare students for these promising roles, ensuring not just theoretical knowledge but also industry readiness.

DataMites Other Top Certifications in Data Science

DataMites proudly offers some of the most sought-after data science certifications in Hyderabad;

Statistics for Data Science: This course emphasizes the crucial statistical techniques and tools necessary for data analysis in Data Science.

Data Science for Managers: Specifically designed for managers, it addresses the strategic use of Data Science in business decision-making.

Python for Data Science: Focuses on utilizing Python, a vital programming language, for diverse Data Science tasks.

Data Science Foundation: An all-encompassing beginner's course establishing the basic principles of Data Science.

Data Science in Marketing: Offers specialized training in the application of Data Science for marketing strategy and decision-making.

Data Science with R: Aims to teach the application of R programming for data analysis and statistical modeling in Data Science.

Data Science in Operations: Teaches the application of data science in improving operational efficiency, supply chain management, and industry processes.

Data Science in Finance:  Provides insights into financial data analysis and risk management, teaching skills for data-informed financial decision-making.

Data Science in HR: Merges data science with human resources, focusing on data-driven strategies for talent and workforce management.

Data Science Associate: Gives a basic yet thorough understanding of data science, suitable for beginners eyeing data analysis roles.

Diploma in Data Science: This comprehensive program covers data analysis, machine learning, and visualization, preparing you for advanced data science roles.

Each of these certifications is tailored to specific career goals and industry requirements, guaranteeing our students the best possible training to advance their data science careers in Hyderabad.

DataMites’ Data Science Course Curriculum in Hyderabad

DataMites' Certified Data Scientist Course in Hyderabad is structured into a detailed curriculum, thoughtfully created to cover a broad spectrum of subjects in data science. This extensive training is segmented into 9 focused modules, each targeting a specific area of data science to ensure an all-encompassing educational experience.

Python Foundation

- Fundamentals of Python
- Control Structures in Python
- Data Structures in Python
- Function Implementation in Python
- Utilizing Python's Numpy Library
- Working with Python's Pandas Library

Data Science Foundations

- Core Principles of Data Science
- Basics of Data Engineering
- Python Applications in Data Science
- Data Visualization Using Python
- Fundamentals of R Programming
- Statistical Methods
- Introduction to Machine Learning

Machine Learning Expert

- Overview of Machine Learning
- Linear Regression Techniques
- Logistic Regression Methods
- K-Nearest Neighbors (Knn)
- K Means Clustering Approach
- Introduction to Principal Component Analysis (PCA)
- Decision Tree Algorithms
- Fundamentals of Naïve Bayes
- Understanding Gradient Boosting and Xgboost
- Support Vector Machine (SVM) Strategies
- Basics of Artificial Neural Networks (ANN)
- Advanced Machine Learning Concepts

Advanced Data Science

- ARIMA for Time Series Forecasting
- Techniques in Feature Engineering
- Analyzing Sentiments
- Python Regular Expressions
- Deploying ML Models Using Flask
- Enhanced Data Analysis with MS Excel
- Utilizing AWS Cloud in Data Science
- Data Science Applications with Azure

Version Control With Git

- Introduction to Git
- Managing Git Repositories and GitHub
- Operations: Commits, Pull, Fetch, Push
- Git Operations: Tagging, Branching, Merging
- Reversing Changes in Git
- Integrating Git with GitHub and Bitbucket

Big Data Foundation

- Introduction to Big Data
- Basics of HDFS and MapReduce
- Foundation of PySpark
- Spark SQL and Hadoop Hive
- Machine Learning with Spark ML
- Exploring Kafka and Spark

Certified BI Analyst

- Introduction to Business Intelligence
- Getting Started with BI using Tableau
- Connecting Data Sources in Tableau
- Gaining Business Insights with Tableau
- Creating Dashboards, Stories, and Pages in Tableau
- Business Intelligence with Power BI

Database: SQL and MongoDB

- Overview of Databases
- Basic SQL Techniques
- Data Types and Constraints in SQL
- Managing Databases and Tables in MySQL
- SQL Join Operations
- Key SQL Commands and Clauses
- Understanding Document DB/NoSQL DB

Artificial Intelligence Foundation

- Overview of Artificial Intelligence
- Introduction to Deep Learning
- TensorFlow Basics
- Fundamentals of Computer Vision
- An Introduction to Natural Language Processing (NLP)
- Ethical Issues and Concerns in AI

Our Certified Data Scientist Course in Hyderabad has a syllabus covering an extensive range of topics, including Python Foundation, Data Science Foundation, Machine Learning Expertise, Advanced Data Science, and more. 

DataMites Data Science Course Tools in Hyderabad

In the Certified Data Scientist Course in Hyderabad, participants gain hands-on experience with a wide range of essential data science tools. These tools are integral for various aspects of data analysis, machine learning, and data management. The course covers the following tools:

  • Google Colab
  • Anaconda
  • Python
  • Apache Pyspark
  • Git
  • Hadoop
  • MongoDB
  • Amazon SageMaker
  • Apache Kafka
  • Google Bert
  • Advanced Excel
  • Scikit Learn
  • MySQL
  • Azure Machine Learning
  • Flask
  • Numpy
  • TensorFlow
  • Pandas
  • Tableau
  • Atlassian BitBucket
  • Power BI
  • Natural Language Toolkit
  • PyCharm
  • GitHub

Why DataMites is the Best Choice for Data Science Courses in Hyderabad;

Choosing DataMites in Hyderabad for data science education means:

  • Learning from expert faculty, including globally renowned AI expert Ashok Veda.
  • Gaining internationally recognized certifications like IABAC and NASSCOM FutureSkills.
  • Accessing cutting-edge learning resources.
  • Engaging in 20 capstone and one client project for hands-on experience.
  • Enjoying flexible learning options with data science training online in Hyderabad and data science classroom training Hyderabad in the prominent city of Madhapur.

The Crucial Role of Internships with Data Science Course

Internships in data science in Hyderabad are key to translating academic concepts into practical skills, offering crucial experience in applying data science in real-world scenarios. Such internships are vital for practical skill acquisition and gaining insights into industry practices.

At DataMites, we integrate data science courses with internships in Hyderabad, ensuring that students gain a comprehensive mix of theoretical knowledge and essential hands-on experience. This combination of academic learning and practical exposure, augmented by a data science internship certification from a renowned AI company, effectively enhances the skillset and job market readiness of students in the vibrant data science landscape of Hyderabad.

The Crucial Role of Data Science Course with Placement 

In the competitive landscape of Hyderabad's job market, especially in data science, the transition from academic learning to a professional career is a critical phase. Ensuring this shift is smooth and effective, 'data science job ready' becomes essential, equipping graduates with the necessary skills and knowledge to thrive in this challenging field.

DataMites caters to this necessity by offering robust data science courses with placement in Hyderabad, managed by our specialized Placement Assistance Team (PAT). Our curriculum is not just focused on imparting technical knowledge; it also includes a vital emphasis on soft skills, preparing our graduates comprehensively for the dynamic demands of Hyderabad's data science job market.

Hyderabad, known as the "City of Pearls," has become a key player in India's tech sector, especially in IT and data science. Merging its historical heritage with modern tech, it's now a top choice for IT professionals and companies. The city boasts excellent technological infrastructure, a skilled workforce from top universities, and government support, marking it as a leading IT and data science hub.

In Hyderabad, the data science job market is flourishing, offering data science job roles in Hyderabad like Data Scientist, Data Analyst, and Machine Learning Engineer. Other prominent positions include Business Intelligence Analyst, Data Engineer, Statistician, and Data Science Consultant. These roles are renowned for their competitive salaries and career growth opportunities in the city's dynamic IT industry.

Hyderabad presents a fertile ground for data science professionals, with LinkedIn listing over 11,000+ data scientists job openings in Hyderabad. This reflects the city's growing need for expertise in this dynamic sector. While the average data science salary in India is around INR ?12,00,000, data scientists salary in Hyderabad offers a more competitive average of INR ?13,30,549 per year. (Glassdoor) This salary benchmark highlights Hyderabad's position as a strong and attractive market for careers in data science.

DataMites in Hyderabad offers an extensive gateway into the world of data science. Our data scientist training in Hyderabad, led by expert faculty and a hands-on approach, lays the groundwork for a thriving career in data science. The institute also offers various courses tailored to industry needs, including data analytics, python, Artificial Intellignece, MLOps, machine learning and data engineering. These programs are crafted to align with current industry trends, ensuring up-to-date skills and knowledge.

Enroll with us to commence your journey into data science, and equip yourself with the skills necessary for a thriving career in this rapidly evolving industry.

 

DESCRIPTION OF DATA SCIENCE COURSE IN HYDERABAD

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 Hyderabad is 8 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 Hyderabad, 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 Hyderabad, offers quality training sessions in Data Science, Artificial Intelligence, Machine Learning etc. The data science courses provided by DataMites in Hyderabad 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 Hyderabad, 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.

Hyderabad is one of the technological hubs of India,  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 Hyderabad 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 Hyderabad. As an acknowledgement to this rising demand, DataMites has come with the Certified Data Scientist course in Hyderabad. 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. 

Hyderabad, in India, is one of the technological hubs of India, with a lot 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. 

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

Hyderabad 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 Hyderabad.

As per the reports published by Indeed.com, the average salary of Data Scientists in Hyderabad is ₹ 7,04,064 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

Enrolling in online training online is very simple. The payment can be done using your debit/credit card that includes Visa Card, MasterCard; American Express, or PayPal. You will receive the receipt after the payment is successful. You can get in touch with our educational counsellor for more information.

  • Graduate Freshers 

  • Individuals looking to switch their career into Data Science.

  • Professionals who have experience in the Data Science domain

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 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;-

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.

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FAQ’S OF DATA SCIENCE TRAINING IN HYDERABAD

DataMites in Hyderabad 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.

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 Hyderabad 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

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 Hyderabad, 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.

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, in order 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 Hyderabad includes 20 capstone projects and 3 client projects.

The training sessions provided by DataMites in Hyderabad 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.

 

DataMites in Hyderabad offers  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.

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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