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Advanced Python Programming for Real World Applications

This course is designed for experienced Python developers looking to advance their skills and apply Python to solve comp...

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Advanced Python Programming for Real World Applications

Sections

1. Advanced Python Syntax and Techniques
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Explore advanced syntax features and techniques to write more efficient and readable Python code, leveraging the full power of the language.

10 topics (10 versions)

1.1Decorators

1.2Context Managers

1.3Generators and Iterators

1.4Metaclasses

1.5Comprehensions

1.6Lambda Functions

1.7Python's Magic Methods

1.8Dynamic Typing and Annotations

1.9Advanced Unpacking

1.10Python's GIL and Threading

2. Object-Oriented Programming in Python
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Deep dive into advanced object-oriented programming concepts, design patterns, and best practices for building robust Python applications.

10 topics (10 versions)

2.1Inheritance and Composition

2.2Polymorphism

2.3Encapsulation

2.4Design Patterns in Python

2.5The SOLID Principles

2.6Mixins and Abstract Base Classes

2.7Object Serialization and Persistence

2.8UML Diagrams with Python

2.9Refactoring Object-Oriented Code

2.10Testing Object-Oriented Code

3. Functional Programming with Python
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Learn how to utilize functional programming paradigms in Python to create cleaner, more efficient code.

10 topics (10 versions)

3.1Higher-Order Functions

3.2Pure Functions

3.3Immutable Data Structures

3.4Lazy Evaluation

3.5Function Chaining

3.6Map, Filter, and Reduce

3.7Partial Functions

3.8Currying

3.9Monads and Functors

3.10Testing Functional Code

4. Data Structures and Algorithms
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Master advanced data structures and algorithms to optimize your Python applications for performance and efficiency.

10 topics (10 versions)

4.1Advanced List Operations

4.2Linked Lists and Trees

4.3Graph Algorithms

4.4Sorting and Searching Algorithms

4.5Dynamic Programming

4.6Hashing and Hash Tables

4.7Complexity Analysis

4.8Algorithm Design Techniques

4.9Optimizing Recursive Solutions

4.10Data Structure Libraries

5. Working with Databases
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An overview of interfacing Python with various database systems to store and retrieve data efficiently.

10 topics (10 versions)

5.1SQLAlchemy ORM

5.2NoSQL Databases with Python

5.3SQLite in Python

5.4Database Normalization

5.5Database Transactions

5.6Indexing and Query Optimization

5.7Database Security Practices

5.8Connecting to Cloud Databases

5.9Data Migrations

5.10Using Python with Big Data

6. Web Development with Python
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Learn how to build dynamic, scalable web applications using popular Python frameworks and tools.

10 topics (10 versions)

6.1Flask Web Framework

6.2Django Framework

6.3RESTful APIs with Python

6.4Asynchronous Web Applications

6.5WebSockets and Real-Time Data

6.6Template Engines

6.7Session Management and Security

6.8Deploying Python Web Apps

6.9Microservices Architecture

6.10Web Application Testing

7. Concurrency and Parallelism
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Understand how to effectively manage concurrency and parallelism in Python to improve application performance.

10 topics (10 versions)

7.1Threading in Python

7.2Multiprocessing Module

7.3AsyncIO for Asynchronous Programming

7.4Concurrent Futures

7.5Event-Driven Programming

7.6Race Conditions and Deadlocks

7.7Performance Profiling

7.8Task Scheduling

7.9Distributed Computing

7.10Parallel Algorithms

8. Network Programming
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Explore the capabilities of Python for network programming and building network-based applications.

10 topics (10 versions)

8.1Socket Programming

8.2HTTP and Web Services

8.3Building Clients and Servers

8.4Network Protocols

8.5Working with REST APIs

8.6Data Serialization Formats

8.7Secure Sockets Layer (SSL)

8.8Network Monitoring and Debugging

8.9Peer-to-Peer Networks

8.10Using Python for IoT

9. Testing and Debugging
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Learn effective testing and debugging techniques to ensure your Python applications are robust and error-free.

10 topics (10 versions)

9.1Unit Testing with PyTest

9.2Test-Driven Development (TDD)

9.3Behavior-Driven Development (BDD)

9.4Continuous Integration Testing

9.5Mocking and Stubbing

9.6Code Coverage Analysis

9.7Debugging Tools in Python

9.8Logging Best Practices

9.9Automated Testing Frameworks

9.10Profiling and Performance Tuning

10. Data Analysis and Visualization
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Harness Python's powerful libraries for data analysis and visualization to extract insights from complex datasets.

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Advanced Python Programming for Real World Applications

Sections

1. Advanced Python Syntax and Techniques3 views

2. Object-Oriented Programming in Python3 views

3. Functional Programming with Python1 views

4. Data Structures and Algorithms1 views

5. Working with Databases1 views

6. Web Development with Python2 views

7. Concurrency and Parallelism3 views

8. Network Programming2 views

9. Testing and Debugging2 views

10. Data Analysis and Visualization0 views

Sign in to track your progress

1. Advanced Python Syntax and Techniques
3 views

2. Object-Oriented Programming in Python
3 views

3. Functional Programming with Python
1 views

4. Data Structures and Algorithms
1 views

5. Working with Databases
1 views

6. Web Development with Python
2 views

7. Concurrency and Parallelism
3 views

8. Network Programming
2 views

9. Testing and Debugging
2 views

10. Data Analysis and Visualization
0 views