OS Concepts: Introduction to Operating System, Processes Architecture, Multithreading, CPU Scheduling and Synchronization, Memory management

Linux Programming: Introduction Linux Architecture, Basic Commands, Linux Shell Programming

   Need of RDBMS Client/Server, Computing Codd’s Rules, Data Models, Normalization Techniques, ER Diagrams, Data Flow Diagrams, SQL: DDL, DML, DCL, Sub query Joins, SQL Functions, Stored Procedures, NoSQL concepts, Introduction to MongoDB.

  

Introduction to STL (Standard Type Libraries), Define the problem, Find Creative Solutions using creativity tools, Evaluate and Select solution, Implementing Decisions, Algorithm Design and Analysis, Analyzing time and space complexity.

Basic Data Structures: Arrays, Stacks, Queues (Circular Queues, Priority Queues, De-queues), Linked lists (Single, Double and Circular Linked Lists),

Trees and Applications: Tree traversals, Ordered Trees, Binary trees, Complete Binary Trees, Search trees, Binary Search Trees, Self-Balancing Trees

Searching & sorting algorithms: Sequential Search, Binary Search, Selection sort, Insertion sort, Bubble sort, Heap sort, Merge sort, Quick sort, Hash Functions and Hash Tables

Graph and Applications: Graph traversal algorithms (BFS, DFS), Dijkstra’s Algorithm, Bellman Ford Algorithm, All-pairs shortest path, Floyd-Warshall algorithm, Johnson's algorithm, Maximum flow algorithms, Ford-Fulkerson algorithms, Spanning Trees.

  

OOPS: Introduction to OOPs concepts, Classes and Objects, Access specifiers, Abstraction, Data hiding, Encapsulation, Polymorphism and Inheritance.

Core Java: Java 8 and its features, Introduction to JDK, JRE & JVM, JVM Architecture Overview, Language Fundamentals, Arrays. Classes & Objects, Fields & Methods, Constructors, method overloading and overriding, super and this keyword, static fields & methods. Packages and access rules, Inheritance and its types, Polymorphism, Abstract classes and Interfaces, Exception Handling, String and Wrapper classes, Generics and Collections, File Handling and Multithreading, Reflection & Annotations, JDBC.

  

ORM Concepts, JPA, Spring Data architecture, Entity relations and ID generators, Transaction management, Spring Data CRUD API & Query Methods, JPQL, Spring framework, Spring Boot, IOC & Dependency Injection, Spring Beans using Annotation config, Autowiring, Web application using Controller, Service & Repository layers, RESTful web service using Spring Boot.

  

1. Android Programming(90 Hrs)

Introduction of Android and its architecture, Android SDK features, Introduction to Kotlin Programming, Android activities, lifecycle and callback methods, Android UI design fundamentals, Layouts, Intents, Toast, Adapters, Dialogs , Animations, Notification and Media Player, Material Design, Fragments , fragments lifecycle and callback methods.List View and Recycler view, ActionBar, ToolBar, Menus and Popups, View Pager, Navigation Drawer Android Storage: SQLite database,Content Providers, Multitasking in Android, Android Location based services, Android Sensors, Using blue tooth and telephony Consuming REST API , JSON Parsing, Retrofit Libraries, Integration with Social Networking like Facebook, Twitter etc , Design Patterns- MVP and MVVM, Publish application on play store.

2. iOSProgramming(60 Hrs)

iOS History and iOS Architecture, Swift Programming Basics, iOS app development: XCode, UIKit, Controllers, Storyboard, Basic UI Controls, UITextField, UIButton, UILabel, UISegmentedControl, Controller Life Cycle, UINavigationController, UIAlertController, Advance UI Development, Local Storage, REST API Integration: Multithreading and GCD, CocoaPods, JSON GET POST Handling, Alamofire, SwiftyJSON.

  

Introduction to Hybrid development, Hybrid application frameworks, HTML 5.0, CSS, JavaScript, jQuery, Node.js, Express, Responsive Web Design, React Native: Introduction to React Native and its architecture.

Props and states, Inline and External styling, React native binding, handling events and user inputs, validations, using network in app, Timers, Animations and Gesture Support, Consuming web services, Publishing App to Play Store and App Store.

   Machine Learning Fundamentals, supervised vs. unsupervised learning, ML used in Mobile Apps, Mobile ML Frameworks: TensorFlow Lite (Android) & Core ML (iOS), Data Handling and Preprocessing for Mobile. Capture data from the mobile devices/sensors & prepare for ML models. Using pre-trained models with TensorFlow Lite/Core ML (iOS) for common tasks, Converting TensorFlow/ML models to TensorFlow Lite/Core ML format using IDE, Using models in mobile for image processing, sensor data, text. Optimizing, Testing, and Deploying ML Models on Mobile, Model Optimization for Mobile devices by quantization, pruning, and reducing model size, Personalized User Experiences using ML (recommendations), Real-time feedback loops, Speech and Text Recognition, Using NLP to analyze text inputs in mobile apps, Voice controlled Apps.

  

 Aptitude: Percentage, Profit & Loss, Ratio & Proportion, Average, Mixture & Allegation, Simple Interest & Compound Interest, Seating Arrangements (Linear & Circular), Ages, Time, Speed & Distance, Trains, Boats & Streams, Time & Work, Wages (Man days), Pipes & Cisterns, Clocks, Permutations & Combinations, Probability, 

  

Software: A Process, Various Phases in s/w development Software life cycle agile model (Self Study of other models), Introduction to Coding Standards Software Quality Assurance.