Full Stack Development (Python)
What is a Full Stack ?
Full-stack development refers to the practice of developing both the front end (client-side) and back end (server-side) of a web application. This means that a full-stack developer is capable of working on both the "front end" (the part of the application that users interact with directly in their web browsers) and the "back end" (the server-side code, databases, and server management that power the application).
By mastering both front end and back end technologies, full-stack developers have the skills and knowledge needed to build complete web applications from start to finish, handling all aspects of development, deployment, and maintenance.
Overall, full-stack developers have a broad range of skills and knowledge across both front end and back end technologies, allowing them to take a project from concept to completion and handle all aspects of web development.

Responsibilities of a Full Stack Developer
Front End
Designing and developing the user interface (UI) of web applications using HTML, CSS, and JavaScript. Implementing responsive design principles to ensure that applications are optimized for various devices and screen sizes. Creating interactive and engaging user experiences through features like animations, transitions, and dynamic content
Back End
Building server-side logic and functionality using server-side scripting languages like Python, Ruby, PHP, or Node.js. Developing APIs (Application Programming Interfaces) to allow communication between the front end and back end of the application. Integrating with databases and managing data persistence using SQL or NoSQL databases like MySQL, PostgreSQL, or MongoDB. Implementing authentication and authorization mechanisms to secure access to the application's resources.
Database Management
Designing database schemas and data models to support the application's requirements. Writing database queries and optimizing database performance for efficient data retrieval and manipulation. Ensuring data integrity, consistency, and security through proper database design and access control mechanisms.
DevOps and Deployment
Configuring and deploying web applications to production environments using tools like Docker, Kubernetes, or traditional server setups. Setting up continuous integration and continuous deployment (CI/CD) pipelines to automate the deployment process. Monitoring application performance, logging, and error tracking to identify and resolve issues in real-time.
Why you should learn
Versatility
Python is a highly versatile programming language with a wide range of applications. By mastering full stack development with Python, you gain the ability to work on both the front-end and back-end of web applications, as well as database management, making you a well-rounded developer capable of handling various tasks within a project.
High Demand
There’s a high demand for full stack developers proficient in Python due to its popularity and effectiveness in web development. Many companies, from startups to large enterprises, rely on Python for building robust and scalable web applications. Having these skills can make you a desirable candidate in the job market.
Increased Employability
Full stack developers are sought after because they possess a comprehensive skill set that allows them to take a project from conception to completion. By learning full stack development using Python, you enhance your employability and open up opportunities in a wide range of industries and organizations.
Ability to Work Independently
With proficiency in full stack development, you have the capability to work independently on projects without the need for extensive collaboration with specialists in each domain. This autonomy can be valuable in freelance or remote work scenarios where you may not have immediate access to a team of specialists.
Agility and Efficiency
Python’s simplicity and readability enable developers to write clean and concise code, which can lead to faster development cycles and more efficient project delivery. This agility is crucial in today’s fast-paced tech industry, where companies need to rapidly iterate on products to stay competitive.
Continuous Learning and Growth
Full stack development with Python is a dynamic field that constantly evolves with new tools, frameworks, and best practices. By investing in learning and mastering these skills, you demonstrate your commitment to continuous learning and growth, which is highly valued by employers and can lead to advancement opportunities in your career.
Course Syllabus
Module 1 : Introduction to System Architecture
- Overview of system architecture and its importance
- Evolution of computing architectures
- Key principles of system design: scalability, reliability, performance, and security
- Case studies of successful system architectures
Module 2 :Fundamentals of Distributed Systems
- Introduction to distributed systems architecture
- Challenges and benefits of distributed computing
- Distributed system models: client-server, peer-to-peer, and hybrid
- Communication protocols and message passing in distributed systems
Module 3 :Designing Scalable Systems
- Scalability principles and strategies
- Horizontal vs. vertical scaling
- Load balancing techniques: DNS-based, hardware-based, software-based
- Caching strategies and CDN (Content Delivery Network) integration
Module 4 : Ensuring Reliability and Fault Tolerance
- Redundancy and fault tolerance in system design
- High availability architectures: active-passive, active-active
- Data replication and consistency models in distributed systems
- Failure detection and recovery mechanisms
Module 5 : Monolithic Architecture
- Understanding monolithic architecture
- Characteristics and components of monolithic systems
- Monolithic vs. microservices architecture
- Challenges and benefits of monolithic architecture
Module 6 : Microservices Architecture
- Introduction to microservices architecture
- Principles of microservices design: modularity, autonomy, bounded context
- Communication patterns: synchronous vs. asynchronous communication
- Containerization with Docker and orchestration with Kubernetes
Module 7 : Security and Privacy in System Design
- Threat modeling and risk assessment
- Principles of secure system design
- Authentication and authorization mechanisms
- Data encryption, hashing, and secure communication protocols
Module 8 : Introduction to Version Control and Git
- Overview of version control systems
- Introduction to Git: history, purpose, and benefits
- Setting up Git: installation, configuration, and global settings
- Initializing a Git repository and basic Git workflow
Module 9 : Git Basics: Commits, Branches, and Merging
- Git fundamentals: commits, snapshots, and the commit graph
- Branching and branching strategies: feature branches, release branches, and hotfix branches
- Merging branches: fast-forward, recursive, and conflicts
- Resolving merge conflicts: manual conflict resolution and merge tools
Module 10 : Collaboration with Remote Repositories
- Working with remote repositories: cloning, fetching, pulling, and pushing
- Adding remote repositories:
git remote
command - Collaborative workflows: centralized vs. distributed version control
- Forking and contributing to open-source projects on GitHub
Module 11 : Advanced Git Concepts
- Git rebase: rebasing branches and interactive rebasing
- Git cherry-pick: selecting and applying specific commits
- Git stash: temporarily shelving changes
- Git bisect: finding the commit that introduced a bug
Module 12 : Git Best Practices
- Repository organization and structure
- Commit message conventions and guidelines
- Branch naming conventions
- Code review best practices using Git pull requests
Module 13 : Git Workflow Strategies
- Gitflow workflow: feature branches, release branches, and hotfix branches
- GitHub flow: simple and continuous deployment-oriented workflow
- GitLab flow: similar to GitHub flow with additional testing and deployment stages
- Choosing the right workflow for your team and project
Module 14 : Git Hooks and Customization
- Introduction to Git hooks: pre-commit, post-commit, pre-push, etc.
- Writing custom Git hooks in Bash or other scripting languages
- Automating repetitive tasks with Git hooks
- Customizing Git configuration: aliases, colors, and settings
Module 15 : Introduction to Data Structures and Algorithms
- Overview of data structures and algorithms
- Importance of data structures and algorithms in software development
- Big O notation and analysis of algorithm efficiency
- Strategies for algorithm design and problem-solving
Module 16 : Arrays and Linked Lists
- Introduction to arrays and linked lists
- Operations on arrays: insertion, deletion, search, and traversal
- Implementing arrays and linked lists in programming languages
- Comparison of arrays and linked lists: advantages and disadvantages
Module 17 : Stacks and Queues
- Introduction to stacks and queues
- Implementing stacks and queues using arrays and linked lists
- Applications of stacks and queues in algorithm design
- Evaluating expressions, breadth-first search, and depth-first search using stacks and queues
Module 18 : Trees and Binary Search Trees
- Introduction to trees and binary trees
- Operations on binary search trees: insertion, deletion, search, and traversal
- Balancing binary search trees: AVL trees, Red-Black trees
- Applications of binary search trees: searching, sorting, and indexing
Module 19 : Heaps and Priority Queues
- Introduction to heaps and priority queues
- Operations on heaps: insertion, deletion, and heapification
- Implementing priority queues using heaps
- Applications of heaps: heap sort, Dijkstra’s algorithm, and Huffman coding
Module 20 : Hash Tables and Hashing
- Introduction to hash tables and hashing
- Hash functions and collision resolution techniques
- Implementing hash tables using arrays and linked lists
- Applications of hash tables: associative arrays, caching, and spell checking
Module 21 : Graphs and Graph Algorithms
- Introduction to graphs: representation and terminology
- Graph traversal algorithms: depth-first search (DFS) and breadth-first search (BFS)
- Shortest path algorithms: Dijkstra’s algorithm, Bellman-Ford algorithm
- Minimum spanning tree algorithms: Prim’s algorithm, Kruskal’s algorithm
Module 22 : Introduction to HTML
- Overview of web development technologies
- Introduction to HTML: history, purpose, and structure
- Basic structure of an HTML document
- HTML elements and tags: headings, paragraphs, lists, and links
Module 23 : Working with Text and Multimedia
- Text formatting in HTML: emphasis, strong emphasis, and text alignment
- Inserting images and multimedia content
- Hyperlinks: internal links, external links, and anchor tags
- HTML character entities and special symbols
Module 24 : Tables and Forms
- Creating tables in HTML: table structure, rows, columns, and headers
- Formatting tables using CSS
- Introduction to HTML forms: form elements, input types, and form attributes
- Form validation and submission using HTML attributes
Module 25 : Cascading Style Sheets (CSS)
- Introduction to CSS: purpose, syntax, and selectors
- Inline CSS, internal CSS, and external CSS
- CSS properties: text styling, colors, backgrounds, and borders
- CSS box model: margin, padding, border, and content
Module 26 : Advanced HTML5 Features
- Canvas element: drawing graphics and animations with JavaScript
- SVG (Scalable Vector Graphics) in HTML5
- Geolocation API: retrieving geographical location information
- Web storage: localStorage and sessionStorage
Module 27 : Introduction to JavaScript
- Overview of JavaScript: history, purpose, and features
- Setting up the development environment: text editor, web browser, developer tools
- Writing and running JavaScript code in the browser console
- Basic syntax: variables, data types, and comments
Module 28 : Control Flow and Functions
- Conditional statements: if-else, switch-case
- Looping constructs: for loop, while loop, do-while loop
- Functions: defining functions, function parameters, return statement
- Scope and variable visibility: global scope, function scope, block scope
Module 29 : Arrays and Array Methods
- Introduction to arrays: creating arrays, accessing elements, and array properties
- Array methods: push, pop, shift, unshift, slice, splice, for Each
- Iterating over arrays using loops and array methods
- Multi-dimensional arrays and array manipulation techniques
Module 30 : Objects and Object-Oriented Programming
- Introduction to objects: creating objects, properties, and methods
- Object literals and object constructors
- Object-oriented programming concepts: encapsulation, inheritance, and polymorphism
- Prototypes and prototype-based inheritance in JavaScript
Module 31 : Document Object Model (DOM) Manipulation
- Introduction to the DOM: structure, nodes, and elements
- Accessing and manipulating DOM elements using JavaScript
- Event handling: adding event listeners, event types, and event propagation
- Dynamic HTML manipulation: creating, modifying, and removing DOM elements
Module 32 : JavaScript Functions and Closures
- Advanced function concepts: function expressions, arrow functions, and immediately-invoked function expressions (IIFE)
- Closures: understanding closure scope and closure use cases
- Higher-order functions: functions as arguments and return values
- Practical examples of closures and higher-order functions in JavaScript
Module 33 : Asynchronous JavaScript and Promises
- Introduction to asynchronous programming: setTimeout, setInterval
- Callback functions and callback hell
- Promises: creating, chaining, and error handling
- Async/await: asynchronous functions and handling asynchronous operations synchronously
Module 34 : Introduction to Modern JavaScript
- ES6 (ECMAScript 2015) features: let and const, template literals, arrow functions, destructuring assignment, spread syntax, and rest parameters
- Introduction to ES modules: import and export statements
- Introduction to modern JavaScript frameworks and libraries (e.g., React, Angular)
Module 35 : Introduction to Python
- Overview of Python: history, purpose, and features
- Installing Python: Python distributions, IDEs, and text editors
- Running Python code: interactive mode, script mode, and command-line interface
- Writing and running your first Python program
Module 36 : Python Basics: Variables and Data Types
- Variables and data types in Python: integers, floats, strings, booleans
- Basic operations: arithmetic operations, string concatenation, and comparison operators
- Type conversion and typecasting in Python
- Best practices for naming variables and choosing data types
Module 37 : Control Flow and Conditional Statements
- Conditional statements: if-else, elif, nested if statements
- Comparison operators and logical operators in Python
- Short-circuiting and conditional expressions (ternary operator)
- Flow control statements: break, continue, and pass
Module 38 : Loops and Iterations
- Looping constructs in Python: for loop, while loop
- Iterating over sequences: lists, tuples, strings, and dictionaries
- Loop control statements: break and continue
- Nested loops and loop optimization techniques
Module 39 : Functions and Modular Programming
- Introduction to functions: defining functions, function parameters, return statement
- Function arguments: positional arguments, keyword arguments, default arguments
- Variable scope and lifetime: local scope, global scope, and nonlocal keyword
- Modular programming in Python: organizing code into modules and packages
Module 40 : Data Structures: Lists, Tuples, and Dictionaries
- Introduction to data structures: lists, tuples, dictionaries
- List manipulation: indexing, slicing, adding elements, removing elements
- Tuple manipulation: accessing elements, immutable nature of tuples
- Dictionary manipulation: accessing, adding, and removing key-value pairs
Module 41 : File Handling and Input/Output Operations
- Reading and writing files in Python: open() function, file modes
- Reading file contents: read(), readline(), readlines() methods
- Writing to files: write() method, handling file paths
- Working with file objects: closing files, using context managers (with statement)
Module 42 : Object-Oriented Programming (OOP) in Python
- Introduction to object-oriented programming (OOP) concepts: classes and objects
- Defining classes and creating objects in Python
- Class constructors and instance variables
- Class methods, static methods, and instance methods
Module 43 : Advanced Python Concepts
- Exception handling: try-except blocks, handling specific exceptions, finally block
- Built-in functions and standard library modules
- Lambda functions and functional programming concepts
- Decorators: defining decorators, applying decorators to functions
Module 44 : Introduction to Python Libraries and Frameworks
- Overview of popular Python libraries and frameworks (e.g., NumPy, Pandas, Flask, Django)
- Installing and using third-party libraries using package managers (e.g., pip)
- Exploring real-world applications and projects built with Python
Module 45 : Introduction to Django
- Overview of Django: features, architecture, and benefits
- Setting up the Django development environment: installing Django, setting up a project
- Django project structure: understanding settings.py, urls.py, and manage.py
- Creating and running a basic Django project: Hello World example
Module 46 : Django Models and Database Interactions
- Introduction to Django models: defining models, fields, and relationships
- Creating database tables using Django ORM (Object-Relational Mapping)
- Django admin interface: registering models, managing data using the admin panel
- Performing CRUD (Create, Read, Update, Delete) operations on database records
Module 47 : Django Views and URL Routing
- Introduction to Django views: defining views, handling HTTP requests
- URL routing in Django: mapping URLs to views using URL patterns
- Class-based views vs. function-based views
- Working with request and response objects in Django views
Module 48 : Django Templates and Template Language
- Introduction to Django templates: creating template files, template inheritance
- Rendering dynamic content in templates using template variables and filters
- Template tags and template logic: loops, conditionals, and includes
- Template inheritance and extending base templates
Module 49 : Django Forms and Form Handling
- Introduction to Django forms: creating HTML forms using Django form classes
- Form validation in Django: built-in validators, custom validation methods
- Handling form submissions in Django views: processing form data, form validation
- Displaying form errors and messages in templates
Module 50 : User Authentication and Authorization
- User authentication in Django: built-in authentication system, login/logout views
- User registration and password management: registration forms, password reset functionality
- User authorization and permissions: defining user roles and permissions, restricting access to views
- Integrating third-party authentication providers (e.g., social authentication)
Module 51 : Django Advanced Features
- Working with static files: configuring static file directories, serving static files in development and production
- Django middleware: writing custom middleware for request/response processing
- Django signals: implementing custom actions triggered by specific events
- Introduction to Django REST Framework for building RESTful APIs
Module 52 : Introduction to MySQL
- Overview of MySQL: history, features, and benefits
- Installing MySQL: local installation (e.g., MySQL Community Edition, XAMPP)
- Connecting to MySQL server using command-line interface (CLI) and graphical user interface (GUI)
- Running basic MySQL commands: creating databases, tables, and executing queries
Module 53 : MySQL Data Types and Operators
- Introduction to MySQL data types: numeric, string, date/time, and boolean data types
- Understanding MySQL operators: arithmetic, comparison, logical, and string operators
- Working with NULL values in MySQL: handling NULL values in queries and data manipulation
Module 54 : MySQL Joins and Subqueries
- Understanding MySQL joins: inner join, left join, right join, and cross join
- Using aliases for table and column names in MySQL queries
- Writing subqueries in MySQL: correlated and non-correlated subqueries
- Combining multiple queries using UNION and UNION ALL operators
Module 55 : MySQL Data Modeling and Database Design
- Introduction to database normalization: first normal form (1NF), second normal form (2NF), and third normal form (3NF)
- Database design principles: designing relational database schemas, entity-relationship modeling
- Implementing relationships between tables: one-to-one, one-to-many, and many-to-many relationships
- Denormalization and optimizing database performance
Module 56 : MySQL Indexes and Constraints
- Introduction to MySQL indexes: improving query performance using indexes
- Creating and managing indexes in MySQL: primary key, unique key, and composite indexes
- Understanding MySQL constraints: NOT NULL, UNIQUE, PRIMARY KEY, FOREIGN KEY constraints
- Enforcing data integrity using constraints in MySQL tables
Module 57 : MySQL Stored Procedures and Functions
- Introduction to stored procedures and functions in MySQL
- Creating and executing stored procedures and functions
- Passing parameters to stored procedures and functions
- Managing transactions using stored procedures in MySQL
Module 58 : MySQL Tables and Data Manipulation
- Creating and modifying MySQL tables: defining table structure, specifying data types, and constraints
- Inserting, updating, and deleting data in MySQL tables
- Retrieving data from MySQL tables: using SELECT statement, filtering, sorting, and limiting results
- Performing basic data manipulation operations: sorting, filtering, and aggregating data
Module 59 : MySQL Security and Administration
- Managing MySQL users and privileges: user authentication, authorization, and permissions
- Securing MySQL server: configuring firewall, encrypting connections
- Backing up and restoring MySQL databases: using mysqldump, MySQL Workbench
- Monitoring MySQL server performance: using MySQL performance schema and monitoring tools