Machine Learning course syllabus

Machine Learning Language Environment

The Machine Learning (ML) Language Environment requires a stack that strikes a compromise between ease of deployment, library support, and performance.

Object Oriented
Platform Independent
Automatic Memory Management
Compiled / Interpreted Approach
Robust
Secure
Dynamic Linking
Multi Threaded
Built-In Networking

Machine Learning Fundamentals

A kind of artificial intelligence called machine learning (ML) allows computers to learn from data without the need for explicit programming.

Data Types
Operators
Control Statements
Arrays
Enhanced For-Loop
Enumerated Types
Static Import
Auto Boxing
C-Style Formatted I/O
Variable Arguments

Essentials Of Object-Oriented Programming

The paradigm of object-oriented programming, or OOP, is predicated on the idea of "objects," which comprise both code and data. By emulating real-world structures, it seeks to make software more scalable, reusable, and maintainable.

Object And Class Definition
Using Encapsulation To Combine Methods And Data In A Single Class
Inheritance And Polymorphism

Writing Machine Learning Classes

Real-time projects and career-ready abilities were the main focus of practical machine learning courses.

Encapsulation
Polymorphism
Inheritance
OOP In Machine Learning
Class Fundamentals
Using Objects
Constructor
Garbage Collection
Method Overloading
Method Overriding
Static Members
Understanding Interface
Using Interfaces Class

Packages

Adaptable training programs with practical instruction and real-time machine learning projects. Packages for machine learning that are reasonably priced and build useful, career-ready abilities.

Why Packages
Understanding Classpath
Access Modifiers And Their Scope

Exception Handling

properly managing runtime problems to guarantee seamless program execution and avoid application crashes.

Importance Of Exception Handling
Exception Propagation
Exception Types
Using Try And Catch
Throw, Throws, Finally
Writing User Defined Exceptions

I/O Operations In Machine Learning

effectively managing data input and output for ML model deployment, testing, and training.

Byte Oriented Streams
File Handling
Readers And Writers

Multi Threaded Programming

Multiple tasks can run concurrently thanks to multi-threaded programming, which enhances performance, efficiency, and application execution speed.

Introduction To Multi-Threading
Understanding Threads And Its States
Machine Learning Threading Model
Thread Class And Runnable Interface
Thread Priorities
Thread Synchronization
Inter Thread Communication
Preventing Deadlocks

Developing Machine Learning APPS

Creating production-ready It is necessary to transition from basic Jupyter notebooks to structured, scalable, and maintainable software structures for machine learning applications.

Defining A Solution Without Writing Code
Organizing A Concept Solution
Creating A Program Skeleton
Defining Error Checking Requirements
Introduction To Application Security

Network Programming

Writing programs that use common protocols to communicate with one another via a network is known as network programming.

Introduction To Networking
Inet Address
URL
TCP Socket And Server Socket
UDP Socket
Developing A Chat Application

Machine Learning Util Package / Collections Framework

Transitioning from experimental notebooks to production-grade pipelines requires either a bespoke Collections Framework or a Machine Learning Utility Package.

Collection And Iterator Interface
Enumeration
List And ArrayList
Vector
Comparator
Set Interface And SortedSet
Hashtable
Properties

Generics

Writing classes, structures, and functions that can operate with any data type while upholding strict type safety is made possible by generics, a potent programming feature.

Introduction To Generics
Using Built-In Generics Collections
Writing Simple Generic Class
Bounded Generics
Wild Card Generics

Inner Classes

Inner classes, also known as nested classes, are a potent structural tool in machine learning development that are used to contain assistance functionality particular to a parent model.

Nested Top Level Classes
Member Classes
Local Classes
Anonymous Classes

Abstract Window Toolkit

Java's first platform-independent windowing, graphics, and UI widget toolkit is called the Abstract Window Toolkit (AWT)

Graphics
Color And Font
AWT Components/Controls
Event Handling And Layouts

Swing Programming

A robust framework for creating Graphical User Interfaces (GUIs) is Java Swing. Swing components are "lightweight" and platform-independent because they are written solely in Java, in contrast to its predecessor AWT.

Introduction To Swing And MVC Architecture
Light Weight Component
Swing Hierarchy
Atomic Components E.G. JButton, JList And More
Intermediate Container E.G. JPanel, JSplitPane And More
Top-Level Container E.G. JFrame And JApplet
Swing Related Events

Regular Expressions

Strong patterns called regular expressions, or Regex, are used to match, search, and work with text strings.

Introduction
Match function
Search function
Grouping
Matching at Beginning or End
Match Objects
Flags
Exercise

.: In addition to object-oriented programming ideas, this machine learning coursework provides a solid foundation in ML language environments and basic principles. Students have practical experience in developing machine learning classes, packages, exception handling, I/O operations, multithreading, and network programming. ML app development, collections framework, generics, inner classes, regex, AWT, Swing, and useful image-based applications are also covered in this course.

Excellent Content with a Focus on Job Opportunities (Student Perspective)