List of topics which are covered in this learning:
These topics cover a wide range of Python knowledge and should help you prepare for job interviews in various domains, whether it’s web development, data analysis, machine learning, or other areas where Python is commonly used. Tailor your focus based on the specific requirements of the job you’re applying for.
- Installing Python
- Basic Syntax and Data Types
- Variables and Constants
- Numeric Types (int, float)
- Strings and String Manipulation
- Lists
- Tuples
- Dictionaries
- Sets
- Booleans
- Basic Input and Output
- Type Conversion
- Control Structures (if, elif, else, while, for)
- Conditional Expressions (ternary operator)
- Functions
- Function Arguments
- Return Values
- Variable Scope
- Lambda Functions
- Recursion
- Object-Oriented Programming (OOP)
- Classes and Objects
- Constructors and Destructors
- Inheritance
- Method Overriding
- Encapsulation
- Abstraction
- Polymorphism
- Multiple Inheritance
- Exception Handling (try, except, else, finally)
- Custom Exceptions
- File Handling
- Opening and Closing Files
- Reading and Writing Files
- Working with CSV and JSON
- File Paths and Directories
- Data Structures (stack, queue, linked list)
- List Comprehensions
- Dictionary Comprehensions
- Generators and Iterators
- Decorators
- Context Managers
- Recursion vs. Iteration
- Date and Time
- Regular Expressions (re module)
- Modules and Packages
- Importing Modules
- Creating Modules
- Built-in Modules (math, random, datetime, os, sys)
- sys.argv and Command-Line Arguments
- Virtual Environments
- Global Variables
- Constants in Python
- Magic Methods
- List vs. Set vs. Dict Comprehensions
- Python Garbage Collection
- Namespaces and Scope
- Closures
- First-Class Functions
- Functional Programming
- Map, Filter, and Reduce
- Anonymous Functions (lambda)
- Higher-Order Functions
- Itertools
- Multithreading vs. Multiprocessing
- Threading
- GIL (Global Interpreter Lock)
- Synchronization and Locks
- Multiprocessing
- Concurrent Futures
- Asynchronous Programming (async and await)
- Asyncio
- Coroutines
- Web Scraping with Beautiful Soup
- Web Scraping with Requests
- RESTful APIs
- HTTP Methods (GET, POST, PUT, DELETE)
- Cookies and Sessions
- Web Development (Flask, Django)
- Flask Basics (Routes, Templates, Forms)
- Django Basics (Models, Views, Templates)
- Database Access (SQL and NoSQL)
- SQLite
- SQLAlchemy
- ORM (Object-Relational Mapping)
- MySQL and PostgreSQL
- MongoDB
- Database Connectivity (SQLAlchemy, pymongo)
- Data Serialization (JSON, XML)
- Serialization Libraries (pickle, json)
- GUI Programming (Tkinter)
- Unit Testing (unittest, pytest)
- Test-Driven Development (TDD)
- Version Control (Git, GitHub, GitLab)
- Git Basics (commit, branch, merge)
- Git Collaboration (clone, pull, push)
- Git Branching and Merging
- Git Conflict Resolution
- Collaborative Coding
- Software Design Patterns
- Model-View-Controller (MVC)
- Singleton Pattern
- Factory Pattern
- Adapter Pattern
- Decorator Pattern
- Observer Pattern
- Command Pattern
- Python 2 vs. Python 3
- Key Differences
- Migration Strategies
- Printing in Python (print function)
- Working with Directories (os and os.path)
- Environment Variables
- Unicode and Character Encoding
- PyPI (Python Package Index)
- Package Management (pip)
- Virtual Environments (virtualenv)
- Third-Party Libraries
- Debugging Techniques
- Profiling Python Code
- Memory Management
- Performance Optimization
- Code Documentation (docstrings)
- PEP 8 Style Guide
- Coding Standards
- Code Linting
- IDEs and Text Editors
- Jupyter Notebooks
- REPL (Read-Eval-Print Loop)
- Interactive Mode
- Data Analysis with Pandas
- NumPy for Numerical Computing
- Data Visualization (Matplotlib, Seaborn)
- Data Cleaning and Preprocessing
- Statistical Analysis
- Machine Learning Libraries (scikit-learn)
- Supervised Learning
- Unsupervised Learning
- Deep Learning (TensorFlow, PyTorch)
- Neural Networks
- Convolutional Neural Networks (CNN)
- Recurrent Neural Networks (RNN)
- Natural Language Processing (NLP)
- Sentiment Analysis
- Computer Vision
- Image Processing
- Reinforcement Learning
- Data Science Tools (Jupyter, Anaconda)
- Big Data Processing (PySpark)
- Data Warehousing (Snowflake, Redshift)
- Data Analysis with SQL (SQLite, SQLAlchemy)
- Data Visualization with Plotly
- Web Development with Flask
- RESTful API Design
- JavaScript Integration (JSON, AJAX)
- Full-Stack Development
- DevOps (Docker, Kubernetes)
- Continuous Integration/Continuous Deployment (CI/CD)
- Cloud Services (AWS, Azure, Google Cloud)
- Serverless Computing (AWS Lambda)
- Microservices Architecture
- Scalability and Load Balancing
- SQL Injection Prevention
- Cross-Site Scripting (XSS) Prevention
- Web Security Best Practices
- Secure Password Hashing
- Cryptography with Python
- Hash Functions (md5, sha)
- Symmetric Encryption
- Asymmetric Encryption
- Public and Private Keys
- SSL/TLS Encryption
- Networking (socket programming)
- Creating a Socket Server
- Creating a Socket Client
- Protocols (HTTP, FTP, SMTP)
- API Authentication (OAuth, JWT)
- REST API Testing (Postman)
- Serialization Formats (XML, JSON)
- Concurrency Control
- Mutexes and Semaphores
- Deadlocks
- Thread Safety
- Parallel Programming
- Data Structures (Heap, Priority Queue)
- Data Compression
- Algorithms (Sorting, Searching)
- Sorting Algorithms (QuickSort, MergeSort)
- Searching Algorithms (Binary Search)
- Big O Notation
- Data Analysis Libraries (Pandas, NumPy)
- Machine Learning Algorithms
- Neural Network Architectures
- Hyperparameter Tuning
- Model Evaluation and Metrics
- Clustering Algorithms
- Image Recognition
- Object Detection
- Generative Adversarial Networks (GANs)
- Reinforcement Learning Algorithms
- Time Series Analysis
- Data Engineering
- ETL (Extract, Transform, Load)
- Data Warehousing (AWS Redshift, Google BigQuery)
- Data Visualization (Tableau, Power BI)
- Web Development Frameworks (Django, Ruby on Rails)
- GraphQL
- Authentication and Authorization
- Cross-Origin Resource Sharing (CORS)
- Serverless Architecture (AWS Lambda)
- Containerization (Docker)
- Orchestration (Kubernetes)
- Infrastructure as Code (Terraform, Ansible)
- IoT (Internet of Things)
- DevOps Best Practices
- Site Reliability Engineering (SRE)
- Agile and Scrum Methodologies
- Project Management
- Problem Solving and Algorithmic Thinking
- Coding Challenges and LeetCode
- System Design Interviews
- Behavioral Interviews
- Soft Skills for Software Engineers