Python is a general-purpose, versatile and popular programming language. It’s great as a first language because it is concise and easy to read, and it is also a good language to have in any programmer’s stack as it can be used for everything from web development to software development and scientific applications.
With Python Advance you can work with Artificial Intelligence, Data Science, Machine Learning and many more. So based on your requirements we can even customize the Advance Python program to suit your requirements.
Curriculum
- 14 Sections
- 37 Lessons
- 24 Hours
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- Python review1
- Classes and Objects3
- 2.1An introduction to creating and using user-defined objects in Python.
- 2.2Describes how to use the class statement to create new objects and presents details on various special methods that can be defined to customize object behavior.
- 2.3Commonly used object oriented programming techniques are also presented.
- Advanced I/O Handling1
- Idiomatic Data Handling3
- 4.1An introduction to various tools and techniques for effective data processing.
- 4.2Discusses different options for creating data structures and gives an inside look at how the built-in data types are put together along with their performance and memory usage properties.
- 4.3Students will learn how to apply list, set, and dictionary comprehensions to various problems in data handling.
- Inside the Python Object Model3
- 5.1A detailed tour of how the Python object system is implemented.
- 5.2Topics include the definition of objects, object representation, attribute binding, inheritance, descriptors, properties, slots, private attributes, static methods, and class methods.
- 5.3Cover important details concerning Python memory management and garbage collection.
- Testing, Debugging and Logging4
- Packages and Distribution3
- 7.1How to organize Python code into packages and how to distribute packages to users and programmers.
- 7.2Covers the underlying mechanics of how packages are put together and the distutils module for creating distributions.
- 7.3Also covers more advanced packaging options such as Distribute and setup tools.
- Iterators, Generators, Coroutines3
- 8.1The section starts with a description of the iteration protocol and moves on to practical use of generators and coroutines.
- 8.2A major focus on this section is on the use of generators and coroutines to set up processing pipelines, much like pipes in Unix programming.
- 8.3You will see how generators and coroutines can lead to very elegant programming abstractions for processing data and how such programs can be used to process huge data files and streaming I/O.
- Functional Programming2
- Metaprogramming3
- 10.1Loosely defined, metaprogramming refers to programs that are able to manipulate their own program structure (functions, classes, etc.) or the structure of other programs as data.
- 10.2This section introduces and covers practical examples of Python’s metaprogramming features including function decorators, class decorators, met classes, and context managers.
- 10.3A major emphasis of this section is to understand how advanced programming frameworks utilize these features to provide a richer programming environment for their end users.
- Extension Programming3
- 11.1How to create C and C++ extensions to Python. Covers the absolute basics of the Python C API followed by some details on using the c types library and Swig code generator.
- 11.2A major focus of this section is on how to organize extension code so that it can more seamlessly integrate with the Python environment.
- 11.3Topics include memory management, data handling, encapsulation, and common pitfalls.
- Concurrent Programming with Threads3
- 12.1An introduction to programming with Python threads.
- 12.2Starts with the basics of using the threading library and dives into a variety of more advanced topics including a survey of how and when to use the different thread synchronization primitives, queues, deadlock avoidance, and thread debugging.
- 12.3Also includes detailed information on how the Python interpreter executes programs and properties of the global interpreter lock (GIL).
- Multiprocessing2
- Python 33
