What will you learn in Advanced Java Certification Training Course
Work with advanced Java EE APIs including Servlets, JSP, and JDBC for enterprise applications
Leverage Java annotations and design patterns to write clean, maintainable code
Implement robust exception handling, logging with Log4j, and regular expressions for input validation
Utilize collections and generics for efficient data management
Build multithreaded applications and manage concurrency in Java
Program Overview
Module 1: Java Basics & Environment Setup
⏳ 45 minutes
Topics: JDK installation, IDE configuration, basic syntax, data types
Hands-on: Write and run “Hello World,” explore primitive and reference types
Module 2: Classes, Interfaces & Annotations
⏳ 45 minutes
Topics: Class structure, interfaces, annotations, access modifiers
Hands-on: Define classes and interfaces, apply built-in annotations
Module 3: Polymorphism & Event Handling
⏳ 1 hour
Topics: Method overloading/overriding, event listeners, inner classes
Hands-on: Create polymorphic examples and simple GUI event handlers
Module 4: Exceptions, Log4j & Regex
⏳ 45 minutes
Topics: Checked vs. unchecked exceptions, Log4j setup, regular expressions
Hands-on: Implement try–catch blocks, configure Log4j, validate input with regex
Module 5: Collections & Generics
⏳ 30 minutes
Topics: List, Set, Map interfaces; generic classes and methods
Hands-on: Manipulate collections and write a generic utility class
Module 6: File I/O & Concurrency
⏳ 30 minutes
Topics: File streams, NIO; threads, executors, synchronization
Hands-on: Read/write files and build a multithreaded file processor
Module 7: JDBC & Database Connectivity
⏳ 1 hour
Topics: JDBC architecture, connection pooling, CRUD operations
Hands-on: Connect to a sample database and perform SQL queries from Java
Module 8: Network Programming
⏳ 45 minutes
Topics: Socket API, server/client models, URL and HTTP connections
Hands-on: Implement a simple chat server and client
Module 9: Hadoop Ecosystem Introduction
⏳ 45 minutes
Topics: HDFS, MapReduce overview, YARN, ecosystem components
Hands-on: Write a basic MapReduce job and run it on a local cluster
Module 10: Code Robustness & Optimization
⏳ 45 minutes
Topics: Refactoring best practices, performance tuning, memory management
Hands-on: Profile and optimize a sample Java application
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Job Outlook
As of July 1, 2025, the average annual salary for a Java Developer in the U.S. is $105,982
Employment of software developers, including Java roles, is projected to grow 21% through 2030 according to BLS
Java expertise is in high demand across industries like finance, e-commerce, and big data
Opportunities include backend developer, enterprise architect, and Hadoop engineer
Specification: Advanced Java Certification Training
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FAQs
- Java is widely used with Hadoop, Spark, and other big data frameworks.
- JDBC and multithreading skills allow efficient data processing pipelines.
- Advanced collections and generics improve memory and performance handling.
- Java APIs integrate with HDFS for large-scale data storage and retrieval.
- Skills in Java EE and concurrency enable enterprise-grade big data solutions.
- Design patterns improve code maintainability and readability.
- Facilitate reuse of tried-and-tested architectural solutions.
- Help in building modular and loosely-coupled enterprise systems.
- Support large-team collaboration by standardizing code approaches.
- Enhance debugging and refactoring efficiency in complex applications.
- Multithreading enables better resource utilization in cloud-hosted Java apps.
- Supports asynchronous processing for APIs and microservices.
- Thread-safe operations are critical for distributed systems.
- Executors and synchronization help manage high-volume cloud requests.
- Concurrency knowledge aids in scaling applications efficiently on platforms like AWS or Azure.
- Java’s Socket API supports TCP/UDP communication for client-server apps.
- Can build REST or SOAP APIs for web and mobile applications.
- URL and HTTP connection classes simplify web service integration.
- Enables chat apps, file transfers, and real-time communication systems.
- Networking knowledge pairs with concurrency for scalable backend solutions.
- Backend or full-stack Java developer in enterprise applications.
- Big data engineer using Hadoop, Spark, or Kafka ecosystems.
- Cloud solutions developer with scalable Java-based services.
- Enterprise architect designing modular, robust software systems.
- Technical consultant or trainer for Java-centric projects and workshops.

