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Home  / Data Science Course In IDM Techpark

Data Science Course Training in Erode

"Learn to create data-driven solutions. Join now to learn from an experienced data science expert."

Master Java programming with this in-depth course! Learn core Java, OOP, data structures, and build real-world applications. Perfect for beginners & experienced developers looking to enhance their skills.

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Best Data Science course in Erode

4.9/5

Best Data Science course in Erode

4.8/5

Best Data Science course in Erode

4.7/5

Best Data Science course in Erode

4.9/5

Best Data Science course in Erode

4.5/5

Live Project

Course Duration

80 Hrs.

2 Project

Training Format

Certification Pass

Guranteed

Live Online /Self-Paced/Classroom

Best Software training institute in Erode -IDM Teckpark

Speciality

500 +

Professionals Trained

4 +

Batches every month

100+

Corporate Served

Data Science Course in Erode

Data Science is an interdisciplinary field that focuses on analyzing both structured and unstructured data to uncover valuable insights. It combines statistical methods, algorithms, and machine learning techniques to extract meaningful patterns, aiding businesses in making informed decisions. By leveraging big data, organizations can identify trends, improve efficiency, and implement data-driven strategies. With its growing importance, Data Science is now essential across multiple industries such as finance, healthcare, e-commerce, and technology.

Course includes:

 Course Level Expert

Duration: 6 Months

Modules: 47

Certification: Yes

Projects: 5+

Timings Doesn't Suit You ?

We can set up a batch at your convenient time.

Blue Gradient

Program Core Credentials - Data Science Course in Erode

Trainer Profiles

Industry Experts

Trained Students

5000+

Corporate Training

For India 

Job Assistance

100%

BATCH TIMING

As per your requirement

Training Features of Data Science course in Erode

Instructor-led Sessions

SDigital Academy offers a traditional learning experience with modern advantages, providing easy access to content anytime on any internet-connected device. 

Real-life Case Studies

SDigital Academy offers real-life case studies to provide practical insights and hands-on learning experiences. Gain valuable knowledge from real-world examples to enhance your skills and understanding.

Assignment

SDigital Academy provides engaging assignments to reinforce learning and assess progress. These tasks are designed to challenge learners and ensure a deeper understanding of the material.

Lifetime Access

SDigital Academy offers lifetime access to course content, allowing learners to revisit and review materials at any time. Enjoy continuous learning and growth, 

24 x 7 Expert Support

SDigital Academy provides 24/7 expert support to assist learners whenever needed. Our team is always available to resolve queries and guide you through your learning experience.

Certification

SDigital Academy offers certificates upon successful completion of courses, Showcase your achievements and enhance your professional credentials with our recognized certifications.

Blue Gradient

Showcase your Course Completion Certificate to Recruiters

Training Certificate is Govern By 12 Global Associations.

Training Certificate is Powered by "Verifiable Skill Credentials"

Best Software training institute in Erode -IDM Teckpark
Best Software training institute in Erode -IDM Teckpark
Best Data Science course in Erode
Best Software training institute in Erode -IDM Teckpark

Students Placements & Reviews

200+ Companies hired 

Best Data Science course in Erode

Skills You’ll Learn in Data Science course in Erode​

"This Data Science course at IDM Techpark in Coimbatore covers a wide range of skills, including:"

Best Data Science course in Erode

PYTHON

Best Data Science course in Erode

SQL

Best Data Science course in Erode

MEACHINE

LEARNING

Best Data Science course in Erode

BIG DATA

Best Data Science course in Erode

DEEP 

LEARNING

Tools Covered

By the end of the Data Science course at IDM Techpark in Coimbatore, you'll have a powerful tech stack at your fingertips, including tools

Best Data Science course in Erode

TABLEAU

Best Data Science course in Erode

POWER BI

Best Data Science course in Erode

MATPLOTLIB 

Best Data Science course in Erode
Best Data Science course in Erode
What are the skills required in Data Science course?

Programming Languages

Python, R, and SQL for data manipulation and analysis.

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Data Analysis & Visualization

Using tools like Pandas, Matplotlib, and Tableau to interpret data.

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Machine Learning & AI

Applying supervised and unsupervised learning techniques using TensorFlow, Scikit-Learn, and PyTorch.

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Statistical & Mathematical Modeling

​Understanding probability, regression, and hypothesis testing for accurate predictions.

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Career Opportunities in Data Science Course in Erode

Data Science is a rapidly growing field that focuses on extracting meaningful insights from data using statistical methods, machine learning, and artificial intelligence. It combines programming, data analysis

Data Scientist

Machine Learning Engineer

Data Analyst

Data Engineer

Who Can Enroll in the Data Science Course in Erode?

There are no strict prerequisites to join the course. However, ideal candidates include:

Beginners looking to start a career in Data Science.

Students & graduates in Computer Science, 

Graduates and working professionals 

Business professionals who want to leverage data

Tech enthusiasts passionate about data-driven problem-solving.

Data Science Course Fees & Enrollment

Flexible payment options available.

EMI and installment plans for easy accessibility.

Follow us on Instagram & Telegram for updates on new courses and discounts.

50+ Advanced Modules Covered
  • 2. Ruby on Rails Modules
    ActiveRecord – Object-Relational Mapping (ORM) for working with databases. ActionView – Handles templates and rendering in Rails applications. ActionController – Manages user requests and responses in MVC architecture. ActiveSupport – Adds useful utilities like time calculations (2.days.ago).
  • 1. Core Ruby Modules (Built-in)
    Enumerable – Adds iteration methods like map, select, reduce, and each_with_index. Comparable – Enables comparison of objects using <, >, ==, etc. Math – Provides mathematical functions such as sqrt, log, and sin. Time & Date – Helps manage and manipulate time-related data. File & Dir – Enables file handling and directory management.
  • 3. Web Development & API Modules
    Sinatra – A lightweight framework for web applications. HTTParty – Makes HTTP requests easier. JSON – Parses and generates JSON data. Puma – A web server for Ruby applications.
  • 5. Testing & Debugging Modules
    Modules that help in testing and debugging Ruby applications. RSpec – A popular testing framework. MiniTest – A lightweight testing framework built into Ruby. Pry – A powerful debugging tool for Ruby. Byebug – A step-by-step debugger for troubleshooting issues.
  • 4. Security & Authentication Modules
    BCrypt – Encrypts passwords securely. Devise – Handles user authentication in Rails. OmniAuth – Allows third-party authentication (Google, Facebook, GitHub).
  • 3. Layouts & Navigation
    Column, Row, Stack, ListView, GridView Navigation & Routing (Named Routes, Push & Pop) Passing Data between Screens
  • 2. Flutter Basics
    Understanding Flutter architecture Widgets: Stateless & Stateful Building UI with Material & Cupertino Widgets Handling User Inputs (TextFields, Buttons, Forms)
  • 4. State Management
    setState (Local State Management) Provider (Basic State Management) Riverpod, Bloc, GetX (Advanced State Management)
  • 5. Working with APIs & Networking
    HTTP Requests using http and dio packages Consuming REST APIs & JSON Handling Displaying Data in ListView
  • 1. Introduction to Flutter & Dart
    Overview of Flutter and its advantages Setting up the development environment (Flutter SDK, Android Studio, VS Code) Introduction to Dart (Syntax, Variables, Data Types, Functions, OOP)
  • 1. Fundamentals of Graphic Design
    Introduction to Graphic Design & Visual Communication Color Theory, Typography, and Layout Design Understanding Composition & Balance in Design
  • 5. UI/UX & Web Graphics (Optional but In-Demand)
    Wireframing & Prototyping Designing for Websites & Mobile Apps Responsive Design Basics
  • 3. Branding & Identity Design
    Logo & Icon Design Principles Business Cards, Letterheads & Corporate Branding Packaging & Label Design
  • 2. Design Software & Tools (Hands-on Training)
    Adobe Photoshop – Image Editing & Manipulation Adobe Illustrator – Vector Graphics & Logo Design Adobe InDesign – Print Layout & Publishing CorelDRAW – Advanced Vector Design (Optional) Figma / Adobe XD – UI/UX & Web Design (Optional)
  • 4. Digital Marketing Graphics
    Social Media Post & Banner Design Website Banners & Ads Infographic Design for Marketing
  • Module 2: PL/SQL Block Structure
    Anonymous blocks Declaring variables and data types Using BEGIN, EXCEPTION, and END Writing simple PL/SQL programs
  • Module 5: Stored Procedures and Functions
    Creating and calling stored procedures Creating functions with return values Difference between procedures and functions
  • Module 1: Introduction to PL/SQL
    Overview of PL/SQL and its importance Differences between SQL and PL/SQL PL/SQL architecture and block structure Execution environments (SQL*Plus, Oracle SQL Developer)
  • Module 4: Cursors and Exception Handling
    Implicit vs. Explicit Cursors Cursor attributes (%FOUND, %NOTFOUND, %ROWCOUNT) Handling errors using EXCEPTION and RAISE_APPLICATION_ERROR
  • Module 3: Control Structures in PL/SQL
    Conditional statements (IF-THEN-ELSE, CASE) Looping constructs (FOR, WHILE, LOOP, EXIT)
  • Module 5: Typography & Text Effects
    Working with Text Layers & Font Styles Creating 3D & Embossed Text Effects Using Text in Branding & Social Media Graphics Applying Gradients, Shadows, and Strokes
  • Module 1: Introduction to Adobe Photoshop
    Overview of Photoshop Interface & Tools Understanding Raster vs. Vector Graphics Working with Workspaces and Panels Customizing Photoshop Preferences
  • Module 4: Selection & Transformation Tools
    Marquee, Lasso, and Quick Selection Tools Pen Tool & Paths for Precise Selections Transforming & Distorting Images (Scale, Warp, Perspective) Clipping Masks for Creative Effects
  • Module 2: Image Editing & Retouching
    Cropping, Resizing, and Adjusting Images Color Correction & Enhancements (Levels, Curves, Hue/Saturation) Removing Backgrounds (Selection, Masking, and Cutout Techniques) High-End Photo Retouching (Skin Smoothing, Blemish Removal)
  • Module 3: Working with Layers & Masking
    Layer Management & Smart Objects Layer Styles, Blending Modes, and Opacity Advanced Layer Masking Techniques Adjustment Layers for Non-Destructive Editing
  • 5. Statistical Analysis Using R
    Descriptive statistics (mean, median, mode, variance, standard deviation) Hypothesis testing (t-test, chi-square test, ANOVA) Correlation and regression analysis
  • 3. Data Import & Export
    Reading and writing CSV, Excel, JSON, and databases Web scraping and API integration
  • 4. Data Visualization in R
    ggplot2, lattice, and base R graphics Creating bar charts, histograms, scatter plots, and box plots Customizing and styling visualizations
  • 2. Data Structures in R
    Vectors, Lists, Matrices, and Data Frames Factors and Arrays Data manipulation using dplyr and tidyr
  • 1. Introduction to R Programming
    Overview of R and its applications Installation and setup of R and RStudio Basic R syntax, variables, and data types
  • Module 4: Working with Colors & Gradients
    Color modes (RGB, CMYK, Pantone, HEX) for digital & print Gradient, mesh tool, and color blending techniques Creating and applying custom swatches and patterns Using opacity, transparency, and layer blending modes
  • Module 3: Typography & Text Effects
    Working with Type Tool & Character Panel Creating custom fonts, text effects, and typography layouts Warping, outlining, and styling text Path-based text and text wrapping techniques
  • Module 1: Introduction to Adobe Illustrator
    Overview of vector graphics vs. raster graphics Adobe Illustrator interface, tools, and workspace customization Creating and saving new documents in different formats Understanding artboards, rulers, grids, and guides
  • Module 2: Basic Drawing & Shapes
    Working with pen, pencil, brush, and blob brush tools Creating and modifying basic geometric shapes Using stroke, fill, and gradient tools Customizing dashed lines, variable width strokes, and blending
  • Module 5: Advanced Pen Tool & Paths
    Mastering the Pen Tool for smooth curves and precise shapes Pathfinder & Shape Builder Tool for complex vector designs Creating custom icons, logos, and scalable vector art
  • 📌 Module 2: Video Editing Software & Tools
    Introduction to Adobe Premiere Pro, Final Cut Pro, DaVinci Resolve, Sony Vegas Pro. Setting up the workspace, project files, and editing timeline. Importing, organizing, and managing raw video footage.
  • 📌 Module 5: Color Correction & Grading
    Adjusting brightness, contrast, and saturation. Using LUTs (Look-Up Tables) and color grading techniques for cinematic looks. Fixing exposure issues and white balance correction.
  • 📌 Module 1: Introduction to Video Editing
    Overview of video editing and its role in digital media. Understanding different types of video content (films, advertisements, social media, etc.). Basics of storytelling and visual continuity.
  • 📌 Module 4: Audio Editing & Sound Design
    Synchronizing audio with video. Enhancing sound quality with noise reduction and audio effects. Adding background music, voiceovers, and sound effects.
  • 📌 Module 3: Basic Video Editing Techniques
    Trimming, cutting, and arranging clips on the timeline. Using transitions, jump cuts, and montage sequences. Understanding different video formats, codecs, and resolutions.
  • 4. Wireframing & Prototyping
    Low-fidelity vs. high-fidelity wireframes Creating interactive prototypes using Figma, Adobe XD, or Sketch Design handoff and collaboration with developers Usability testing of wireframes and prototypes
  • 2. UX Research & User Analysis
    Conducting user research and competitor analysis Creating user personas and user journey maps Wireframing and information architecture Heuristic evaluation and usability testing
  • 3. UI Design Principles
    Fundamentals of color theory, typography, and layouts UI components, grid systems, and visual hierarchy Mobile-first and responsive design principles Accessibility and inclusive design
  • 5. UI/UX Design Tools & Software
    Hands-on training in Figma, Adobe XD, Sketch, Photoshop, and Illustrator Designing and prototyping with real-world projects Asset exporting and integration with development teams
  • 1. Introduction to UI/UX Design
    Understanding the difference between UI (User Interface) & UX (User Experience) Importance of UI/UX in product development Design thinking and user-centered design principles Industry trends and career opportunities in UI/UX
  • Text and Typography Animation
    Creating and animating text layers Using text presets and effects Kinetic typography techniques
  • 1. Introduction to After Effects
    Overview of the interface and workspace Understanding compositions, layers, and keyframes Importing assets and organizing projects
  • 5. Motion Tracking & Stabilization
    2D and 3D motion tracking Camera tracking for integrating 3D elements Object removal and stabilization techniques
  • 4. Visual Effects (VFX) & Compositing
    Green screen (chroma keying) techniques Rotoscoping for isolating objects Using blending modes and mattes Color correction and grading
  • 2. Animation Basics
    Keyframing and interpolation Motion paths and easing for smooth animations Shape layers and vector graphics
  • Module 1: Introduction to Databases & SQL
    Overview of Relational Database Management Systems (RDBMS) Understanding Databases, Tables, and Schemas Introduction to SQL & its Importance in Data Management Installing MySQL, PostgreSQL, or SQL Server
  • Module 4: Database Design & Normalization
    Understanding Data Relationships (One-to-One, One-to-Many, Many-to-Many) Normalization Techniques (1NF, 2NF, 3NF, BCNF) Denormalization & Indexing for Performance Optimization Designing ER Diagrams and Schema Modeling
  • Module 5: Data Manipulation & Transactions
    INSERT, UPDATE, DELETE Statements Using Primary Keys & Foreign Keys Understanding Transactions & ACID Properties Implementing ROLLBACK, COMMIT, and SAVEPOINTS
  • Module 3: Advanced SQL Queries
    Joins & Relationships (INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN) Subqueries & Nested Queries Using GROUP BY and HAVING Clauses Window Functions & Common Table Expressions (CTEs)
  • Module 2: SQL Basics & Querying Data
    Writing Basic SQL Queries (SELECT, FROM, WHERE, ORDER BY, LIMIT) Filtering & sorting data efficiently Using Aliases and Aggregate Functions (SUM, COUNT, AVG, MAX, MIN) Handling NULL values and Data Constraints
  • Module 3: Advanced SQL & Joins
    ✔ Understanding primary & foreign keys ✔ One-to-One, One-to-Many, Many-to-Many relationships ✔ INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN ✔ Subqueries & nested queries ✔ UNION, INTERSECT, and EXCEPT
  • Module 2: SQL Fundamentals & Querying
    ✔ Data types, tables, and schema design ✔ Writing basic SQL queries (SELECT, INSERT, UPDATE, DELETE) ✔ Filtering data using WHERE, GROUP BY, and HAVING ✔ Sorting & limiting results (ORDER BY, LIMIT) ✔ Using DISTINCT & aggregate functions (COUNT, SUM, AVG, MIN, MAX)
  • Module 1: Introduction to MySQL & Databases
    ✔ Understanding relational databases (RDBMS) ✔ MySQL architecture & components ✔ Installing & setting up MySQL ✔ Connecting to MySQL using CLI & GUI tools (MySQL Workbench, phpMyAdmin)
  • Module 4: MySQL Stored Procedures & Functions
    ✔ Writing & executing stored procedures ✔ Creating and using MySQL functions ✔ Handling parameters & return values ✔ Error handling with MySQL exceptions ✔ Implementing cursors and loops
  • State Management Modules
    Context API (React Built-in) – Lightweight state management. Redux – Advanced state management with a centralized store. Zustand – Lightweight and minimalistic state management. MobX – Simpler alternative to Redux. Recoil – Easy-to-use state management from Facebook.
  • UI & Component Libraries
    React Native Paper – Material Design components. NativeBase – Pre-built UI components for faster development. React Native Elements – UI components with easy customization. Lottie for React Native – Animated vector graphics for smooth UI animations.
  • API & Networking Modules
    Axios – Popular library for handling API requests. Fetch API (Built-in) – Native JavaScript method for API requests. GraphQL (Apollo Client, Relay) – Efficiently fetch and manage GraphQL-based APIs.
  • Core React Native Modules
    View – A container for UI elements, similar to <div> in HTML. Text – Displays text content. Image – Displays images from local or remote sources. ScrollView – A scrollable container for UI elements. FlatList / SectionList – Optimized lists for rendering large sets of data. TouchableOpacity / TouchableHighlight – Provides button-like functionality with animations. TextInput – Input field for user text entry.
  • Navigation Modules
    React Navigation – The most popular navigation library for handling stacks, tabs, and drawers. @react-navigation/native (Core) @react-navigation/stack (Stack navigation) @react-navigation/drawer (Side drawer navigation) @react-navigation/bottom-tabs (Bottom tab navigation) React Native Navigation (Wix) – Alternative navigation library with native performance.
  • Module 2: Kotlin Basics & Core Concepts
    Variables and Data Types Operators and Expressions Control Flow (if-else, when, loops) Functions and Scope Lambda Expressions and Higher-Order Functions
  • Module 5: Exception Handling & Null Safety
    Try-Catch Blocks Throwing and Custom Exceptions The Elvis Operator (?:) and Safe Calls (?.) Late Initialization (lateinit and lazy)
  • Module 4: Functional Programming in Kotlin
    Collections (Lists, Sets, Maps) Extension Functions Generics and Type Safety Kotlin Standard Library Functions Streams, Filtering, and Mapping Data
  • Module 3: Object-Oriented Programming (OOP) in Kotlin
    Classes, Objects, and Constructors Inheritance and Polymorphism Abstract Classes and Interfaces Data Classes and Sealed Classes Singleton and Companion Objects
  • Module 1: Introduction to Kotlin
    Overview of Kotlin and its advantages Setting up the development environment (Android Studio, IntelliJ IDEA) Kotlin vs Java – Key differences Writing your first Kotlin program
  • Module 3: Setting Up a GraphQL Server
    Installing and configuring a GraphQL server Using Apollo Server and Express-GraphQL Connecting GraphQL with a database (SQL & NoSQL) Implementing resolvers for API endpoints
  • Module 1: Introduction to GraphQL
    What is GraphQL? GraphQL vs. REST APIs Benefits and use cases of GraphQL GraphQL ecosystem and tools
  • Module 4: Queries, Mutations, and Subscriptions
    Writing advanced queries with filters, arguments, and variables Performing mutations to create, update, and delete data Implementing real-time data updates using GraphQL subscriptions
  • Module 5: GraphQL Schema Design
    Defining types, fields, and relationships Working with enums, unions, and interfaces Schema best practices and versioning
  • Module 2: GraphQL Basics
    GraphQL query structure Writing basic queries and mutations GraphQL schemas and types Understanding resolvers
  • Requirement Gathering & Elicitation
    Techniques for gathering business requirements (interviews, surveys, workshops, observations) Stakeholder identification and management Documenting requirements (BRD, FRD) Defining functional and non-functional requirements
  • Agile Methodology for Business Analysts
    Introduction to Agile and Scrum frameworks Writing user stories and acceptance criteria Agile ceremonies (sprints, stand-ups, retrospectives) Working in an Agile team and facilitating Agile practices
  • Data Analysis & Reporting
    Introduction to data analysis for business insights Data collection and cleaning Analyzing business data using Excel, Power BI, and Tableau Creating dashboards and reports for decision-makers
  • Introduction to Business Analysis
    Role and responsibilities of a Business Analyst Key concepts in Business Analysis Overview of the business analysis lifecycle Importance of Business Analysis in organizations
  • Business Process Modeling & Improvement
    Process mapping techniques (BPMN, flowcharts, SIPOC) Business process analysis and redesign Identifying inefficiencies and bottlenecks Process improvement methodologies (Six Sigma, Lean)
  • Module 1: Introduction to DevOps and AWS Cloud
    Overview of DevOps principles and practices. Introduction to Cloud Computing and AWS services. Differences between traditional software development and DevOps. Importance of automation in DevOps. Understanding AWS cloud architecture and core services like EC2, S3, IAM, VPC.
  • Module 5: Continuous Integration/Continuous Deployment (CI/CD) Pipelines
    Setting up a full CI/CD pipeline using AWS CodePipeline. Automating the build, test, and deploy phases of the pipeline. Integrating CodeCommit, CodeBuild, and CodeDeploy into a seamless pipeline. Managing pipeline stages and monitoring pipeline status.
  • Module 3: Continuous Integration (CI) with AWS
    Introduction to Continuous Integration (CI). Setting up AWS CodeBuild for building code and automating builds. Integrating AWS CodeBuild with Git repositories. Building and testing applications automatically. Understanding build pipelines and managing build artifacts.
  • Module 4: Continuous Delivery (CD) with AWS
    Introduction to Continuous Delivery (CD). Setting up AWS CodeDeploy for automating application deployments. Deployment strategies: Blue/Green, Rolling, and Canary deployments. Integrating CodeDeploy with EC2, Lambda, or on-premises servers. Handling versioning and rollback scenarios.
  • Module 2: Source Control and Version Control with Git
    Introduction to Git and version control systems. Setting up AWS CodeCommit (AWS’s managed Git service). Basic Git commands (clone, commit, push, pull). Managing repositories and branches in CodeCommit. Best practices for version control.
  • Module 5: Deep Neural Networks (DNNs)
    Understanding Deep Neural Networks Feedforward Networks and Backpropagation Challenges in Deep Networks (Vanishing/Exploding Gradients) Regularization Techniques (Dropout, L2 regularization)
  • Module 2: Mathematics for Deep Learning
    Linear Algebra (Matrices, Vectors, and Tensors) Probability and Statistics Calculus for Optimization (Gradient Descent) Cost Functions and Backpropagation
  • Module 1: Introduction to Deep Learning
    Overview of AI and Deep Learning Difference between AI, Machine Learning, and Deep Learning Applications of Deep Learning Key Concepts in Deep Learning
  • Module 3: Python for Deep Learning
    Introduction to Python Programming Libraries for Deep Learning: NumPy, Pandas, Matplotlib, Seaborn TensorFlow and Keras Basics Data Preprocessing with Python
  • Module 4: Neural Networks Fundamentals
    Basic Concepts: Neurons, Layers, Activation Functions Building a Simple Neural Network Training Neural Networks Gradient Descent and Optimization
  • Module 1: Introduction to Artificial Intelligence & Machine Learning
    Overview of AI, ML, and Deep Learning Applications of AI & ML in various industries Difference between AI, ML, and Data Science Supervised vs. Unsupervised Learning
  • Module 5: Deep Learning & Neural Networks
    Fundamentals of Neural Networks Activation Functions & Optimization Techniques Introduction to TensorFlow & PyTorch Building Deep Learning Models
  • Module 2: Python for AI & ML
    Python programming basics and advanced concepts Data structures and algorithms in Python Libraries for AI & ML: NumPy, Pandas, Matplotlib, Seaborn
  • Module 3: Data Preprocessing & Feature Engineering
    Data cleaning and handling missing values Data transformation and normalization Feature selection and dimensionality reduction
  • Module 4: Machine Learning Algorithms
    Linear Regression & Logistic Regression Decision Trees & Random Forest Support Vector Machines (SVM) K-Nearest Neighbors (KNN) Naïve Bayes Classification
  • Statistics & Probability for Data Science
    ✅ Descriptive and Inferential Statistics ✅ Probability Distributions (Normal, Binomial, Poisson) ✅ Hypothesis Testing and Confidence Intervals ✅ Correlation and Regression Analysis
  • Data Handling & Manipulation
    ✅ Introduction to NumPy and Pandas ✅ Data Cleaning, Preprocessing, and Transformation ✅ Handling Missing Values and Outliers ✅ Exploratory Data Analysis (EDA)
  • Machine Learning Fundamentals
    ✅ Introduction to Supervised & Unsupervised Learning ✅ Linear Regression, Logistic Regression ✅ Decision Trees and Random Forest ✅ Clustering (K-Means, Hierarchical Clustering)
  • Introduction to Data Science & Python
    ✅ Overview of Data Science and its applications ✅ Role of Python in Data Science ✅ Setting up Python Environment (Anaconda, Jupyter Notebook, VS Code) ✅ Python Basics – Variables, Data Types, and Control Structures
  • Data Visualization
    ✅ Matplotlib and Seaborn for Data Visualization ✅ Creating Charts, Graphs, and Plots ✅ Heatmaps, Boxplots, and Histogram Analysis ✅ Interactive Dashboards with Plotly
  • Fundamentals of Programming & .NET Framework
    🔹 Introduction to Full Stack Development 🔹 Understanding .NET Framework vs .NET Core 🔹 Setting up Visual Studio & .NET Development Environment 🔹 Basics of C# Programming 🔹 Object-Oriented Programming (OOP) with C# 🔹 Error Handling & Debugging
  • Database Management & ORM
    🔹 Introduction to SQL Server & Database Design 🔹 Writing SQL Queries & Stored Procedures 🔹 Database Connectivity with ADO.NET & Entity Framework (EF Core) 🔹 LINQ (Language Integrated Query) for Data Manipulation 🔹 Implementing CRUD Operations
  • Frontend Development
    🔹 HTML5, CSS3, and JavaScript for UI Design 🔹 Responsive Design with Bootstrap & Tailwind CSS 🔹 Modern JavaScript (ES6+) & DOM Manipulation 🔹 TypeScript & Angular (or React) for frontend development 🔹 Blazor for building interactive web applications 🔹 State Management & UI Components
  • API Development & Integration
    🔹 RESTful API Development with ASP.NET Core 🔹 JSON & XML Data Handling 🔹 API Documentation with Swagger 🔹 Third-party API Integration & OAuth Authentication 🔹 GraphQL Basics & Implementation
  • Backend Development with ASP.NET Core
    🔹 Introduction to ASP.NET Core & MVC Architecture 🔹 Routing, Controllers, and Actions 🔹 Dependency Injection & Middleware 🔹 Entity Framework Core (EF Core) for Database Integration 🔹 Authentication & Authorization with JWT & Identity 🔹 API Development with ASP.NET Core Web API 🔹 Microservices Architecture in .NET
  • Version Control & Deployment
    🔹 Git & GitHub – Version control and collaboration 🔹 Docker & Kubernetes – Containerization and orchestration 🔹 Cloud Deployment – AWS, Heroku, and Firebase hosting
  • Real-World Project Development
    🔹 Capstone Projects – Hands-on experience in building applications 🔹 Live Projects – Develop and deploy real-world applications 🔹 Portfolio Building – Showcase skills through GitHub and LinkedIn
  • Frontend Development
    🔹 HTML5, CSS3, and JavaScript – Web structuring and styling 🔹 Bootstrap & Tailwind CSS – Responsive UI design 🔹 React.js / Angular – Dynamic frontend development 🔹 DOM Manipulation – Interactive web pages 🔹 AJAX & Fetch API – Asynchronous data fetching
  • Backend Development with Python
    🔹 Core Python – Syntax, data types, and OOP concepts 🔹 Django & Flask – Web frameworks for backend development 🔹 RESTful APIs & GraphQL – API creation and integration 🔹 Authentication & Security – User authentication, JWT, OAuth 🔹 Error Handling & Debugging – Writing efficient backend code
  • Database Management
    🔹 SQL & NoSQL Databases – MySQL, PostgreSQL, and MongoDB 🔹 ORM (Object Relational Mapping) – Django ORM & SQLAlchemy 🔹 CRUD Operations – Data handling and management
  • Module 1: Core Java & Object-Oriented Programming (OOP)
    ✅ Introduction to Java and JVM ✅ Variables, Data Types, and Operators ✅ Control Flow Statements (Loops & Conditions) ✅ Functions and Exception Handling ✅ Object-Oriented Programming Concepts (Classes, Objects, Inheritance, Polymorphism) ✅ Collections Framework and Multithreading
  • Module 2: Backend Development with Java Spring Boot
    ✅ Introduction to Spring Boot and Microservices ✅ RESTful API Development with Spring Boot ✅ Dependency Injection and Spring MVC ✅ Hibernate & JPA for Database Integration ✅ Spring Security & Authentication (JWT, OAuth) ✅ Logging, Exception Handling, and API Testing
  • Module 5: Capstone Project & Placement Assistance
    ✅ End-to-End Full Stack Web Application Development ✅ Version Control with Git & GitHub ✅ Debugging, Performance Optimization, and Testing ✅ Resume Building & Interview Preparation ✅ Mock Interviews and Coding Challenges ✅ 100% Placement Assistance with Career Guidance
  • Module 4: Database Management & Cloud Deployment
    ✅ Introduction to SQL & NoSQL Databases ✅ MySQL and PostgreSQL – Queries, Joins, and Indexing ✅ MongoDB for NoSQL Database Integration ✅ Connecting Java Applications with Databases (JDBC, Hibernate) ✅ Cloud Deployment with AWS/GCP/Azure ✅ CI/CD Pipelines and Docker Containerization
  • Module 3: Frontend Development with HTML, CSS, JavaScript & React/Angular
    ✅ HTML5, CSS3, and Bootstrap for UI Design ✅ JavaScript Fundamentals (ES6, DOM Manipulation) ✅ React.js or Angular for Frontend Development ✅ State Management with Redux (React) ✅ Consuming REST APIs in Frontend ✅ Responsive Web Design & UI Optimization
  • Module 4: Full Stack Integration & Deployment
    Connecting React frontend with Node.js backend API integration and handling requests Authentication & authorization (User login/logout) Deployment using Heroku, Vercel, or Netlify Environment variables and production optimization
  • Module 3: Database Management with MongoDB
    Introduction to NoSQL and MongoDB CRUD operations with MongoDB Mongoose for database modeling Aggregation framework and indexing for performance Connecting MongoDB with Express.js
  • Module 5: Advanced Concepts & Capstone Project
    WebSockets and real-time communication (Socket.io) Serverless architecture and cloud functions Performance optimization & debugging Building a real-world project (E-commerce, Social Media App, etc.) Portfolio building and interview preparation
  • Module 2: Backend Development with Node.js & Express.js
    Introduction to Node.js and its architecture Setting up Express.js for backend development RESTful API development Middleware and authentication (JWT, OAuth) Error handling and security best practices
  • Module 1: Frontend Development with React.js
    Introduction to HTML, CSS, and JavaScript React.js fundamentals: Components, Props, and State React Hooks (useState, useEffect, useContext) React Router for navigation State Management (Context API, Redux - optional) Responsive design with Bootstrap/Tailwind CSS
  • Version Control & Deployment
    Git & GitHub Basics Hosting & Deployment on Servers Debugging & Performance Optimization
  • Front-End Development
    HTML, CSS, JavaScript Bootstrap & Responsive Design React.js or Vue.js Basics
  • Back-End Development with PHP
    Core PHP & Advanced PHP Object-Oriented Programming (OOP) in PHP Handling Forms & Sessions
  • Database Management
    MySQL & SQL Queries Database Connectivity with PHP (PDO & MySQLi) CRUD Operations
  • PHP Frameworks
    Laravel / CodeIgniter Basics MVC Architecture RESTful API Development
  • Functions and Modular Programming in C
    Defining and calling functions Scope and lifetime of variables Recursive functions Header files and standard libraries
  • Introduction to Programming Concepts
    Understanding algorithms and flowcharts Problem-solving techniques
  • Control Structures in C
    Decision-making statements (if, else, switch) Looping constructs (for, while, do-while) Jump statements (break, continue, goto)
  • Arrays and Strings in C
    Single and multidimensional arrays String handling and manipulation Dynamic arrays
  • Basics of C Programming
    History and evolution of C Structure of a C program Data types, variables, and constants Operators and expressions Input and output functions
  • CSS (Cascading Style Sheets)
    CSS syntax and selectors Box model, margins, padding, and borders Layouts: Flexbox and Grid systems Responsive design principles and media queries CSS animations and transitions
  • JavaScript
    Fundamentals of programming with JavaScript DOM manipulation and event handling ES6+ features Introduction to AJAX for asynchronous data fetching
  • Introduction to Web Technologies
    Understanding the internet and web protocols Types of websites (static vs. dynamic) Basics of domain names and hosting services
  • HTML (HyperText Markup Language)
    HTML syntax and structure Tags, attributes, and elements Creating forms and tables Semantic HTML5 elements
  • Front-End Frameworks and Libraries
    Introduction to jQuery for simplified JavaScript operations Overview of front-end frameworks like React.js or Angular Utilizing CSS frameworks such as Bootstrap or Tailwind CSS for responsive design
  • Strings and Regular Expressions
    String operations and functions Pattern matching with regular expressions
  • Functions
    Defining and invoking functions Function parameters and return values Variable scope and recursion
  • Control Structures
    Conditional statements (if, else, switch) Loops (for, while, do-while, foreach)
  • Arrays
    Indexed and associative arrays Array functions and manipulation Multidimensional arrays
  • Introduction to PHP
    Overview of PHP and its evolution Basic syntax and embedding PHP in HTML Variables, constants, and data types Operators and expressions
  • Java/Kotlin Programming Fundamentals
    Review of object-oriented programming concepts. Syntax and features of Java or Kotlin, the primary languages for Android development. Exception handling and multithreading.
  • Introduction to Android Development
    Overview of the Android platform and its architecture. Setting up the development environment using Android Studio. Understanding the components of an Android application. Creating and running a simple Android application.
  • Activity and Fragment Lifecycle
    Managing the lifecycle of Activities and Fragments. Navigating between different screens within an app. Handling user interactions and events.
  • User Interface (UI) Design
    Designing layouts using XML. Understanding Views, ViewGroups, and common UI components. Implementing responsive designs for various screen sizes and orientations.
  • Data Storage and Management
    Using SQLite databases for local data storage. Implementing SharedPreferences for simple data persistence. Working with Content Providers to share data between applications
  • React Router
    Setting up routing for single-page applications Implementing nested routes and navigation Utilizing route parameters and query strings
  • React Hooks
    Understanding built-in hooks such as useState, useEffect, and useContext Developing custom hooks for reusable logic Best practices for using hooks in functional components
  • State and Props
    Managing component state and understanding its significance Passing data between components using props Implementing controlled and uncontrolled components
  • State Management with Redux
    Introduction to Redux principles Setting up Redux in a React application Creating actions, reducers, and managing the store Handling asynchronous actions with middleware like Redux Thunk
  • React Components
    Creating and managing functional and class components Component lifecycle methods and their applications Handling events within components
  • AngularJS Expressions and Data Binding
    Utilizing expressions in AngularJS Implementing two-way data binding
  • Controllers and Modules
    Defining controllers and attaching properties/functions to the scope Organizing code using modules
  • Forms and Validation
    Implementing form controls and bindings Validating user inputs
  • Directives
    Exploring built-in directives Creating custom directives
  • Introduction to AngularJS
    Overview of AngularJS and its features Understanding the Model-View-Controller (MVC) architecture Setting up the development environment
  • Java Servlets
    Developing and deploying servlets. Handling HTTP requests and responses. Session tracking and management. Implementing filters and listeners
  • Introduction to J2EE
    Overview of J2EE architecture and components. Understanding J2EE containers and services. Significance of J2EE in enterprise application development.
  • Enterprise JavaBeans (EJB)
    Introduction to EJB and its types (Session Beans, Message-Driven Beans). Developing stateless and stateful session beans. Understanding EJB container services like transactions and security.
  • JavaServer Pages (JSP
    Creating dynamic web content with JSP. Understanding JSP directives, scripting elements, and actions. Using JavaBeans in JSP. Implementing JSP Expression Language (EL) and JSTL
  • Java Persistence API (JPA)
    Object-relational mapping (ORM) concepts. Defining entities and mapping them to database tables. Performing CRUD operations using JPA. Managing entity relationships
  • MVC Architecture
    Understanding the Model-View-Controller (MVC) design pattern Creating models, views, and controllers Routing mechanisms and URL patterns Data binding and validation techniques
  • Introduction to ASP.NET and .NET Framework:
    Overview of the .NET Framework and its components Understanding the Common Language Runtime (CLR) Setting up the development environment with Visual Studio Basics of C# programming language
  • Web API Development
    Building RESTful services using ASP.NET Core Web API Handling HTTP methods (GET, POST, PUT, DELETE) Content negotiation and formatting responses Securing APIs with authentication and authorization mechanisms
  • Entity Framework Core
    Introduction to Object-Relational Mapping (ORM) Setting up Entity Framework Core in ASP.NET Core projects Performing CRUD (Create, Read, Update, Delete) operations Handling relationships and migrations
  • ASP.NET Core Fundamentals
    Introduction to ASP.NET Core and its advantages over previous versions Setting up and configuring an ASP.NET Core project Understanding the ASP.NET Core request-response pipeline Middleware components and their roles
  • Java Syntax and Data Types
    Variables, data types, and type casting Operators and expressions Control flow statements: decision-making (if-else, switch) and loops (for, while, do-while)
  • Object-Oriented Programming (OOP) in Java
    Classes and objects Constructors and methods Access modifiers and encapsulation Inheritance, polymorphism, abstraction, and interfaces
  • Introduction to Java
    Overview of Java, its history, and features Setting up the Java Development Kit (JDK) and Integrated Development Environment (IDE) Understanding the Java Virtual Machine (JVM) and platform independence Writing and executing a simple Java program
  • Collections Framework
    Introduction to collections: List, Set, Map Working with ArrayList, HashSet, HashMap, etc. Iterators and the enhanced for-loop
  • Exception Handling
    Understanding exceptions and error handling Try-catch blocks, throw and throws keywords Creating custom exceptions
  • HTML (HyperText Markup Language)
    Understanding the structure and semantics of web pages. Learning to use various HTML tags and attributes to create content. Building forms, tables, and embedding multimedia elements.
  • CSS (Cascading Style Sheets)
    Styling web pages to enhance visual appeal. Implementing layouts, colors, fonts, and responsive designs. Utilizing frameworks like Bootstrap for streamlined styling.
  • Front-End Frameworks and Libraries
    Learning frameworks like React.js to build dynamic user interfaces. Managing state and props in component-based architectures.
  • JavaScript
    Adding interactivity to web pages. Understanding variables, data types, functions, and control structures. Manipulating the Document Object Model (DOM) to dynamically update content.
  • Back-End Development
    Understanding server-side programming with languages like Node.js or Python. Managing databases, server logic, and authentication processes.
  • Windows Forms and Event-Driven Programming
    Designing graphical user interfaces (GUIs) Handling events and delegates Implementing controls like buttons, text boxes, and labels Form navigation and user input validation
  • Object-Oriented Programming (OOP) in VB.NET
    Classes and objects Inheritance and polymorphism Encapsulation and abstraction Interfaces and abstract classes
  • Introduction to .NET Framework and Visual Studio
    Overview of the .NET Framework architecture Navigating the Visual Studio Integrated Development Environment (IDE) Understanding the Common Language Runtime (CLR) and .NET languages
  • Data Access with ADO.NET
    Connecting to databases Executing SQL queries and stored procedures Using DataSets, DataTables, and DataReaders Performing CRUD (Create, Read, Update, Delete) operations
  • VB.NET Language Fundamentals
    Data types, variables, and constants Operators and expressions Control structures: decision-making and loops Error handling and exception management
  • Test Planning and Documentation
    Developing test strategies and plans. Designing effective test cases and scenarios. Understanding the significance of test documentation in ensuring traceability and accountability.
  • Non-Functional Testing Techniques
    Performing performance testing, including load and stress testing. Assessing usability and compatibility of software across different platforms and devices.
  • Software Development Life Cycle (SDLC) and Testing
    Exploring various SDLC models like Waterfall, V-Model, and Agile. Integrating testing activities within these models. Understanding different levels of testing: unit, integration, system, and acceptance testing.
  • Test Planning and Documentation
    Developing test strategies and plans. Designing effective test cases and scenarios. Understanding the significance of test documentation in ensuring traceability and accountability.
  • Software Development Life Cycle (SDLC) and Testing
    Exploring various SDLC models like Waterfall, V-Model, and Agile. Integrating testing activities within these models. Understanding different levels of testing: unit, integration, system, and acceptance testing.
  • Introduction to Python
    Overview of Python and its applications. Setting up the Python environment. Writing and executing simple Python scripts. Understanding basic syntax and indentation.
  • Functions and Modules
    Defining and invoking functions. Function parameters and return values. Lambda functions. Importing and utilizing modules.
  • Control Flow
    Conditional statements: if, elif, and else. Loops: for and while. Control statements: break, continue, and pass.
  • Operators and Expressions
    Arithmetic, relational, logical, and bitwise operators. Operator precedence and associativity.
  • Data Types and Variables
    Exploring fundamental data types: integers, floats, strings, and booleans. Variable declaration and assignment. Type conversion and casting.
  • Introduction to WordPress and Content Management Systems (CMS)
    Understanding the concept and benefits of CMS. Differentiating between WordPress.com and WordPress.org. Exploring the history and evolution of WordPress.
  • Content Creation and Management:
    Differentiating between posts and pages. Utilizing the Block Editor (Gutenberg) for content creation. Organizing content with categories and tags.
  • Themes and Customization
    Selecting, installing, and activating themes. Customizing themes using the WordPress Customizer. Creating child themes for advanced customization.
  • Setting Up WordPress
    Installing WordPress on local and remote servers. Configuring basic settings and understanding the dashboard interface. Managing user roles and permissions.
  • Plugins and Functionality Enhancement
    Understanding the role of plugins in extending site functionality. Installing, activating, and configuring essential plugins. Exploring popular plugins for SEO, security, and performance optimization.
  • Scanning Networks
    Methods to detect live systems, open ports, and services to map out network infrastructures
  • Introduction to Ethical Hacking
    Understanding the fundamentals of ethical hacking, including its purpose, legal implications, and the role of an ethical hacker.
  • Vulnerability Analysis
    Assessing systems for known vulnerabilities using various tools and techniques.
  • Footprinting and Reconnaissance
    Techniques for gathering information about targets using passive and active methods to identify potential vulnerabilities
  • Enumeration
    Extracting detailed information such as user names, machine names, and network resources to identify potential entry points
  • Social Media Marketing
    Leveraging platforms like Facebook, Instagram, LinkedIn, and Twitter to promote products or services, engage with audiences, and build brand awareness
  • Fundamentals of Digital Marketing
    Understanding the digital marketing landscape, including various channels, platforms, and technologies. This module explores the evolution of digital marketing and its impact on consumer behavior
  • Content Marketing
    Creating and distributing valuable, relevant content to attract and engage a target audience. This includes blog posts, videos, infographics, and more.
  • Search Engine Optimization (SEO)
    Techniques to improve website visibility on search engines, focusing on keyword research, on-page and off-page optimization, and understanding search engine algorithms
  • Search Engine Marketing (SEM)
    Strategies involving paid advertising to increase website visibility on search engines, including Pay-Per-Click (PPC) campaigns and Google Ads
  • Support Vector Machines (SVM)
    Understanding the concept of hyperplanes and margins. Implementing SVMs for linear and non-linear classification tasks. Utilizing kernel functions to handle complex data structures.
  • Linear Models
    Linear regression for predicting continuous outcomes. Logistic regression for binary classification problems. Understanding the assumptions and limitations of linear models.
  • Introduction to Machine Learning
    Overview of machine learning concepts and applications. Understanding different types of learning: supervised, unsupervised, and reinforcement learning. Exploring the history and evolution of machine learning.
  • Decision Trees and Ensemble Methods
    Constructing decision trees for classification and regression tasks. Implementing pruning techniques to prevent overfitting. Exploring ensemble methods like bagging, boosting, and random forests to improve model performance.
  • Clustering and Dimensionality Reduction:
    Applying clustering algorithms such as K-means and hierarchical clustering for unsupervised learning. Implementing dimensionality reduction techniques like Principal Component Analysis (PCA) to simplify data.
  • Introduction to Data Analytics
    Understanding the role and responsibilities of a Data Analyst. Exploring the data analysis process, including data collection, cleaning, analysis, and visualization. Familiarity with the modern data ecosystem and the various roles within it.
  • Programming for Data Analysis
    Introduction to programming languages commonly used in data analysis, such as Python or R. Data manipulation and analysis using libraries like pandas (Python) or dplyr (R). Implementing basic algorithms for data processing.
  • Data Management and SQL
    Understanding relational databases and data warehousing concepts. Writing SQL queries to extract and manipulate data. Data cleaning and preprocessing techniques.
  • Data Visualization
    Principles of effective data visualization. Utilizing tools like Tableau and Power BI to create interactive dashboards. Designing charts and graphs to effectively communicate data insights.
  • Statistics and Probability
    Fundamental concepts of descriptive and inferential statistics. Probability distributions and their applications in data analysis. Hypothesis testing and confidence intervals.
  • Module 3: Frontend Development - JavaScript Frameworks
    JavaScript ES6+ Features (Arrow Functions, Promises, Modules) Introduction to React.js or Angular/Vue.js Components, Props, State Management (Redux/Context API) React Router and Hooks API Calls with Fetch/Axios
  • Module 2: Frontend Development - HTML, CSS, and JavaScript
    Advanced HTML and CSS (Flexbox, Grid, Media Queries) JavaScript Basics: Variables, Loops, Functions, DOM Manipulation Responsive Web Design Bootstrap and Tailwind CSS
  • Module 1: Introduction to Web Development
    Understanding Full Stack Development Overview of Frontend, Backend, and Databases Setting up the Development Environment Introduction to HTML, CSS, and JavaScript
  • Module 4: Backend Development - Server-side Programming
    Introduction to Node.js and Express.js RESTful API Development Authentication and Authorization (JWT, OAuth) Middleware and Routing
  • Module 5: Databases and ORM
    Relational Databases (MySQL, PostgreSQL) NoSQL Databases (MongoDB) Using ORM (Mongoose for MongoDB, Sequelize for SQL) CRUD Operations in Databases Database Security and Optimization
  • Data Wrangling and Preprocessing
    Data Collection and Cleaning Handling Missing Data and Outliers Feature Engineering Exploratory Data Analysis (EDA)
  • Foundations of Data Science
    Introduction to Data Science Role of Data Scientists Data Science Lifecycle Basics of Statistics and Probability
  • Data Visualization
    Principles of effective data visualization. Creating visualizations using tools like Matplotlib, Seaborn, or Tableau. Designing dashboards for interactive data exploration.
  • Data Wrangling and Exploration:
    Techniques for data cleaning and preprocessing. Handling missing data and outliers. Performing exploratory data analysis (EDA) to uncover patterns.
  • Machine Learning Fundamentals
    Supervised vs. Unsupervised Learning Regression and Classification Algorithms Clustering Techniques (K-Means, Hierarchical) Model Evaluation and Hyperparameter Tuning
Best Software training institute in Erode -IDM Teckpark
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Course Highlights and Why Data Science Course in Erode at IDM Techpark?

Comprehensive Data Science Options – IDM Techpark offers multiple data science tracks, including Machine Learning, Deep Learning, Artificial Intelligence, Big Data Analytics, Data Visualization, and NLP. You can choose the one that best suits your career goals.

Industry-Aligned Curriculum – The course is designed by industry experts to ensure a balanced focus on data analysis, machine learning, statistical modeling, and big data technologies, equipping you with essential skills for real-world data science applications.

Hands-on Learning Approach – IDM Techpark provides an intensive learning experience with practical, hands-on coding sessions to help you master programming languages effectively.

Regular Recap Sessions – After each class, students receive recap sessions to reinforce key concepts and ensure a strong understanding of data science principles, including data analysis, machine learning, and statistical modeling.

Flexible Batch Schedules – IDM Techpark offers flexible training schedules, including weekday, weekend, and fast-track batches, allowing learners to choose the best timing that suits their availability.

Real-Time Project Exposure – The training includes working on live projects to gain practical experience, ensuring that learners are industry-ready with hands-on project development skills.

100% Placement Assistance – IDM Techpark has strong tie-ups with over 3000 companies, providing extensive placement support and career guidance to help students secure high-paying jobs in the industry.

Data Science Course Objectives

  • Mastering Data Science Fundamentals – Gain a strong foundation in statistics, probability, and data manipulation, essential for extracting insights from data.

  • Proficiency in Data Analysis – Learn to analyze and visualize data using tools like Python, R, Pandas, NumPy, and Matplotlib.

  • Machine Learning Expertise – Explore supervised and unsupervised learning techniques, deep learning, and model deployment with hands-on experience in frameworks like TensorFlow and Scikit-learn.

  • Database Management & Big Data – Understand relational databases like MySQL and PostgreSQL, as well as big data technologies like Hadoop and Spark for efficient data processing.

  • Data Wrangling & Automation – Learn how to clean, preprocess, and automate data pipelines to streamline workflows and improve model performance.

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Data Science Course Trainer Profile 

Industry-Experienced Trainers – Our Data Science trainers are seasoned professionals with expertise in Machine Learning, Deep Learning, Artificial Intelligence, Big Data Analytics, and other cutting-edge technologies.

Comprehensive Student Guidance – With years of experience in mentoring aspiring data scientists, our trainers provide in-depth guidance to help students master data science concepts, tools, and techniques.

Hands-on Practical Training – Students receive real-time training in data analysis, machine learning, deep learning, and big data technologies, ensuring a strong foundation in data science.

​​Industry-Relevant Frameworks – Instructors familiarize students with leading data science frameworks, including TensorFlow, PyTorch, Scikit-Learn, Pandas, and other trending technologies.

Regular Progress Assessments – Trainers conduct periodic evaluations and assessments to track each student's learning progress and provide necessary improvements.

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Student Success Story of Data Science Course in Erode

Karthik, an MSc Computer Science graduate, initially worked in the technical support domain for a year. However, he soon realized that it wasn’t the right career path for him. Determined to advance his skills, he discussed his career goals with a friend and conducted thorough research to find the best learning opportunity that aligned with his passion for data science.

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After exploring various options, Karthik chose IDM Techpark’s Data Science Course, as it provided comprehensive training in Machine Learning, Deep Learning, Big Data Analytics, and Artificial Intelligence. Since he was already employed, he opted for weekend classes to effectively balance his job and studies. With dedication and enthusiasm, he attended every session, mastering essential tools and technologies such as Python, TensorFlow, Pandas, Scikit-Learn, SQL, and Power BI.

One of the key aspects of his learning journey was the hands-on experience he gained through real-world capstone projects. Under the mentorship of experienced trainers, he worked on data-driven projects that enhanced his analytical skills and problem-solving abilities. He also participated in hackathons and industry-relevant case studies, which helped him build a strong portfolio showcasing his expertise in data science.

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Upon completing the course, Karthik participated in placement training provided by IDM Techpark. The training included resume building, mock interviews, coding assessments, and data-driven problem-solving sessions, which helped him gain confidence in facing technical interviews.

With his newly acquired skills and strong preparation, Karthik successfully cleared interviews with NTT Data and ITSS Global. He ultimately accepted a Data Analyst role at NTT Data, with a salary package of 2.8 LPA.

 

This opportunity marked the beginning of his successful journey in the IT industry, allowing him to work on real-time data projects, predictive analytics, and business intelligence solutions.Karthik’s story is a testament to the power of upskilling and perseverance. His transition from a technical support role to a data science professional proves that with the right training and determination, career transformation is possible. Today, he continues to grow in his field, leveraging his data science expertise to drive meaningful insights and business decisions.

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right Career for you!

Data Science Certification Training in Erode

Upon successfully completing the Data Science Course in Erode at IDM Techpark, students will receive a certification from the institute. This certification serves as concrete proof of the industry-relevant skills and comprehensive knowledge acquired during the course. It validates their expertise in data analysis, machine learning, deep learning, big data analytics, and artificial intelligence, granting professional recognition and enhancing their credibility in the job market. Additionally, the certification reflects the student’s performance in practical training, real-world projects, and evaluative examinations, providing an overview of their proficiency in data science.

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The Data Science Course at IDM Techpark holds a strong reputation in the industry and is widely recognized by both national and international organizations. Adding this certification to your resume will significantly boost your career prospects, making you a competitive candidate for roles such as Data Analyst, Machine Learning Engineer, Business Analyst, AI Specialist, and more. The course is designed to align with industry best practices, leveraging cutting-edge technologies and an up-to-date curriculum to ensure students are job-ready.

 

Under the expert guidance of our faculty, students will develop the necessary skills to efficiently analyze data, build predictive models, and derive actionable business insights. The Data Science Course at IDM Techpark is structured to strengthen technical capabilities and refine the problem-solving skills of learners. Earning this certification will elevate your professional profile, unlocking exciting career opportunities in the rapidly growing field of data science and analytics.

Placement Session & Job Opportunities after completing Data Science Course in Erode

Growing Demand for Data Science Professionals – IDM Techpark, Erode

As technology advances at an exponential rate, businesses are constantly striving to stay ahead by harnessing the power of data. This digital transformation has resulted in a surge in demand for skilled Data Science professionals across a wide range of industries. Companies are increasingly relying on data-driven insights to optimize operations, predict trends, and make informed decisions.

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  • Data Science is no longer just an area for tech giants or research institutions; companies of all sizes are investing in analytics to stay competitive. With the ability to extract valuable insights from massive datasets, Data Scientists play a pivotal role in shaping business strategies and driving innovation.

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  • At IDM Techpark, Erode, we are dedicated to equipping students with the expertise required to excel in the high-demand field of Data Science.“Students will receive 100% placement assistance upon completing the Data Science Training at IDM Techpark.”​

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  • Data Scientists are highly sought after, with opportunities to work across various sectors including finance, healthcare, marketing, and e-commerce. With the continuous advancements in machine learning, AI, and big data technologies, the demand for qualified Data Science professionals is expected to keep growing.​

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  • By enrolling in the Data Science Course at IDM Techpark, Erode, students will gain hands-on experience, access to industry tools, and insights from industry experts, ensuring they are well-equipped to thrive in the competitive job market.Data Science professionals enjoy higher salaries, job stability, and abundant career opportunities, including the flexibility to pursue freelance projects or contribute to high-impact research.

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  • This program provides students with the necessary skills to develop expertise in statistical analysis, machine learning, and data visualization.Take the first step towards a rewarding career in Data Science with IDM Techpark, Erode – your gateway to success in one of the most promising fields of the future.

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