Mastering Python 3 Programming

Get acquainted with the concepts of Python 3.x programming to enhance the performance of your code

Ratings 3.60 / 5.00

What You Will Learn!

Get hands-on experience developing various kinds of Python applications on different platforms, architectures, and tools
Build four real-world applications: a stock portfolio, a mortgage refinance analysis tool, an email automation system, and a database-driven web app
Create Graphical User Interfaces for desktop and mobile applications
Know how to create HTTP-based microservices to build efficient and flexible server architectures
Learn lambda expressions, generators, and iterators to speed up your code
Gain a solid understanding of multiprocessing and multithreading in Python for parallelism
Optimize performance and efficiency by leveraging NumPy, SciPy, and Cython for numerical computations
Load large data using Dask in a distributed setting
Learn reactive programming in Python

Description

Python is an easy to learn, powerful programming language. It’s elegant syntax and dynamic typing, together with its interpreted nature, makes it an ideal language for scripting and rapid application development in many areas and on most platforms. If you're a developer who wishes to build a strong programming foundation with this simple yet powerful programming language Python, then this learning path is for you.

This practical course is designed to teach you the programming aspects of Python 3.x and use them to build powerful applications. You will begin with exploring the new features of this version and build multiple projects to get hold of the topic. You will learn about event-driven, reactive programming, error handling, asynchronous programming, decorators and non-type annotations, descriptors and distributed computing in Python. You will also build high-performance, concurrent applications in Python and also work with some of the powerful libraries such as NumPy and SciPy. Next, you will perform large-scale computations using Dask and implement distributed applications in Python. Finally, you will learn reactive programming with Python to construct robust and responsive applications.

By the end of this course you will be well-versed with the programming concepts in Python 3.x to build Python applications in a better and efficient manner.

Meet Your Expert(s):

We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:

Matthew Macarty has taught graduate and undergraduate business school students for over 15 years and currently teaches at Bentley University. He has taught courses in statistics, quantitative methods, information systems and database design.
Daniel Arbuckle holds a Doctorate in Computer Science from the University of Southern California, where he specialized in robotics and was a member of the nanotechnology lab. He now has more than ten years behind him as a consultant, during which time he’s been using Python to help an assortment of businesses, from clothing manufacturers to crowdsourcing platforms. Python has been his primary development language since he was in High School. He’s also an award-winning teacher of programming and computer science.
Mohammed Kashif works as a Data Scientist at Nineleaps, India, dealing mostly with graph data analysis. Prior to this, he was working as a Python developer at Qualcomm. He completed his Master's degree in computer science from IIIT Delhi, with specialization in data engineering. His areas of interest include recommender systems, NLP, and graph analytics. In his spare time, he likes to solve questions on StackOverflow and help debug other people out of their misery. He is also an experienced teaching assistant with a demonstrated history of working in the higher-education industry.