Advance Industry-Ready Java, Cloud & AI Engineering

Duration – 12 Days

Program Summary

Designed to strengthen programming fundamentals and enhance interview confidence for IT and product-based companies.


Java Programming & Coding Interview Preparation
  • Build Strong Object-Oriented Programming Fundamentals
  • Master Java Collection Framework
  • Crack Coding Rounds with Confidence
Python, Data Science & Artificial Intelligence
  • Build Strong Python Programming Fundamentals
  • Master Data Analysis & Machine Learning Techniques
  • Crack AI & Coding Interviews with Confidence
  • Gain Hands-On Expertise in Deep Learning & Generative AI
Cloud Computing & Deployment Essentials
  • Build Strong Cloud Computing Fundamentals
  • Master Core Cloud Services & Deployment Models
  • Crack Cloud Interviews with Confidence

Tools/Software/Hardware

  • Java JDK, Eclipse / IntelliJ IDEA
  • Python 3.x, NumPy, Pandas
  • AWS Free Tier / Sandbox Account, AWS CLI
  • Laptop/Desktop with a minimum 8 GB RAM and internet connectivity

Pre-requisites

  • Basic computer and operating system knowledge
  • Logical thinking and problem-solving skills
  • Familiarity with any programming language is an added advantage

Take away

  • Strong Programming & Problem-Solving skills for interviews
  • Hands-On Expertise in AI & Data Technologies
  • Cloud Deployment & Industry Readiness
  • LMS Access with Short notes and Coding practice platform
  • 1000+ Sample interview questions
  • Digital Videos for reference
  • Improved technical and interview readiness

Variables, Data Types & Control Statements

<p?Topics

  • Variables in Java
    • Local, instance, and static variables
  • Data Types
    • Primitive data types
    • Non-primitive data types (String, arrays – intro)
  • Operators
    • Arithmetic, relational, logical, assignment
    • Increment/decrement operators
  • Control Statements
    • Conditional statements: if, if-else, switch
    • Looping statements: for, while, do-while
    • break and continue

<pHands-on

  • Write programs using different data types
  • Implement decision-making programs
  • Loop-based programs (number patterns, sum, factorial, etc.)
  • Practice operator precedence examples

OOP Concepts & Arrays

Topics

  • Object-Oriented Programming Concepts
    • Class and Object
    • Object creation and memory allocation
  • Object Class (overview)
    • toString(), equals(), hashCode()
  • Arrays
    • Single-dimensional arrays
    • Multi-dimensional arrays
    • Array initialization and traversal
  • Real-world examples using OOP concepts

Hands-on

  • Create classes and objects
  • Use object reference variables
  • Write programs using arrays
  • Implement simple OOP-based applications

Keywords & Inheritance Concepts

Topics

  • Static Keyword
    • Static variables
    • Static methods
    • Static blocks
  • this Keyword
    • Referring to current object
    • Constructor chaining
  • super Keyword
    • Accessing parent class members
    • Constructor calling
  • Inheritance
    • Types of inheritance in Java
    • Method overriding
  • Abstraction
    • Abstract classes
    • Abstract methods
  • Encapsulation
    • Access modifiers
    • Getters and setters

Hands-on

  • Programs using static members
  • Demonstrate this and super keywords
  • Implement inheritance examples
  • Create abstract classes and methods
  • Apply encapsulation using access modifiers

Cloud – AWS

AWS fundamentals

Topics

  • Introduction to the Course
  • What is Cloud Computing and AWS?

Hands-On Practice

  • Free Tier vs Sandbox
  • AWS Account Overview
  • Create your AWS Account
  • [HOL] Configure Account and Create a Budget
  • [HOL] Install Tools and AWS CLI
  • Introduction
  • The AWS Global Infrastructure
  • The AWS Shared Responsibility Model
  • Application Programming Interfaces (APIs)
  • AWS Pricing Fundamentals
  • The 6 Advantages of Cloud Computing

AWS Authentication and Access Control

Topics

  • AWS Identity and Access Management (IAM)
  • [HOL] Creating IAM Users and Groups
  • IAM Roles and Policies
  • [HOL] Switching IAM Roles
  • IAM Identity Center
  • [HOL] IAM Identity Center in Action

Amazon EC2, Auto Scaling and Load Balancin

Topics

  • Server Virtualization
  • Scaling Up vs Scaling Out
  • High Availability and Fault Tolerance
  • Amazon EC2 Overview
  • [HOL] Launching Amazon EC2 Instances

Amazon VPC

Topics

  • The OSI Model
  • Routers, Switches and Firewalls
  • IP Addressing
  • Amazon Virtual Private Cloud (VPC)
  • [HOL] Create a Custom VPC
  • Security Groups and Network ACLs
  • Block vs File vs Object Storage
  • Amazon EBS and Instance Stores
  • [HOL] Create and Attach an EBS Volume
  • [HOL] EBS Snapshots and AMIs
  • Amazon Elastic File System (EFS)

Artificial Intelligence & Machine Learning (AI/ML)

AI & Machine Learning Fundamentals

Topics

  • AI vs ML vs Deep Learning
  • Types of machine learning
  • ML workflow
  • Role of AI in Embedded & IoT
  • Industry use cases

Hands-on

  • Analyse datasets for ML suitability
  • Identify ML type for given problem statements
  • Map IoT problems to ML solutions

Core Machine Learning Algorithms

Topics

  • Linear regression
  • Logistic regression
  • Decision trees
  • KNN algorithm
  • Model evaluation

Hands-on

  • Train a regression model
  • Perform classification on sample dataset
  • Evaluate model accuracy
  • Compare algorithm performance

Python for AI/ML & Data Processing

Topics

  • Python basics for ML
  • Working with CSV and log files
  • Data cleaning and preprocessing
  • NumPy and Pandas basics
  • Exploratory data analysis

AI/ML Integration, Edge AI & Use Cases

Topics

  • ML model deployment concepts
  • Edge AI fundamentals
  • Predictive maintenance
  • AI integration with IoT
  • Industry expectations

Hands-on

  • End-to-end ML case study
  • Integrate ML output with IoT data
  • Predict anomalies using ML
  • Final review & interview discussion

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