Python Courses Online

About

Think Python is a concise introduction to software design using the Python programming language. Intended for people with no programming experience, this course starts with the most basic concepts and gradually adds new material. Some of the ideas students find most challenging, like recursion and object-oriented programming, are divided into a sequence of smaller steps and introduced over the course of several chapters. The focus is on the programming process, with a special emphasis on debugging. The course includes a wide range of exercises, from short examples to substantial projects, so that students have ample opportunity to practice each new concept.

Course Content

1. Preface
2. The way of the program
3. Variables, expressions and statements
4. Functions
5. Case study: interface design
6. Conditional and recursion
7. Fruitful functions
8. Iteration
9. Strings
10. Case study: word play
11. Lists
12. Dictionaries
13. Tuples
14. Case study: data structure selection
15. Files
16. Classes and objects
17. Classes and functions
18. Classes and methods
19. Inheritance
20. Debugging

About

Classes are a way of aggregating similar data and functions. A class is basically a scope inside which various code (especially function definitions) is executed, and the locals to this scope become attributes of the class, and of any objects constructed by this class. An object constructed by a class is called an instance of that class.

Contents

• Overview
• Defining a Class
• Instance Construction
• Class Members
  • Methods
    • Why a mandatory argument?
    • Why self?
  • Invoking Methods
  • Dynamic Class Structure
    • Viewing Class Dictionaries
    • Changing Class Dictionaries
• Why use classes?
• New Style Classes
  • Properties
  • Static Methods
• Inheritance
• Multiple inheritances
• Special Methods
  • Initialization and Deletion
  • Representation
  • Attributes
  • Other Overrides
• Programming Practices
  • Encapsulation
  • Doc Strings
  • Adding methods at runtime
    • To a class
    • To an instance of a class
    • Using a function

About

wxPython is a wrapper for the cross-platform GUI API (often referred to as a "toolkit") wxWidgets (which is written in C++) for the Python programming language. It is one of the alternatives to Tkinter. It is implemented as a Python extension module (native code). wxPython gives an amazing arrangement of tools that permit you to rapidly and effectively developing applications that can run on a wide range of platforms. Since wxWidgets gives a covering around every stage's local GUI toolbox, the applications worked with wxPython will have a local look and feel any place they are deployed.

Content

• Create UI
• Controls
• Deploy wxPython applications to various OS.
• Application events
• Using Grids
• Web Services interaction
• Customization of displays using Paint events
• Multiple language Interaface

About

The languages Python and Ruby have the following in common:

1. They are free software (i.e., The source code can be easily accessed, and the interpreter that we will use for each language is written in the language itself);
2. They both support Object-Oriented Programming. (Python is actually Multi-Paradigm)
3. They are distributed with lightweight interactive consoles (IDLE for Python, irb (interactive Ruby) for Ruby)

Therefore, it is worthwhile to explore these two languages to solve mathematical problems. In this book, we shall enumerate what they bring to the teaching of mathematics and algorithms. In particular, we will study how certain mathematical structures are managed by these two languages.

Content

Mathematics with Python

• Numbers
  • Integers
  • Fractions
  • Complex Numbers

Mathematics with Ruby

• Numbers
  • Integers
  • Fractions
  • Real numbers
  • Complex numbers
  • Quaternions and octonions

About

Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively

Information Analysis with Python offers an advanced way to deal with data analysis so you can work with the most recent and most remarkable Python tools, AI procedures, and open source libraries. 

Content

• The tools needed
• Various case studies
• Toolset across Python and Jupyter
• The future of Data Science

About

Python and Math is an introductory approach to learning how to apply programming skills to solving math problems, while presenting high-level content with low-level terminology. Both experienced and beginner programmers will benefit from what this Wiki-book has to offer. Here are the main objectives: (1) Introduce programmers to solving math problems using programming. (2) Practice problem-solving skills using programming. (3) Introduce new skills and techniques that increase the efficiency of programs. So as a starter, here is an example of a problem you would solve using programming: Find the 10001th prime number, given that 2 is the first and 3 is the second. The main benefit of using programming in problem-solving is where the limitations of pencil/paper become apparent: time. Solving problems by hand can take a long time, especially solving a problem as the one above. Because there are no patterns in prime numbers (as we know), in order to get the 10001th prime, we must write them all out, in hand, one by one. Won't that take a long time! Essentially computers are just fast-number crunchers - we use them to calculate numbers really fast, but only combined with the programmer's mathematical genius can really hard problems be solved.

Content

• Welcome to Python and Math!
• Programming + Math
• Practice
• Dynamic Programming

About

IPython (Interactive Python) is a command shell for interactive computing in multiple programming languages, originally developed for the Python programming language, that offers introspection, rich media, shell syntax, tab completion, and history. IPython provides the following features:

• Interactive shells (terminal and Qt-based).
• A browser-based notebook interface with support for code, text, mathematical expressions, inline plots and other media.
• Support for interactive data visualization and use of GUI toolkits.
• Flexible, embeddable interpreters to load into one's own projects.
• Tools for parallel computing.

Content

• Parallel computing
• Other features
• End of Python 2 support
• Project Jupyter

About

The Splunk Software Development Kit (SDK) for Python contains library code and examples designed to enable developers to build applications using Splunk.

Splunk is a search engine and analytic environment that uses a distributed map-reduce architecture to efficiently index, search and process large time-varying data sets. The Splunk product is popular with system administrators for aggregation and monitoring of IT machine data, security, compliance and a wide variety of other scenarios that share a requirement to efficiently index, search, analyze and generate real-time notifications from large volumes of time series data.

In this course, developers will use the Splunk developer platform to build exciting new applications that are enabled by Splunk's unique capabilities.

Content

• Getting started with Splunk SDK for Python
• Requirements and Installation
• Testing Quickstart
• Create a .splunkrc convenience file
• Run examples
• Run the unit tests

About

spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython.

Content

• History
• Main features
• Extensions and visualizers

About

The Biopython Project is an open-source collection of non-commercial Python tools for computational biology and bioinformatics, created by an international association of developers. It contains classes to represent biological sequences and sequence annotations, and it is able to read and write to a variety of file formats. It also allows for a programmatic means of accessing online databases of biological information, such as those at NCBI. Separate modules extend Biopython's capabilities to sequence alignment, protein structure, population genetics, phylogenetics, sequence motifs, and machine learning. Biopython is one of a number of Bio* projects designed to reduce code duplication in computational biology.

Content

• History
• Design
• Key features and examples
  • Sequences
  • Sequence annotation
  • Input and output
  • Accessing online databases
  • Phylogeny
  • Genome diagrams
  • Macromolecular structure
  • Population genetics
  • Wrappers for command-line tools

About

OpenCV (Open Source Computer Vision Library) is a library of programming functions mainly aimed at real-time computer vision. Originally developed by Intel, it was later supported by Willow Garage then Itseez (which was later acquired by Intel). The library is cross-platform and free for use under the open-source Apache 2 License. Starting with 2011, OpenCV features GPU acceleration for real-time operations.

Content

• History
• Applications
• Programming language
• Hardware acceleration
• OS support

About

Python is general-purpose programming language It is a object-based language. named after Monty Python. Python is mainly influenced by ALGOL 68, ABC and Modula-3. Python follows a programming paradigm of functional programming, object-oriented programming and dynamic programming. Python is developed by Python Software Foundation and Guido van Rossum. It is designed by Guido van RossumSupported by cross-platform Operating Systems.

Content

• Design philosophy and features
• Syntax and semantics
  • Indentation
  • Statements and control flow
  • Expressions
  • Methods
  • Typing
  • Arithmetic operations
• Programming examples
• Libraries
• Development environments
• Implementations
  • Reference implementation
  • Other implementations
  • Unsupported implementations
  • Cross-compilers to other languages
  • Performance
• Development
• API documentation generators
• Naming
• Uses

About

scikit-image (formerly scikits.image) is an open-source image processing library for the Python programming language. It includes algorithms for segmentation, geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection, and more. It is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

Content

• Overview
• Implementation