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Backend Development Programs

Principal Component Analysis in under 20 minutes

Course Description

Master Backend Development course is 3 month guided program is designed for beginner and professionals to up skills and growth your carrer. You will get good hands on experience of building real word projects, etc.
JavaA2Z designed some courses for students and beginners and some courses are technolgoies combination courses which are designed for professionals to upskill and grow in carrier. you can choose any course(s) and register for free Demo classes respectively. If you have any queries please go through FAQ(s) or share your details for mentorship.

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for first 30 students

Course Overview

  • The core concepts of machine learning: Understand the different types of machine learning (supervised, unsupervised, reinforcement), common algorithms, and how they work.

  • Data preparation and preprocessing: Learn how to clean, organize, and transform your data into a format suitable for machine learning algorithms.

  • Model building and training: Explore various algorithms like linear regression, decision trees, and k-nearest neighbors, and learn how to train them on your data.

  • Model evaluation and optimization: Discover techniques to assess the performance of your models and improve their accuracy.

  • Real-world applications: See how machine learning is used in various industries, from healthcare and finance to marketing and social media.

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       Benefits of taking this course:

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  • Develop a strong foundation in machine learning: Gain the knowledge and skills needed to explore further and specialize in specific areas of AI.

  • Boost your career prospects: Machine learning skills are highly sought after in today's job market, making you a more valuable candidate.

  • Apply machine learning to solve real-world problems: Learn how to use machine learning to analyze data, make predictions, and automate tasks.

  • Join a vibrant community: Connect with other learners and experts, share knowledge, and learn from each other.  

 

      This course is perfect for:

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  • Beginners with no prior knowledge of machine learning.

  • Professionals looking to add machine learning skills to their resume.

  • Anyone with an interest in artificial intelligence and its applications.

       Enroll today and take your first step into the fascinating world of machine learning!

Backend Development Program (Syllabus):

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A syllabus for a comprehensive backend development program typically covers a range of topics, including programming languages, databases, frameworks, tools, and best practices. Below is a sample syllabus for a backend development program:

Module 1: Introduction to Backend Development

  • Overview of backend development

  • Client-server architecture

  • Role of backend in web development

Module 2: Programming Languages

  • Introduction to programming languages commonly used for backend development (e.g., Java, Python, Node.js)

  • Syntax, data types, and control structures

  • Best practices for writing clean and efficient code

Module 3: Database Fundamentals

  • Relational database management systems (e.g., MySQL, PostgreSQL)

  • SQL basics: querying, filtering, sorting, joining tables

  • Database design principles: normalization, indexing

Module 4: Introduction to NoSQL Databases

  • Overview of NoSQL databases (e.g., MongoDB, Cassandra)

  • Document, key-value, and columnar databases

  • Use cases for NoSQL databases

Module 5: RESTful APIs

  • Understanding Representational State Transfer (REST)

  • Designing RESTful APIs

  • Implementing CRUD operations using RESTful principles

Module 6: Web Frameworks

  • Introduction to backend frameworks (e.g., Spring Boot for Java, Django for Python, Express.js for Node.js)

  • MVC architecture and routing

  • Hands-on project: building a simple web application using a chosen framework

 

Module 7: Authentication and Authorization

  • Authentication methods: token-based, session-based

  • Authorization mechanisms: role-based access control (RBAC), OAuth

  • Securing APIs and endpoints

 

Module 8: Data Serialization and Deserialization

  • Introduction to data serialization formats (e.g., JSON, XML)

  • Serializing and desterilizing data between frontend and backend

  • Working with RESTful APIs to send and receive data

Module 9: Caching and Performance Optimization

  • Understanding caching mechanisms

  • Implementing caching strategies using tools like Redis or Memcached

  • Performance optimization techniques for backend applications

Module 10: Testing and Debugging

  • Writing unit tests and integration tests

  • Debugging backend applications

  • Test automation tools and frameworks

Module 11: Deployment and DevOps

  • Continuous Integration/Continuous Deployment (CI/CD) pipelines

  • Deployment strategies (e.g., Blue/Green deployment, canary deployment)

  • Containerization and orchestration (e.g., Docker, Kubernetes)

Module 12: Scalability and Monitoring

  • Strategies for scaling backend applications

  • Monitoring backend performance and health

  • Tools for monitoring and logging (e.g., Prometheus, ELK stack)

Module 13: Security Best Practices

  • Common security vulnerabilities and threats

  • Best practices for securing backend applications

  • Data encryption, input validation, and parameterized queries

Module 14: Real-world Project

  • Capstone project: building a scalable, secure, and performance t backend application from scratch

  • Implementing features such as user authentication, data persistence, and API endpoints

  • Deployment and testing of the project in a production-like environment

 

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