Python is an interpreted, object-oriented, high-level programming language. It is an open source programming language with more than 1 million libraries and more than 100,000 active contributors. Python is also known for its simplicity as compared to other programming languages. Be it Artificial Intelligence or Web Development or IoT or Big Data Analysis or Cloud Application Development or Automation domain you can find n number of use cases for Python. In this course, we will start with Python Installation and few basics of Python.

This Python tutorial for Data Science and Machine Learning will kick-start your learning of Python concepts needed for data science, as well as programming in general. Understand how to use the Jupyter Notebook, Understanding of Python from the beginning, Learn to use Object Oriented Programming with classes, Learn how to use NumPy, Pandas, Seaborn, Matplotlib, Plotly, Scikit-Learn, Machine Learning, Tensorflow, and more! This course will teach you from Python basics to advanced concepts in a practical manner, with Hands on exercises covered as well. This Python tutorial for data science will kick-start your learning of Python concepts needed for data science, as well as programming in general. Python is required for data science because, Python programming is a versatile language commonly preferred by data scientists and big tech giant companies around the world, from startups to behemoths.

Advanced ActionScript 3 is a fresh look and new approach to utilizing valuable, structural techniques and methods that are commonly used in the field of rich interactive application development. With each method broken down into different strategized explanations, you'll find the approach most suitable for you. Whether it is an example you can utilize as-is, or one you can start with and develop further, you will have a glossary of definitions and organizational concepts at your fingertips. Object-oriented programming (OOP) and design patterns are not new to the field, but can often be overlooked in their value. They are, at times, not only overwhelming to learn, but difficult to put into practice.

Learn how to create desktop applications. Learn how to create console applications. Learn how to create web applications. Python Data Structures.New What you'll learn Learn Python from the ground up. Learn how to create desktop applications Learn how to create console applications Learn how to create web applications Learn about Python Data Types and casting Python String Methods and Formatting Python Data Structures Python Control Flow Statements Python Modules and Packages Working with external files in Python Working with dates and times Handling exception errors Version control system with Git and Github Web scrapping with Python Python and Machine Learning Python and data science Web development with Django Python Object Oriented Programming Building API from scratch Description Python is a dynamic modern object -oriented programming language and can be used to do a lot of things both big and small.

If you're new to ActionScript 3.0, or want to enhance your skill set, this bestselling book is the ideal guide. Designers, developers, and programmers alike will find Learning ActionScript 3.0 invaluable for navigating ActionScript 3.0's learning curve. You'll learn the language by getting a clear look at essential topics such as logic, event handling, displaying content, classes, and much more. Updated for Flash Professional CS5, this revised and expanded edition delivers hands-on exercises and full-color code samples to help you increase your abilities as you progress through the book. Topics are introduced with basic syntax and class-based examples, so you can set your own pace for learning object-oriented programming.

Data science is the study of data. It involves developing methods of recording, storing, and analyzing data to effectively extract useful information . Data is a fundamental part of our everyday work, whether it be in the form of valuable insights about our customers, or information to guide product,policy or systems development. Big business, social media, finance and the public sector all rely on data scientists to analyse their data and draw out business-boosting insights. Python is a dynamic modern object -oriented programming language that is easy to learn and can be used to do a lot of things both big and small.

Work through nearly 200 exercises and quizzes! Learn about all of the latest features in Python 3.6 Use Python to create an automated web crawler and scraper Make complex HTTP requests to APIs using Python Master the quirks of Python style and conventions Really Really Understand Object Oriented programming in Python Learn testing and TDD (Test Driven Development) with Python Write your own Decorators and higher order functions Write your own Generators and other Iterators Confidently work with Lambdas! Work through nearly 200 exercises and quizzes! Comment Policy: Please write your comments that match the topic of this page's posts. Comments that contain links will not be displayed until they are approved.

The Quick Python Book, Second Edition, is a clear, concise introduction to Python 3, aimed at programmers new to Python. This updated edition includes all the changes in Python 3, itself a significant shift from earlier versions of Python. The book begins with basic but useful programs that teach the core features of syntax, control flow, and data structures. It then moves to larger applications involving code management, object-oriented programming, web development, and converting code from earlier versions of Python. True to his audience of experienced developers, the author covers common programming language features concisely, while giving more detail to those features unique to Python.

Object-Oriented Software Engineering is written for both the traditional one-semester and the newer two-semester software engineering curriculum. Part I covers the underlying software engineering theory, while Part II presents the more practical life cycle, workflow by workflow. The text is intended for the substantial object-oriented segment of the software engineering market. It focuses exclusively on object-oriented approaches to the development of large software systems that are the most widely used. Text includes 2 running case studies, expanded coverage of agile processes and open-source development.

In the beginning, there were files. Later there were navigational databases based on structured files. Then there were IMS and CODASYL, and around 40 years ago we had some of the first relational databases. Throughout much of the 1980s and 1990s "database" strictly meant "relational database." Then with the growing popularity of object-oriented programming languages, some thought the solution to the "impedance mismatch" of object-oriented languages and relational databases was to map objects in the database. Thus we ended up with "object-oriented databases."