Machine Learning Course Syllabus
Step into the world of Machine Learning with the Machine Learning Course Syllabus at SLA Institute. This program is really easy to understand, even if you are new to Machine Learning. You will learn how Machine Learning works and how machines use data to make decisions. The Machine Learning Course Syllabus covers things like getting data ready, regression, classification, and basic deep learning using Python tools. We use examples and projects to help you learn Machine Learning. The Machine Learning Course Syllabus at SLA Institute helps you build a foundation in Machine Learning and gets you ready for a great career in Machine Learning and data science.
Course Syllabus
Download SyllabusMachine Learning Language Environment
- Object Oriented
- Platform Independent
- Automatic Memory Management
- Compiled / Interpreted Approach
- Robust
- Secure
- Dynamic Linking
- Multi Threaded
- Built-In Networking
Machine Learning Fundamentals
- 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
- Object And Class Definition
- Using Encapsulation To Combine Methods And Data In A Single Class
- Inheritance And Polymorphism
Writing Machine Learning Classes
- 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
- Why Packages
- Understanding Classpath
- Access Modifiers And Their Scope
Exception Handling
- 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
- Byte Oriented Streams
- File Handling
- Readers And Writers
Multi Threaded Programming
- 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
- Defining A Solution Without Writing Code
- Organizing A Concept Solution
- Creating A Program Skeleton
- Defining Error Checking Requirements
- Introduction To Application Security
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
- Collection And Iterator Interface
- Enumeration
- List And ArrayList
- Vector
- Comparator
- Set Interface And SortedSet
- Hashtable
- Properties
Generics
- Introduction To Generics
- Using Built-In Generics Collections
- Writing Simple Generic Class
- Bounded Generics
- Wild Card Generics
Inner Classes
- Nested Top Level Classes
- Member Classes
- Local Classes
- Anonymous Classes
Abstract Window Toolkit
- Graphics
- Color And Font
- AWT Components/Controls
- Event Handling And Layouts
Swing Programming
- 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
- Introduction
- Match function
- Search function
- Grouping
- Matching at Beginning or End
- Match Objects
- Flags
- Exercise
In conclusion, the Machine Learning Course Syllabus at SLA Institute gives you the knowledge and skills to work with data and build smart models. You get hands-on training with tools used in the industry. This helps you understand how machine learning solves problems better and find jobs in data science and AI. The Machine Learning Course Syllabus at SLA Institute is very helpful. You learn machine learning. Get good at it. The skills you gain can lead to a career in data science and AI, with Machine Learning.
