Programming Courses - Advanced

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Course Name: Build Web Applications using Spring Boots

  • Duration: 60 Hours each
  • Who Should Do This: Aspiring Backend Developers, Java Developers transitioning to Spring Boot, Final-year students or working professionals who want to build scalable web applications, Anyone interested in REST APIs and enterprise web development.
  • Prerequisites: Strong understanding of Java fundamentals, Familiarity with OOP, Exception Handling, Collections, and JDBC, Basic knowledge of HTML/CSS and SQL.
  • Career Options After Learning: Spring Boot Developer, Java Backend Developer, REST API Developer, Full Stack Developer (with Frontend skills), Software Engineer – Java/Spring.
  • Road Map:
    1. Spring Boot Basics
    2. REST APIs with Spring Boot
    3. Data Persistence with Spring Data JPA
    4. Introduction to ORM and Hibernate
    5. Advanced API Features
    6. Exception Handling
    7. Security and Testing
    8. Final Capstone Project and Deployment

Course Name: Build Dynamic Websites using ASP.NET

  • Duration: 90 Hours
  • Who Should Do This: Beginners in web development with basic programming knowledge. Students or professionals looking to learn dynamic website development using Microsoft technologies. Developers familiar with HTML/CSS who want to explore ASP.NET.
  • Prerequisites: Basic understanding of HTML, CSS, and JavaScript. Familiarity with C# programming (optional but helpful). Visual Studio installed (or Visual Studio Code with required extensions).
  • Career Options After Learning: Java Developer, Android Developer, Backend Developer.
  • Road Map:
    1. Introduction to ASP.NET
    2. C# Basics Refresher
    3. Web Forms & Page Lifecycle
    4. ASP.NET Controls
    5. Database Connectivity (ADO.NET)
    6. ASP.NET MVC (Optional Advanced Module)
    7. Security Authentication, Authorization, Forms Authentication
    8. Hosting & Deployment Deploying on IIS or Azure, Web.config settings
    9. Capstone Project - dynamic website

Course Name: Comprehensive Android App Development

  • Duration: 180 Hours
  • Who Should Do This: Beginners and students passionate about creating mobile apps. Developers seeking to specialize in Android app development. Entrepreneurs and tech enthusiasts who want to build their own apps.
  • Prerequisites: Basic understanding of programming concepts (Java or Kotlin preferred). Familiarity with object-oriented programming is advantageous but not mandatory.
  • Career Options After Learning: Android App Developer, Mobile App Designer, Freelance App Developer, Software Engineer specializing in mobile solutions
  • Road Map:
    1. Fundamentals of Android Development : Introduction to Android Studio and development environment setup.
    2. Basics of Java/Kotlin for Android.
    3. Understanding Android architecture and components.
    4. UI/UX design fundamentals (layouts, views, themes).
    5. Core Android Development : Activity lifecycle and fragment management.
    6. Event handling and navigation patterns.
    7. Data storage and management (SQLite, SharedPreferences).
    8. API integration and consuming web services (REST APIs).
    9. Advanced Android Features : Push notifications and background tasks.
    10. Animations and custom views.
    11. Working with location-based services and Google Maps.
    12. Security best practices for Android apps.
    13. Final Project and Deployment : Design and develop a fully functional Android app, Testing and debugging. App deployment on the Google Play Store.

Course Name: Data Structures and Algorithms

  • Duration: 90 Hours
  • Who Should Do This: Students preparing for competitive programming or technical interviews.
    Programmers who want to enhance their problem-solving skills.
  • Prerequisites: Basic knowledge of any programming language (C, C++, Java, or Python).
    Logical thinking and a basic understanding of algorithms
  • Career Options After Learning: Software Developer, Algorithm Engineer, Competitive Programmer, Technical Interview Coach.
  • Road Map:
    1. Introduction to DSA: Why it matters in programming.
    2. Arrays, Strings, and Linked Lists.
    3. Basic Searching (Linear Search, Binary Search) and Sorting (Bubble Sort, Quick Sort).
    4. Stacks and Queues: Applications and implementations.
    5. Recursion: Understanding and solving problems recursively.
    6. Trees: Binary Trees, Binary Search Trees, and Tree Traversals.
    7. Graphs: Representation, BFS, DFS, and shortest path algorithms (Dijkstra’s, Floyd-Warshall).
    8. Advanced Searching and Sorting algorithms.
    9. Dynamic Programming: Problem-solving and memoization techniques.
    10. Hashing and Hashmaps.
    11. Advanced Data Structures: Tries, Heaps, Segment Trees, and Disjoint Set Union (DSU).
    12. Final Project: Solve a real-world problem using efficient algorithms and data structures.