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How Curriculum works?

Our curriculum is designed to provide comprehensive, hands-on learning experiences tailored to your goals. It combines theoretical knowledge with practical application, ensuring you develop the skills needed for real-world success. Whether you're starting from scratch or enhancing your expertise, our courses are structured to help you progress at your own pace.

  • Industry-Relevant Content
  • Hands-on Learning
  • Flexible Structure
  • Expert-Led Sessions
  • Week 1: Introduction to Python Backend Development
  • Week 2: Web Frameworks in Python – Flask or Django
  • Week 3: Working with Databases in Python (SQL and NoSQL)
  • Week 4: Authentication and Authorization
  • Week 5: Introduction to Node.js and Express
  • Week 6: Working with Databases in Node.js
  • Week 7: Full-Stack Integration with Frontend
  • Week 8: Building a Full-Stack Application
  • Week 9: Introduction to AWS for Backend Deployment
  • Week 10: Deploying Python Application on AWS
  • Week 11: Deploying Node.js Application on AWS
  • Week 12: CI/CD Pipeline, Scaling, and Final Project
  • Week 1: Introduction to Python and MySQL
  • Week 2: Connecting Python to MySQL
  • Week 3: CRUD Operations
  • Week 4: Advanced Querying and Joins
  • Week 5: Data Modeling and Database Design
  • Week 6: Stored Procedures, Functions, and Transactions
  • Week 7: Security and Performance Optimization
  • Week 8: Project Week and Certification
  • Week 1: Introduction to Business Analytics
  • Week 2: Data Analysis with Excel
  • Week 3: Introduction to Python for Analytics
  • Week 4: SQL for Data Retrieval
  • Week 5: Data Visualization with Tableau
  • Week 6: Statistical Analysis and Hypothesis Testing
  • Week 7: Introduction to Machine Learning
  • Week 8: Time Series Analysis
  • Week 9: Advanced Machine Learning Models
  • Week 10: Data-Driven Decision Making
  • Week 11: Capstone Project
  • Week 12: Certification and Career Preparation
  • Week 1: Introduction to Machine Learning and AI
  • Week 2: Data Preprocessing and Feature Engineering
  • Week 3: Supervised Learning I (Regression)
  • Week 4: Supervised Learning II (Classification)
  • Week 5: Unsupervised Learning
  • Week 6: Neural Networks and Deep Learning
  • Week 7: Advanced Deep Learning
  • Week 8: Natural Language Processing (NLP)
  • Week 9: Reinforcement Learning
    Week 10: AI in Practice
  • Week 11: Capstone Project
  • Week 12: Certification and Career Preparation
  • Week 1: Introduction to Statistics
  • Week 2: Descriptive Statistics
  • Week 3: Probability Basics
  • Week 4: Probability Distributions
  • Week 5: Inferential Statistics I
  • Week 6: Inferential Statistics II
  • Week 7: Correlation and Regression
  • Week 8: Non-Parametric Statistics
  • Week 9: Multivariate Analysis
  • Week 10: Time Series Analysis
  • Week 11: Capstone Project
  • Week 12: Certification and Career Preparation
  • Week 1: Excel Essentials
  • Week 2: Data Analysis Basics
  • Week 3: Advanced Formulas and Functions
  • Week 4: Data Visualization
  • Week 5: Pivot Tables and Power Query
  • Week 6: Advanced Data Tools
  • Week 7: Macros and VBA Basics
  • Week 8: Advanced VBA
  • Week 9: Power Pivot and DAX
  • Week 10: Data Integration
  • Week 11: Capstone Project
  • Week 12: Certification and Career Preparation
  • Week 1: Introduction to Web Development
  • Week 2: Advanced HTML and CSS
  • Week 3: Introduction to JavaScript
  • Week 4: Frontend Frameworks (React.js)
  • Week 5: Backend Development (Node.js)
  • Week 6: Database Integration (MongoDB)
  • Week 7: Authentication and Security
  • Week 8: Advanced Frontend Development
  • Week 9: Deployment and Hosting
  • Week 10: Advanced Topics in Web Development
  • Week 11: Capstone Project
  • Week 12: Certification and Career Preparation