🔥 Next Batch starts on 18th Oct 2026
Why Choose Linkplux?

Industry-Ready Data Science
Training in Hyderabad

Linkplux delivers career-oriented learning with modern data science tools and methodologies. Our Data Science course emphasizes practical assignments, business datasets, and mentor support to strengthen analytical thinking and equip learners for data-focused roles.

Work on Real Datasets
Python, SQL & Analytics
Job Assistance
Data Science Training in Hyderabad
Build Industry Portfolio
Guidance from Professionals
Course Completion Certificate
Premium Features

Course Highlights

Practical Data Science Learning

Develop applied knowledge through industry datasets, assignments, case studies, and practical exercises covering essential data science processes.

Machine Learning & AI Concepts

Understand ML techniques, AI fundamentals, predictive analysis, model evaluation, and current approaches for creating data-driven applications.

Professional Course Certification

Enhance your credentials with a Data Science certificate that validates your understanding of programming, analytics, and data interpretation.

Career Guidance & Support

Get ready for data-driven roles through CV assistance, placement support, interview preparation, industry insights, and career-focused mentoring.

Industry-Based Data Projects

Work with Python, SQL, statistics, visualization, and data analytics through projects designed around practical business scenarios and relevant datasets.

Mentor-Guided Training

Gain knowledge from skilled instructors through focused sessions on Python development, statistical analysis, machine learning, and data modelling methods.

Data Analytics Portfolio

Build a compelling project portfolio featuring dashboards, analytical reports, ML solutions, and capstone assignments for showcasing your skills.

Technical Interview Training

Strengthen interview readiness with technical questions, mock interviews, analytical challenges, and problem-solving practice for data-focused positions.

Roadmap

How You'll Learn

Psychometric Assessment
Technical Skill Development
20% Theory
Communication Skill Development
80% Practical
Aptitude Skill Development
Webinars/Seminars by Experts
Learning Management System
Discussion Forum
Work on Live Projects
Placement Training
Resume Building
Interview Prep
Assessment MCQs
Mock Interviews
Portfolio Building
Certification
Curriculum

Syllabus Of Data Science Course

Paper 1: Python & Data Science Foundations

  • Unit 1: Python Syntax, Variables, Data Types and Operators
  • Unit 2: Conditions, Loops, Functions and Exception Handling
  • Unit 3: Lists, Tuples, Sets, Dictionaries and Comprehensions
  • Unit 4: Object-Oriented Programming, Modules and File Handling
  • Unit 5: Jupyter Notebook, Git Basics and Python for Analytics

Tools used in this Paper: Python, Jupyter, GitHub Copilot, ChatGPT

Paper 2: Statistics, Probability & Mathematics

  • Unit 1: Descriptive Statistics, Central Tendency and Dispersion
  • Unit 2: Probability Rules, Random Variables and Distributions
  • Unit 3: Sampling, Confidence Intervals and Hypothesis Testing
  • Unit 4: Correlation, Covariance and Regression Concepts
  • Unit 5: A/B Testing, ANOVA and Statistical Decision Making

Tools used in this Paper: Python, NumPy, SciPy, Jupyter

Paper 3: SQL, Data Management & Analytics

  • Unit 1: Relational Databases, Tables, Keys and Data Modelling
  • Unit 2: SQL Queries, Joins, Aggregations and Subqueries
  • Unit 3: CTEs, Window Functions, Views and Query Optimisation
  • Unit 4: Data Cleaning, Transformation and Analytical Queries
  • Unit 5: Data Warehousing, ETL Concepts and Modern Data Platforms

Tools used in this Paper: MySQL, PostgreSQL, BigQuery, ChatGPT

Paper 4: Data Wrangling, EDA & Visualization

  • Unit 1: NumPy Arrays, Vectorization and Numerical Operations
  • Unit 2: Pandas DataFrames, Filtering and Data Transformation
  • Unit 3: Missing Values, Duplicates, Outliers and Data Quality
  • Unit 4: Exploratory Analysis using Matplotlib, Seaborn and Plotly
  • Unit 5: Power BI, Dashboards, Data Storytelling and Business Insights

Tools used in this Paper: NumPy, Pandas, Matplotlib, Seaborn, Power BI

Paper 5: Machine Learning & Predictive Modelling

  • Unit 1: ML Workflow, Preprocessing and Feature Engineering
  • Unit 2: Linear Regression, Logistic Regression and Regularisation
  • Unit 3: KNN, Naive Bayes, SVM and Classification Methods
  • Unit 4: Decision Trees, Random Forests and Ensemble Learning
  • Unit 5: Metrics, Cross-Validation, Hyperparameter Tuning and Model Selection

Tools used in this Paper: Scikit-learn, Pandas, NumPy, MLflow

Paper 6: Advanced Machine Learning & Time Series

  • Unit 1: XGBoost, LightGBM, CatBoost and Gradient Boosting
  • Unit 2: K-Means, Hierarchical Clustering and DBSCAN
  • Unit 3: PCA, Feature Selection and Dimensionality Reduction
  • Unit 4: Time Series, Forecasting, Seasonality and Anomaly Detection
  • Unit 5: SHAP, Explainable AI and Responsible Machine Learning

Tools used in this Paper: XGBoost, LightGBM, CatBoost, SHAP, Python

Paper 7: Deep Learning, NLP & Generative AI

  • Unit 1: Neural Networks, Activation Functions, Backpropagation and Optimisation
  • Unit 2: TensorFlow, Keras and Deep Learning Model Development
  • Unit 3: NLP, Text Processing, Embeddings and Sentiment Analysis
  • Unit 4: Transformers, LLMs, Prompt Engineering and Foundation Models
  • Unit 5: RAG, Vector Databases, AI Agents and Responsible AI

Tools used in this Paper: TensorFlow, Keras, Hugging Face, LangChain, ChatGPT

Paper 8: MLOps, Cloud & Model Deployment

  • Unit 1: Flask, FastAPI, Streamlit and Machine Learning APIs
  • Unit 2: Git, GitHub, Docker and Reproducible ML Workflows
  • Unit 3: MLflow, Experiment Tracking, Model Registry and Monitoring
  • Unit 4: AWS, Azure, Google Cloud and Production Deployment
  • Unit 5: CI/CD, Model Serving, Monitoring and Scalable AI Systems

Tools used in this Paper: Docker, MLflow, GitHub, AWS, Azure, Google Cloud

Paper 9: Capstone Projects & Career Preparation

  • Unit 1: Business Problem Definition, Dataset Selection and Project Planning
  • Unit 2: End-to-End Data Preparation, Analysis and Model Development
  • Unit 3: Dashboard Design, Model Interpretation and Insight Presentation
  • Unit 4: Deployment, Documentation, GitHub Portfolio and Case Study
  • Unit 5: Resume Building, Mock Interviews and Data Science Career Readiness

Tools used in this Paper: GitHub, Streamlit, Power BI, ChatGPT, Gemini

Let's Get Started

Skills Covered

Python
NumPy
Pandas
Jupyter Notebook
SQL
Scikit-learn
Data Cleaning
Exploratory Data Analysis
Feature Engineering
Descriptive Statistics
Probability
Statistical Inference
Hypothesis Testing
Regression Analysis
Correlation
Supervised Learning
Decision Trees
Random Forest
SVM
K-Means Clustering
XGBoost
Hyperparameter Tuning
Model Evaluation
Neural Networks
CNN
RNN & LSTM
TensorFlow
Keras
NLP
Matplotlib
Seaborn
Plotly
Tableau
Interactive Dashboards
Data Storytelling
Generative AI
Prompt Engineering
Large Language Models
RAG Applications
Docker
Git & GitHub
MLflow
Cloud Deployment
Industry Tools

AI-Powered Data Science Tools You'll Master in Chennai

Python & Data Science Tools "Work with Industry-Standard Tools for Data Analysis, Programming & AI-Assisted Data Science Workflows"

Python Data Science Tool
PythonData Science Programming
Jupyter Notebook Data Science Tool
Jupyter NotebookInteractive Data Analysis
NumPy Data Science Tool
NumPyNumerical Computing
Pandas Data Analysis Tool
PandasData Manipulation
Google Colab Data Science Tool
Google ColabCloud Data Analysis
ChatGPT Data Science Tool
ChatGPTAI-Assisted Data Analysis
Google Gemini Data Science Tool
Google GeminiAI Research & Analysis
GitHub Copilot Data Science Tool
GitHub CopilotAI Coding Assistance

SQL & Database Tools "Use Popular Database Platforms and Query Tools for Efficient Data Storage, Retrieval & Management"

MySQL Data Science Tool
MySQLRelational Database
PostgreSQL Data Science Tool
PostgreSQLAdvanced Database
SQLite Data Science Tool
SQLiteLightweight Database
SQLData Querying
Database ToolsData Management
SQL WorkbenchDatabase Querying

Machine Learning Tools "Gain Hands-On Experience with Widely Used Libraries for Building, Evaluating & Optimising Machine Learning Models"

Scikit-learn Data Science Tool
Scikit-learnMachine Learning Library
XGBoost Machine Learning Tool
XGBoostGradient Boosting
SciPy Data Science Tool
SciPyScientific Computing
Model EvaluationML Performance Analysis
Hyperparameter TuningModel Optimisation
Feature EngineeringFeature Preparation

Deep Learning & AI Tools "Explore Modern Frameworks for Neural Networks, Artificial Intelligence, Natural Language Processing & Computer Vision"

TensorFlow Data Science Tool
TensorFlowDeep Learning Framework
PyTorch Data Science Tool
PyTorchAI Model Development
Keras Deep Learning Tool
KerasNeural Network API
OpenCV Data Science Tool
OpenCVComputer Vision Library
Hugging Face AI Tool
Hugging FaceNLP & AI Models
NLP ToolsLanguage Data Processing

Generative AI Tools "Use Leading AI Platforms and Frameworks to Enhance Research, Coding, Automation & Data Science Workflows"

ChatGPT Generative AI Tool
ChatGPTGenerative AI Assistant
Google Gemini AI Tool
GeminiMultimodal AI Platform
LangChain AI Development Tool
LangChainLLM Development
OpenAI Data Science AI Tool
OpenAIAI & LLM Platform
Prompt ToolsAI Interaction
Vector DatabasesAI Data Retrieval
RAG ToolsAI Knowledge Retrieval
AI AgentsAI Workflow Automation

Data Visualization Tools "Create Clear Visual Reports and Interactive Dashboards with Popular Business Intelligence & Python Visualization Platforms"

Power BI Data Science Tool
Power BIBusiness Intelligence
Tableau Data Science Tool
TableauData Visualisation
Matplotlib Data Science Tool
MatplotlibPython Charts
Seaborn Data Visualization Tool
SeabornStatistical Graphics
Plotly Data Visualization Tool
PlotlyInteractive Charts
Dashboard ToolsInteractive Reporting

MLOps & Cloud Tools "Work with Deployment and Collaboration Tools Used to Manage, Package, Monitor & Scale Data Science Solutions"

MLflow Data Science Tool
MLflowML Lifecycle Management
Docker Data Science Tool
DockerModel Containerisation
Git Data Science Tool
GitVersion Control
GitHub Data Science Tool
GitHubCode Collaboration
AWS Data Science Tool
AWSCloud Computing
FastAPI Data Science Tool
FastAPIModel API Deployment
Cloud PlatformsData Science Deployment

Analytics & Professional Tools "Use Practical Tools for Analytics, Documentation, Project Collaboration & Building a Strong Data Science Portfolio"

Analytics ToolsBusiness Data Analysis
GitHub ProjectsProject Collaboration
Jupyter ReportsData Documentation
BI ToolsBusiness Reporting
Data ToolsData Preparation
GitHub Data Science Portfolio Tool
GitHubPortfolio & Collaboration
Qualifications

Eligibility & Criteria

Everything you need to know to join and qualify for placement.

Who Can Apply?

Eligibility Year of Passing

2018 and After

Graduates

Any Graduate / Diploma

Academic Percentage

Min 60%

Placement Eligibility

Attendance

Min 90%

Assessment Marks

Min 75%

Live Projects

100% Completion

Career Growth

Why Data Science
Course Is A Smart Career Choice

Data Science enables businesses to discover patterns, predict outcomes, and make informed decisions from large datasets. Training in Python, analytics, machine learning, visualization, and AI can help learners develop relevant capabilities for diverse technology and data-driven roles.

Growing Need for Data Specialists

Opportunities Across Business Sectors

Diverse Roles in Data & Technology

Access to Global Job Markets

Advancement with AI Innovations

Career Insights

Data Science Job Roles and Annual Salary Range in Hyderabad

Intern (0 - 6 Months)
Entry (0 - 2 Years)
Mid (2 - 5 Years)
Senior (5+ Years)
Stage 01

Data Analyst

Intern ₹2 LPA – ₹4 LPA
Entry ₹4 LPA – ₹8 LPA
  • Junior Data Analyst
  • Data Analyst
  • Business Analyst
  • Reporting Analyst
  • Data Quality Analyst
  • Operations Analyst
Stage 02

Business Intelligence Analyst

Entry ₹5 LPA – ₹9 LPA
Mid ₹8 LPA – ₹14 LPA
  • BI Analyst
  • BI Developer
  • Power BI Developer
  • Tableau Developer
  • BI Consultant
  • BI Manager
Stage 03

Data Scientist

Mid ₹12 LPA – ₹20 LPA
Senior ₹20 LPA – ₹40+ LPA
  • Junior Data Scientist
  • Data Scientist
  • Applied Data Scientist
  • Senior Data Scientist
  • Lead Data Scientist
  • Principal Data Scientist
Stage 04

Machine Learning Engineer

Mid ₹15 LPA – ₹25 LPA
Senior ₹25 LPA – ₹50+ LPA
  • ML Engineer
  • ML Developer
  • Applied ML Engineer
  • Senior ML Engineer
  • ML Architect
  • ML Engineering Lead
Stage 05

AI & Deep Learning Specialist

Mid ₹14 LPA – ₹25 LPA
Senior ₹25 LPA – ₹45+ LPA
  • AI Engineer
  • Deep Learning Engineer
  • Computer Vision Engineer
  • NLP Engineer
  • Generative AI Engineer
  • AI Solutions Architect
Stage 06

Data Science & AI Leadership

Mid ₹14 LPA – ₹25 LPA
Senior ₹20 LPA – ₹50+ LPA
  • Lead Data Scientist
  • Data Science Manager
  • Machine Learning Manager
  • AI Engineering Manager
  • Head of Data Science
  • Director of Data & AI
Career Path

Data Science Career Roadmap

01
Foundation Level
  • Data Analyst
  • Junior Analyst
  • BI Analyst
02
Professional Level
  • Data Scientist
  • ML Engineer
  • BI Developer
03
Advanced Level
  • Senior Data Scientist
  • ML Architect
  • Data Engineer
04
Leadership Level
  • Data Science Manager
  • AI Director
  • Head of Data
YOUR CAREER STARTS HERE

Ready to build your future?

Develop job-ready capabilities through a progressive curriculum covering Python, analytics, machine learning, AI, visualization and industry-based projects.

Enroll Now

● Industry Skills · Practical Projects

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Inspiration

Success Stories from Our Students

See how Linkplux's IT training programs have helped students land top jobs through hands-on learning and expert guidance.

Student Success Story Main
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Trilochana found her path with Linkplux and landed the dream job.

#Datascience
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Krithika transformed her career with Linkplux and secured a Data Analyst role with a 4.5 LPA package. 🚀

#DataAnalytics
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Students shared how Linkplux's practical training and live projects helped him confidently start his Digital Marketing career.

#DigitalMarketing
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Krithika built her Full Stack Development skills at Linkplux and secured a 7 LPA Software Developer role. 🚀

#FullStackDevelopment
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Oviya Shree developed strong Data Analytics skills at Linkplux and launched her career as a Data Analyst. 📊

#DataAnalytics
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From a small town to a top tech firm, learn how our hands-on projects helped.

#Inspiration
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From a small town to a top tech firm, learn how our hands-on projects helped.

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From a small town to a top tech firm, learn how our hands-on projects helped.

#Inspiration
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From a small town to a top tech firm, learn how our hands-on projects helped.

#Inspiration
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From a small town to a top tech firm, learn how our hands-on projects helped.

#Inspiration
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From a small town to a top tech firm, learn how our hands-on projects helped.

#Inspiration
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    Linkplux Certification

    Earn Professional Data Science Course
    Certification in Hyderabad

    A Data Science course certification from Linkplux validates practical skills in Python, SQL, statistics, machine learning, data visualization, predictive modelling, and analytical techniques. It enhances your professional profile, demonstrates hands-on project experience, and reflects your ability to work with data-driven solutions. The certification can support learners pursuing opportunities in Hyderabad’s technology ecosystem across roles such as Data Scientist, Data Analyst, Machine Learning Engineer, Business Intelligence Analyst, and Data Engineer while strengthening their industry-oriented technical foundation.

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    Reviews from Our Successful Students

    See how our AI-powered IT training institute has helped students succeed.

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    Frequently Asked Questions

    Data Science Training in Hyderabad introduces learners to data analysis, Python programming, statistics, data visualization, and machine learning. The curriculum may also include SQL, exploratory data analysis, predictive modelling, deep learning, and Generative AI concepts to help learners understand data-driven problem-solving.
    The course generally covers data collection, cleaning, transformation, statistical analysis, visualization, and predictive modelling. Learners may work with Python libraries, SQL databases, machine learning algorithms, and reporting tools to understand how organizations convert raw information into useful insights.
    Learners can develop analytical thinking, Python coding, statistical interpretation, data preparation, visualization, and machine learning skills. Training activities may also improve their ability to evaluate datasets, identify trends, build predictive models, and communicate findings through reports and dashboards.
    Important topics may include Python fundamentals, NumPy, Pandas, SQL, probability, statistics, data preprocessing, exploratory analysis, visualization, supervised and unsupervised learning, model evaluation, and feature engineering. Advanced modules may introduce deep learning, natural language processing, and model deployment.
    Data Science Training in Hyderabad helps learners build practical knowledge in analytics, programming, and predictive modelling. These skills can support career opportunities in technology, healthcare, finance, retail, and other sectors that rely on data for reporting, forecasting, and business decisions.
    Yes, beginners can join Data Science Training in Hyderabad through a course that starts with foundational concepts. Learners can begin with Python basics, introductory statistics, and data handling before advancing to visualization, machine learning, and practical analytical projects.
    Yes, practical assignments and projects may be included depending on the course syllabus. Learners can practise cleaning datasets, creating visual reports, analysing business trends, building prediction models, and completing case studies that demonstrate their ability to apply data science methods.
    After completing Data Science Training in Hyderabad, learners may explore roles such as Data Analyst, Junior Data Scientist, Machine Learning Engineer, Business Intelligence Analyst, Data Engineer, and AI Engineer. Suitable positions depend on programming ability, analytical knowledge, project experience, and employer requirements.
    No, prior Python knowledge is not always necessary for beginner-level training. A structured course can teach programming fundamentals first, followed by data manipulation, statistical analysis, visualization, and machine learning techniques as learners progress.
    Yes, some training providers offer course completion certificates and career assistance, depending on the program. Available support may include resume preparation, mock interviews, technical interview practice, project guidance, and job updates for relevant data science and analytics roles.