This document provides an introduction to the Python programming language over 30 minutes. It covers basic Python concepts like variables, data types, conditionals, loops, functions, imports, strings, lists, tuples, sets, dictionaries, and classes. Code examples are provided to demonstrate how to use these features. The document encourages learners to continue learning Python through online documentation and resources.
Python 101: Python for Absolute Beginners (PyTexas 2014)Paige Bailey
52 slides•30.1K views
If you're absolutely new to Python, and to programming in general, this is the place to start!
Here's the breakdown: by the end of this workshop, you'll have Python downloaded onto your personal machine; have a general idea of what Python can help you do; be pointed in the direction of some excellent practice materials; and have a basic understanding of the syntax of the language.
Please don't forget to bring your laptop!
Audience: "Python 101" is geared toward individuals who are new to programming. If you've had some programming experience (shell scripting, MATLAB, Ruby, etc.), then you'll probably want to check out the more intermediate workshop, "Python 101++".
This document provides an overview of the Python programming language. It covers Python basics like syntax, datatypes, modules, and control structures. It also discusses topics like functions, classes, files, and popular Python modules. The document contains an agenda that outlines these topics and provides code samples to illustrate Python concepts hands-on. It aims to equip readers with foundational Python programming knowledge.
Basic Python Programming: Part 01 and Part 02Fariz Darari
121 slides•3K views
This document discusses basic Python programming concepts including strings, functions, conditionals, loops, imports and recursion. It begins with examples of printing strings, taking user input, and calculating areas of shapes. It then covers variables and data types, operators, conditional statements, loops, functions, imports, strings, and recursion. Examples are provided throughout to demonstrate each concept.
The document provides an overview of the Python programming language. It discusses Python's history and versions, development environments, frameworks, uses, and basic features. The summary covers:
Python is an interpreted, object-oriented programming language created in 1989. It has undergone several major versions and is widely used for web development, science, and more. Python code can be written and run in various integrated development environments. It supports objects, modules, exceptions, and other features for structured programming.
This document provides an introduction and overview of the Python programming language. It discusses what Python is, its features, applications, and how to install Python on Windows and Linux systems. It also covers Python basics like variables, data types, operators, comments, conditional statements like if/else, and loops like for, while, and nested loops. Examples are provided for key concepts. The document is intended as a beginner tutorial for learning Python.
Functions allow programmers to organize code into reusable blocks. A function is defined using the def keyword and can accept parameters. The body of a function contains a set of statements that run when the function is called. Functions can return values and allow code to be reused, reducing errors and improving readability. Parameters allow information to be passed into functions, while return values allow functions to provide results.
YouTube Link: https://youtu.be/T6uCFDRVoRE
** Python Certification Training: https://www.edureka.co/python **
This Edureka Python JSON PPT will introduce you to JSON in Python and how you can do Parsing with various other operations.
The session will focus on pointers like:
Introduction to JSON in Python
Why do we use JSON?
Parsing JSON
Coding Demonstration
Python Tutorial Playlist: https://goo.gl/WsBpKe
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This document discusses functions and methods in Python. It defines functions and methods, and explains the differences between them. It provides examples of defining and calling functions, returning values from functions, and passing arguments to functions. It also covers topics like local and global variables, function decorators, generators, modules, and lambda functions.
Python is an interpreted programming language created by Guido van Rossum in 1991. It has an elegant syntax, large standard library, and is used widely for data science, machine learning, web development, and more. Key Python libraries for data analysis include NumPy, pandas, and matplotlib. Pandas allows importing and cleaning data from files like CSVs, and matplotlib can be used to visualize and present analyzed data. For example, a program can use pandas to read baby name data from a CSV, find the most popular name with the highest birth count, and plot the results to clearly present the findings.
Youtube Link: https://youtu.be/woVJ4N5nl_s
** Python Certification Training: https://www.edureka.co/data-science-python-certification-course **
This Edureka PPT on 'Python Basics' will help you understand what exactly makes Python special and covers all the basics of Python programming along with examples.
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The document discusses Python programming language. Some key points:
- Python was invented by Guido Van Rossum and is a combination of various programming languages.
- It is a general purpose, high-level programming language that is interpreted, interactive, object-oriented and extensible.
- Python can be used for web applications, desktop applications, data analysis, artificial intelligence, and more. Popular companies that use Python include Google, YouTube, and NASA.
- Python code is portable and can run on various platforms. It has a simple syntax and is easy to learn.
Python is a versatile, object-oriented programming language that can be used for web development, data analysis, and more. It has a simple syntax and is easy to read and learn. Key features include being interpreted, dynamically typed, supporting functional and object-oriented programming. Common data types include numbers, strings, lists, dictionaries, tuples, and files. Functions and classes can be defined to organize and reuse code. Regular expressions provide powerful string manipulation. Python has a large standard library and is used widely in areas like GUIs, web scripting, AI, and scientific computing.
The document discusses recursive functions and provides examples of recursive algorithms for calculating factorial, greatest common divisor (GCD), Fibonacci numbers, power functions, and solving the Towers of Hanoi problem. Recursive functions are functions that call themselves during their execution. They break down problems into subproblems of the same type until reaching a base case. This recursive breakdown allows problems to be solved in a top-down, step-by-step manner.
This document provides an introduction to object-oriented programming in Python. It discusses key concepts like classes, instances, inheritance, and modules. Classes group state and behavior together, and instances are created from classes. Methods defined inside a class have a self parameter. The __init__ method is called when an instance is created. Inheritance allows classes to extend existing classes. Modules package reusable code and data, and the import statement establishes dependencies between modules. The __name__ variable is used to determine if a file is being run directly or imported.
This document provides an introduction to the Python programming language. It covers Python's background, syntax, types, operators, control flow, functions, classes, tools, and IDEs. Key points include that Python is a multi-purpose, object-oriented language that is interpreted, strongly and dynamically typed. It focuses on readability and has a huge library of modules. Popular Python IDEs include Emacs, Vim, Komodo, PyCharm, and Eclipse.
The document provides an introduction and overview of the Python programming language. It discusses that Python is an interpreted, object-oriented, high-level programming language that is easy to learn and read. It also covers Python features such as portability, extensive standard libraries, and support for functional, structured, and object-oriented programming. The document then discusses Python data types including numbers, strings, and various Python syntax elements before concluding with the history and evolution of the Python language through various versions.
Python is a widely-used and powerful computer programming language that has helped system administrators manage computer networks and problem solve computer systems for decades. Python has also built some popular applications like BitTorrent, Blender, Calibre, Dropbox, and much more. Going further, the “Pi” in Raspberry Pi stands for Python, so learning Python will instill more confidence when working with Raspberry Pi projects. Python is usually the first programming language people learn primarily because it is easy to learn and provides a solid foundation to learn other computer programming languages. In this webinar,
• Learn what Python is and what it is capable of doing.
• Install Python’s IDE for Windows and work in the Python shell.
• Use calculations, variables, strings, lists, and if statements.
• Discover Python’s built-in functions and understand modules.
• Create simple programs to build on later.
The recording is available at https://youtu.be/ThcWmJFf-ho.
Python is a popular programming language used in a variety of applications, including data analysis, web development, and artificial intelligence. Here's an introduction to the Basics of Python - A Beginners Guide! Whether you're new to programming or looking to brush up on your skills, this video covers the basics of Python programming language. From data types and operators to loops, functions and libraries, you'll get a solid foundation to start coding in Python.
Visit us: https://www.elewayte.com/
This document provides an agenda and overview for a Python tutorial presented over multiple sessions. The first session introduces Python and demonstrates how to use the Python interpreter. The second session covers basic Python data structures like lists, modules, input/output, and exceptions. An optional third session discusses unit testing. The document explains that Python is an easy to learn yet powerful programming language that supports object-oriented programming and high-level data structures in an interpreted, dynamic environment.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and optionally returning values. Strings are sequences of characters that can be manipulated using indexes and methods. Common string methods include upper() and concatenation using +.
This document discusses files in Python. It begins by defining what a file is and explaining that files enable persistent storage on disk. It then covers opening, reading from, and writing to files in Python. The main types of files are text and binary, and common file operations are open, close, read, and write. It provides examples of opening files in different modes, reading files line by line or in full, and writing strings or lists of strings to files. It also discusses searching files and handling errors when opening files. In the end, it presents some exercises involving copying files, counting words in a file, and converting decimal to binary.
OOPS concepts are one of the most important concepts in high level languages. Here in this PPT we will learn more about Object oriented approach in python programming which includes details related to classes and objects, inheritance, dat abstraction, polymorphism and many more with examples and code.
Provides an introductory level understanding of the Python Programming Language and language features. Serves as a guide for beginners and a reference to Python basics and language use cases.
Python main function. Main function is the entry point of any program. But python interpreter executes the source file code sequentially and doesn't call any method if it's not part of the code. But if it's directly part of the code then it will be executed when the file is imported as a module.
Python is a popular programming language created by Guido van Rossum in 1991. It is easy to use, powerful, and versatile, making it suitable for beginners and experts alike. Python code can be written and executed in the browser using Google Colab, which provides a Jupyter notebook environment and access to computing resources like GPUs. The document then discusses installing Python using Anaconda, basic Python concepts like indentation, variables, strings, conditionals, and loops.
This document provides an overview of the Python programming language. It begins by explaining what Python is - a general purpose, interpreted programming language that can be used as both a programming and scripting language. It then discusses the differences between programs and scripting languages. The history and creator of Python, Guido van Rossum, are outlined. The document explores the scope of Python and what tasks it can be used for. Popular companies and industries that use Python today are listed. Reasons why people use Python, such as it being free, powerful, and portable, are provided. Instructions for installing Python and running Python code are included. The document covers Python code execution and introduces basic Python concepts like variables, strings, data types, lists
This document discusses functions and methods in Python. It defines functions and methods, and explains the differences between them. It provides examples of defining and calling functions, returning values from functions, and passing arguments to functions. It also covers topics like local and global variables, function decorators, generators, modules, and lambda functions.
Python is an interpreted programming language created by Guido van Rossum in 1991. It has an elegant syntax, large standard library, and is used widely for data science, machine learning, web development, and more. Key Python libraries for data analysis include NumPy, pandas, and matplotlib. Pandas allows importing and cleaning data from files like CSVs, and matplotlib can be used to visualize and present analyzed data. For example, a program can use pandas to read baby name data from a CSV, find the most popular name with the highest birth count, and plot the results to clearly present the findings.
Youtube Link: https://youtu.be/woVJ4N5nl_s
** Python Certification Training: https://www.edureka.co/data-science-python-certification-course **
This Edureka PPT on 'Python Basics' will help you understand what exactly makes Python special and covers all the basics of Python programming along with examples.
Follow us to never miss an update in the future.
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The document discusses Python programming language. Some key points:
- Python was invented by Guido Van Rossum and is a combination of various programming languages.
- It is a general purpose, high-level programming language that is interpreted, interactive, object-oriented and extensible.
- Python can be used for web applications, desktop applications, data analysis, artificial intelligence, and more. Popular companies that use Python include Google, YouTube, and NASA.
- Python code is portable and can run on various platforms. It has a simple syntax and is easy to learn.
Python is a versatile, object-oriented programming language that can be used for web development, data analysis, and more. It has a simple syntax and is easy to read and learn. Key features include being interpreted, dynamically typed, supporting functional and object-oriented programming. Common data types include numbers, strings, lists, dictionaries, tuples, and files. Functions and classes can be defined to organize and reuse code. Regular expressions provide powerful string manipulation. Python has a large standard library and is used widely in areas like GUIs, web scripting, AI, and scientific computing.
The document discusses recursive functions and provides examples of recursive algorithms for calculating factorial, greatest common divisor (GCD), Fibonacci numbers, power functions, and solving the Towers of Hanoi problem. Recursive functions are functions that call themselves during their execution. They break down problems into subproblems of the same type until reaching a base case. This recursive breakdown allows problems to be solved in a top-down, step-by-step manner.
This document provides an introduction to object-oriented programming in Python. It discusses key concepts like classes, instances, inheritance, and modules. Classes group state and behavior together, and instances are created from classes. Methods defined inside a class have a self parameter. The __init__ method is called when an instance is created. Inheritance allows classes to extend existing classes. Modules package reusable code and data, and the import statement establishes dependencies between modules. The __name__ variable is used to determine if a file is being run directly or imported.
This document provides an introduction to the Python programming language. It covers Python's background, syntax, types, operators, control flow, functions, classes, tools, and IDEs. Key points include that Python is a multi-purpose, object-oriented language that is interpreted, strongly and dynamically typed. It focuses on readability and has a huge library of modules. Popular Python IDEs include Emacs, Vim, Komodo, PyCharm, and Eclipse.
The document provides an introduction and overview of the Python programming language. It discusses that Python is an interpreted, object-oriented, high-level programming language that is easy to learn and read. It also covers Python features such as portability, extensive standard libraries, and support for functional, structured, and object-oriented programming. The document then discusses Python data types including numbers, strings, and various Python syntax elements before concluding with the history and evolution of the Python language through various versions.
Python is a widely-used and powerful computer programming language that has helped system administrators manage computer networks and problem solve computer systems for decades. Python has also built some popular applications like BitTorrent, Blender, Calibre, Dropbox, and much more. Going further, the “Pi” in Raspberry Pi stands for Python, so learning Python will instill more confidence when working with Raspberry Pi projects. Python is usually the first programming language people learn primarily because it is easy to learn and provides a solid foundation to learn other computer programming languages. In this webinar,
• Learn what Python is and what it is capable of doing.
• Install Python’s IDE for Windows and work in the Python shell.
• Use calculations, variables, strings, lists, and if statements.
• Discover Python’s built-in functions and understand modules.
• Create simple programs to build on later.
The recording is available at https://youtu.be/ThcWmJFf-ho.
Python is a popular programming language used in a variety of applications, including data analysis, web development, and artificial intelligence. Here's an introduction to the Basics of Python - A Beginners Guide! Whether you're new to programming or looking to brush up on your skills, this video covers the basics of Python programming language. From data types and operators to loops, functions and libraries, you'll get a solid foundation to start coding in Python.
Visit us: https://www.elewayte.com/
This document provides an agenda and overview for a Python tutorial presented over multiple sessions. The first session introduces Python and demonstrates how to use the Python interpreter. The second session covers basic Python data structures like lists, modules, input/output, and exceptions. An optional third session discusses unit testing. The document explains that Python is an easy to learn yet powerful programming language that supports object-oriented programming and high-level data structures in an interpreted, dynamic environment.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and optionally returning values. Strings are sequences of characters that can be manipulated using indexes and methods. Common string methods include upper() and concatenation using +.
This document discusses files in Python. It begins by defining what a file is and explaining that files enable persistent storage on disk. It then covers opening, reading from, and writing to files in Python. The main types of files are text and binary, and common file operations are open, close, read, and write. It provides examples of opening files in different modes, reading files line by line or in full, and writing strings or lists of strings to files. It also discusses searching files and handling errors when opening files. In the end, it presents some exercises involving copying files, counting words in a file, and converting decimal to binary.
OOPS concepts are one of the most important concepts in high level languages. Here in this PPT we will learn more about Object oriented approach in python programming which includes details related to classes and objects, inheritance, dat abstraction, polymorphism and many more with examples and code.
Provides an introductory level understanding of the Python Programming Language and language features. Serves as a guide for beginners and a reference to Python basics and language use cases.
Python main function. Main function is the entry point of any program. But python interpreter executes the source file code sequentially and doesn't call any method if it's not part of the code. But if it's directly part of the code then it will be executed when the file is imported as a module.
Python is a popular programming language created by Guido van Rossum in 1991. It is easy to use, powerful, and versatile, making it suitable for beginners and experts alike. Python code can be written and executed in the browser using Google Colab, which provides a Jupyter notebook environment and access to computing resources like GPUs. The document then discusses installing Python using Anaconda, basic Python concepts like indentation, variables, strings, conditionals, and loops.
This document provides an overview of the Python programming language. It begins by explaining what Python is - a general purpose, interpreted programming language that can be used as both a programming and scripting language. It then discusses the differences between programs and scripting languages. The history and creator of Python, Guido van Rossum, are outlined. The document explores the scope of Python and what tasks it can be used for. Popular companies and industries that use Python today are listed. Reasons why people use Python, such as it being free, powerful, and portable, are provided. Instructions for installing Python and running Python code are included. The document covers Python code execution and introduces basic Python concepts like variables, strings, data types, lists
This document provides an overview of the Python programming language. It begins by explaining what Python is, noting that it is a general purpose programming language that is often used for scripting. The key differences between program and scripting languages are then outlined. The history and creation of Python by Guido van Rossum are summarized, along with Python's scope in fields like science, system administration, and web development. Various uses of Python are listed, followed by who commonly uses Python today such as Google and YouTube. Reasons for Python's popularity include being free, powerful, and portable. The document concludes by covering installing Python, running and executing Python code, and some basic Python concepts like strings, variables, data types, and loops/
Python is a general purpose programming language that can be used for web development, system administration, science and more. It is interpreted rather than compiled, and was created in the 1990s by Guido van Rossum to be highly readable. Python is widely used by companies like Google, YouTube, Intel and more due to its power, flexibility and readability. It supports key programming concepts like variables, conditionals, loops, lists, tuples and more.
Introduction to Python 01-08-2023.pon by everyone else. . Hence, they must be...DRVaibhavmeshram1
172 slides•69 views
Python
Language
is uesd in engineeringStory adapted from Stephen Covey (2004) “The Seven Habits of Highly Effective People” Simon & Schuster).
“Management is doing things right, leadership is doing the right things”
(Warren Bennis and Peter Drucker)
Story adapted from Stephen Covey (2004) “The Seven Habits of Highly Effective People” Simon & Schuster).
“Management is doing things right, leadership is doing the right things”
(Warren Bennis and Peter Drucker)
Story adapted from Stephen Covey (2004) “The Seven Habits of Highly Effective People” Simon & Schuster).
“Management is doing things right, leadership is doing the right things”
(Warren Bennis and Peter Drucker)
The Sponsor:
Champion and advocates for the change at their level in the organization.
A Sponsor is the person who won’t let the change initiative die from lack of attention, and is willing to use their political capital to make the change happen
The Role model:
Behaviors and attitudes demonstrated by them are looked upon by everyone else. . Hence, they must be willing to go first.
Employees watch leaders for consistency between words and actions to see if they should believe the change is really going to happen.
The decision maker:
Leaders usually control resources such as people, budgets, and equipment, and thus have the authority to make decisions (as per their span of control) that affect the initiative.
During change, leaders must leverage their decision-making authority and choose the options that will support the initiative.
The Decision-Maker is decisive and sets priorities that support change.
The Sponsor:
Champion and advocates for the change at their level in the organization.
A Sponsor is the person who won’t let the change initiative die from lack of attention, and is willing to use their political capital to make the change happen
The Role model:
Behaviors and attitudes demonstrated by them are looked upon by everyone else. . Hence, they must be willing to go first.
Employees watch leaders for consistency between words and actions to see if they should believe the change is really going to happen.
The decision maker:
Leaders usually control resources such as people, budgets, and equipment, and thus have the authority to make decisions (as per their span of control) that affect the initiative.
During change, leaders must leverage their decision-making authority and choose the options that will support the initiative.
The Decision-Maker is decisive and sets priorities that support change.
The Sponsor:
Champion and advocates for the change at their level in the organization.
A Sponsor is the person who won’t let the change initiative die from lack of attention, and is willing to use their political capital to make the change happen
The Role model:
Behaviors and attitudes demonstrated by them are looked upon by everyone else. . Hence, they must be willing to go first.
Employees watch leaders for consistency between words and actions to see if they s
Daniel Greenfeld gave a presentation titled "Intro to Python". The presentation introduced Python and covered 21 cool things that can be done with Python, including running Python anywhere, learning Python quickly, introspecting Python objects, working with strings, lists, generators, sets and dictionaries. The presentation emphasized Python's simplicity, readability, extensibility and how it can be used for a wide variety of tasks.
Daniel Greenfeld gave a presentation titled "Intro to Python" where he demonstrated 21 cool things that can be done with Python. These included running Python anywhere, learning it quickly, introspecting objects to see their attributes and methods, performing string operations, formatting strings, basic math operations, and working with lists. The presentation emphasized Python's simplicity, readability, and extensive standard library and ecosystem.
AI Machine Learning Complete Course: for PHP & Python DevsAmr Shawqy
96 slides•956 views
Course Discounted Link:
https://www.udemy.com/ai-machine-learning-complete-course/?couponCode=SLIDESHAREDISCOUNT
Become an AI & Machine Learning developer, one of employer's most requested skills for 2018/2019!
Add value to your solutions and products, it is time to start using AI & Machine Learning now!
This course is different than any other AI or Machine Learning course; it requires no prior knowledge in AI or Machine Learning before, and you will be able to have your own AI Machine Learning application up and running right after the course.
This course is straight-forward, practical, and gives you all what you need to start your career in Machine Learning and Data Science. If you are a developer, programmer, technical student, manager, team leader, and you have not explored AI and Machine Learning before, this course is the best, most exciting, and complete course for you.
Examples of how you can build applications that identifies a string language, identify colors, identify human actions "like jump, sleep, anger, sadness etc." in a video, identify if a tweet or a Facebook post is positive or negative, that are all a few examples of what you can do in this course, all explained and you can do it all by yourself during the step by stop journey in this course.
This course will make all AI concepts, terminology, and approaches clear for you, so you understand how everything around you is going, and takes you in a series of a very interesting hands-on step by step examples on how to build amazing AI applications.
The following topics are covered:
- AI
- Rule & Logic Based AI
- Machine Learning
- Machine Learning Types (Supervised, Unsupervised, Reinforced, etc.)
- Machine Learning Algorithms
- Neural Networks & Deep Neural Networks
- Deep Learning
- PHP Step by Step Examples
- Python Step by Step Examples
- Language Detection
- Color Detection
- Human Actions Identification in Videos
- General String Classification
- Handling numerical data, string data, image data, voice data, and video data.
- PHP-ML
- scikit-learn
- numpy
- TensorFlow
- TensorFlow Hub
- Neural Networks Math Step by Step
- And Much More!
Python is a widely used programming language that allows developers to work quickly and integrate systems effectively. It is a general purpose, high-level, interpreted, and cross-platform language. Many large companies use Python, including Google, Facebook, Microsoft, and NASA. The introductory session covered installing Python, writing basic print statements and functions, working with objects, lists, modules, conditions, loops, and more Python concepts. Code examples were provided to demonstrate the core features of the Python language.
The document provides information about an introduction to Python programming presented by Kiattisak Anoochitarom. It begins with welcoming messages and details about the presenter. It then discusses various Python topics like data types, operators, control flow statements, functions, built-in functions, and string and list methods. Examples are provided throughout to demonstrate different Python concepts and syntax. The goal is to teach the basics of the Python language.
A versão 3 do Python teve seu lançamento final 2008, mas ainda há muitas dúvidas se já está na hora de escrever aplicações usando python 3. Eu irei mostrar sobre as diferenças entre o python 2 e o 3, as novidades e como portar seu código para o python 3.
( ** Python Certification Training: https://www.edureka.co/python ** )
This Edureka PPT on Advanced Python tutorial covers all the important aspects of using Python for advanced use-cases and purposes. It establishes all of the concepts like system programming , shell programming, pipes and forking to show how wide of a spectrum Python offers to the developers.
Python Tutorial Playlist: https://goo.gl/WsBpKe
Blog Series: http://bit.ly/2sqmP4s
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Python is a general purpose programming language that can be used for both programming and scripting. It was created in the 1990s by Guido van Rossum. Python is an interpreted language that is free, powerful, and portable. It can be used for tasks like web development, data analysis, and system scripting. The document provides an overview of Python including its history, uses, data types like strings and lists, and basic programming concepts like variables, conditionals, and loops. It recommends Python as a principal teaching language due to its free and easy installation, flexibility, use in academia and industry, and ability to offer a more rapid and enjoyable learning experience for students.
This document provides an outline and overview of a presentation on Python programming. The outline includes sections on what Python is, why Python, an introduction to Python, Python programming tips and tricks, more on Python, and the scientific module. Under each section, there are bullet points explaining key aspects of Python like its design, uses, basic syntax, data structures, functions, classes, modules, and popular scientific programming libraries like NumPy.
Python programming Workshop SITTTR - KalamasserySHAMJITH KM
150 slides•4.3K views
This document provides an overview of Python programming. It begins with an introduction and outlines topics to be covered including what Python is, its features, basics of syntax, importing, input/output functions, and more. Various Python concepts and code examples are then presented throughout in areas such as data types, operators, decision making with if/else statements, loops (for and while), functions, and classes. Examples include calculating square roots, the volume of a cylinder, checking for prime numbers, and a multiplication table. The document serves as teaching material for a Python programming course.
This document provides an introduction to the Java programming language. It discusses that Java is an object-oriented programming language used to write computer programs. It also describes the basic elements of the Java language including commands, variables, data types, control statements, and functions/methods. Additionally, it explains that the basic building block of Java is the class, and that a Java program or application consists of multiple classes organized into packages.
Data X Museum - Hari Museum Internasional 2022 - WMIDFariz Darari
32 slides•161 views
This document discusses the importance of preserving cultural heritage through museums and digitizing cultural artifacts and traditions. It provides statistics on the diversity of Indonesian culture and examples of how structured data and APIs can be used to catalog and provide access to cultural works, including examples from Wikidata and the Metropolitan Museum of Art. The document encourages utilizing structured data to digitally preserve traditions like rendang and making museum data widely available to promote cultural heritage for all.
Kuis tryout 1 mata kuliah Dasar-Dasar Pemrograman 2 Fasilkom UI berisi soal pilihan ganda dan esai tentang konsep-konsep dasar Java seperti tipe data, pewarisan, package, class, objek, dan string builder. Soal-soal tersebut bertujuan mengetes pemahaman mahasiswa terhadap materi pemrograman dasar yang telah diajarkan.
Game theory is the study of strategic decision making between interdependent parties. It analyzes situations where players make decisions that will impact outcomes for themselves and others. The document provides examples of classic game theory scenarios like the prisoner's dilemma and discusses concepts like dominant strategies, Nash equilibriums, and mixed strategies. It also presents a two-player "two-finger Morra game" to illustrate game theory principles.
Neural Networks and Deep Learning: An IntroFariz Darari
64 slides•1.3K views
This document provides an overview of neural networks and deep learning. It describes how artificial neurons are arranged in layers to form feedforward neural networks, with information fed from the input layer to subsequent hidden and output layers. Networks are trained using gradient descent to adjust weights between layers to minimize error. Convolutional neural networks are also discussed, which apply convolution and pooling operations to process visual inputs like images for tasks such as image classification. CNNs have achieved success in applications involving computer vision, natural language processing, and more.
Ringkasan dokumen tersebut adalah sebagai berikut:
1. Dokumen tersebut membahas tentang pengembangan talenta AI di perguruan tinggi dan hubungannya dengan industri, khususnya dalam memenuhi kebutuhan akan keterampilan AI.
2. Talenta AI di perguruan tinggi tidak hanya terfokus pada pendidikan AI saja, tetapi juga penelitian dan pengabdian masyarakat melalui teknologi AI.
3. Dibut
This document discusses several topics related to properly implementing AI in education, including:
1) Ensuring AI teacher evaluation and models are not biased toward specific demographic groups or teaching styles.
2) The importance of data quality when training AI models, such as removing duplicates and standardizing formats.
3) The need for explainable AI models.
4) Examples of non-machine learning AI applications, such as an automated study topic scheduler.
5) A reminder that we have a choice in how AI is designed to have a positive impact.
Featuring pointers for: Single-layer neural networks and multi-layer neural networks, gradient descent, backpropagation. Slides are for introduction, for deep explanation on deep learning, please consult other slides.
Current situation: focus is limited to only implement Tridharma, that is, education, research, and community service, with little concern on openness aspect.
The openness of Tridharma can potentially be a breakthrough in mitigating the quality gap issue: opening Tridharma outputs for public would help to increase the citizen inclusion in accessing the quality content of Tridharma, hence narrowing the quality gap in higher education.
Defense Slides of Avicenna Wisesa - PROWDFariz Darari
34 slides•190 views
This document presents ProWD, a tool for analyzing completeness in Wikidata. It introduces Wikidata and knowledge graphs, discusses issues like knowledge imbalance and inference errors due to lack of completeness awareness. It then presents a formal framework for completeness analysis using class, facet, and attribute profiles. This framework is implemented in ProWD, a proof of concept tool that allows analyzing Wikidata's completeness through single and compare views. ProWD is designed to be updated live and make completeness analysis accessible to laymen. Future work aims to expand the framework, improve scalability, and extend ProWD features.
This document provides an introduction to object-oriented programming concepts using Java. It begins by demonstrating how object-oriented thinking is natural through everyday examples of objects like cars and cats. It then defines key object-oriented programming terminology like class, object, attributes, and methods. The document walks through creating a sample Cube class to demonstrate these concepts in code. It shows how to define the class, instantiate objects, access attributes and call methods. The document also covers other OOP concepts like constructors, the toString() method, passing objects by reference, and the null value. Finally, it provides examples of real-world classes like String, LocalDate, Random and how to work with static variables and methods.
[ISWC 2013] Completeness statements about RDF data sources and their use for ...Fariz Darari
40 slides•95 views
This was presented at ISWC 2013 in Sydney, Australia.
Abstract:
With thousands of RDF data sources available on the Web covering disparate and possibly overlapping knowledge domains, the problem of providing high-level descriptions (in the form of metadata) of their content becomes crucial. In this paper we introduce a theoretical framework for describing data sources in terms of their completeness. We show how existing data sources can be described with completeness statements expressed in RDF. We then focus on the problem of the completeness of query answering over plain and RDFS data sources augmented with completeness statements. Finally, we present an extension of the completeness framework for federated data sources.
Testing in Python: doctest and unittest (Updated)Fariz Darari
33 slides•389 views
The document discusses testing in Python. It defines testing vs debugging, and explains why testing is important even for professional programmers. It provides examples of manually testing a square area function that initially had a bug, and how the bug was detected and fixed. It then introduces doctest and unittest as systematic ways to test in Python, providing examples of using each. Finally, it discusses test-driven development as a software development method where tests are defined before writing code.
Testing in Python: doctest and unittestFariz Darari
33 slides•562 views
The document discusses testing in Python. It defines testing vs debugging, and explains why testing is important even for professional programmers. It introduces doctest and unittest as systematic ways to test Python code. Doctest allows embedding tests in docstrings, while unittest involves writing separate test files. The document also covers test-driven development, which involves writing tests before coding to define desired behavior.
Dissertation Defense - Managing and Consuming Completeness Information for RD...Fariz Darari
70 slides•457 views
The ever increasing amount of Semantic Web data gives rise to the question: How complete is the data? Though generally data on the Semantic Web is incomplete, many parts of data are indeed complete, such as the children of Barack Obama and the crew of Apollo 11. This thesis aims to study how to manage and consume completeness information about Semantic Web data. In particular, we first discuss how completeness information can guarantee the completeness of query answering. Next, we propose optimization techniques of completeness reasoning and conduct experimental evaluations to show the feasibility of our approaches. We also provide a technique to check the soundness of queries with negation via reduction to query completeness checking. We further enrich completeness information with timestamps, enabling query answers to be checked up to when they are complete. We then introduce two demonstrators, i.e., CORNER and COOL-WD, to show how our completeness framework can be realized. Finally, we investigate an automated method to generate completeness statements from text on the Web via relation cardinality extraction.
The document provides information about research writing. It discusses that everyone can be considered a researcher through everyday activities like using social media or traveling. Research is defined as a careful, diligent search to establish new facts or reach conclusions. The constituents of research are outlined as defining problems, formulating hypotheses, collecting and analyzing data, and validating conclusions. The document emphasizes that research writing is important and discusses choosing the right research topic and venue for publication. It provides tips for writing different sections of a research paper and following the common three-phase model of initial workshop or conference papers leading to a journal publication.
KOI - Knowledge Of Incidents - SemEval 2018Fariz Darari
18 slides•109 views
We present KOI (Knowledge Of Incidents), a system that given news articles as input, builds a knowledge graph (KOI-KG) of incidental events.
KOI-KG can then be used to efficiently answer questions such as "How many killing incidents happened in 2017 that involve Sean?" The required steps in building the KG include:
(i) document preprocessing involving word sense disambiguation, named-entity recognition, temporal expression recognition and normalization, and semantic role labeling;
(ii) incidental event extraction and coreference resolution via document clustering; and (iii) KG construction and population.
Slides made and presented by Paramita.
Comparing Index Structures for Completeness ReasoningFariz Darari
43 slides•115 views
Data quality is a major issue in the development of knowledge graphs. Data completeness is a key factor in data quality that concerns the breadth, depth, and scope of information contained in knowledge graphs. As for large-scale knowledge graphs (e.g., DBpedia, Wikidata), it is conceivable that given the amount of information contained in there, they may be complete for a wide range of topics, such as children of Donald Trump, cantons of Switzerland, and presidents of Indonesia. Previous research has shown how one can augment knowledge graphs with statements about their completeness, stating which parts of data are complete. Such meta-information can be leveraged to check query completeness, that is, whether the answer returned by a query is complete. Yet, it is still unclear how such a check can be done in practice, especially when a large number of completeness statements are involved. We devise implementation techniques to make completeness reasoning in the presence of large sets of completeness statements feasible, and experimentally evaluate their effectiveness in realistic settings based on the characteristics of real-world knowledge graphs.
Discover how Agentic AI is transforming intelligent automation with goal-driven behavior, adaptive learning, and multi-agent collaboration. Learn its key features, benefits, and real-world applications driving innovation and efficiency.
AI/ML Infra Meetup | Optimizing ML Data Access with Alluxio: Preprocessing, ...Alluxio, Inc.
15 slides•76 views
AI/ML Infra Meetup
Mar. 06, 2025
Organized by Alluxio
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Bin Fan (VP of Technology @ Alluxio)
In this talk, Bin Fan shares his insights on data access challenges in ML applications, with particular emphasis on how Alluxio's distributed caching helps bridge the gap between storage and compute in preprocessing, pretraining and inference.
AIThe Rise of AI Twins: How Digital Twins Are Changing Business Strategyasmith539880
12 slides•13 views
Digital twins create virtual replicas of physical assets, enabling real-time monitoring and predictive analytics. This topic covers their role in optimizing production, logistics, and financial planning.
How Gamification Can Boost Engagement in Travel Appsmohit579916
9 slides•10 views
Boost user engagement in travel apps with gamification! This PPT explores how rewards, points, and interactive elements drive retention and enhance customer experience in the travel apps.
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You can rapidly generate, edit, combine, and edit digital files and documents. This program's structure is straightforward, and you may easily alter PDF files.
Fixing Project Portfolio Visibilit: How to Get Real-Time Insights for Better ...OnePlan Solutions
43 slides•33 views
Executives need a clear, real-time view of their portfolio to drive strategy, yet too often, they’re forced to make critical decisions based on outdated, incomplete, or siloed data. When project priorities shift and resources are stretched thin, a lack of visibility leads to misalignment, wasted investment, and uncertainty.
Join this webinar to learn how to eliminate strategic blind spots by implementing real-time portfolio insights, AI-driven prioritization, and integrated reporting—so you can see the full picture and make confident, data-backed decisions.
Building Effective Web Portals with Claris FileMakerDBServices1
26 slides•11 views
Discover how to design client and employee web portals in Claris FileMaker that enhance user experience and streamline workflows. This webinar will guide you through best practices for building web portals, including when to leverage WebDirect and when alternative approaches might be more effective. Gain insights into optimizing web portal performance, ensuring security, and creating a seamless, responsive experience for your users.
Unlock Free AI Technology for Seamless Mosaic Removal.pptxUndress Baby
12 slides•64 views
A free mosaic remover AI is a tool that uses artificial intelligence to restore or deblur pixelated areas in images, aiming to reveal hidden details. It works by predicting and filling in the obscured content, with varying effectiveness based on the complexity of the mosaic.
Web:- https://undressbaby.com/
Tuxera NTFS 2025 Crack +Activation key {Latest} Free version Downloadharoonsaeed605
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copy and past on google ➤ ➤➤ https://mediiafiire.com/
Tuxera NTFS provides fast, reliable read and write support for NTFS drives on macOS, ensuring seamless file access and transfer between Windows and Mac devices.
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This program encrypts your Internet traffic and hides your IP address from hackers and trackers, protecting your privacy and security. Just click the Connect button, we will pick the fastest and most stable servers for you.
7. 7
But this Python!
Programming Language
Freely Usable Even for Commercial UseCreated in 1991 by Guido van Rossum
Cross Platform
8. "Python is easy to use, powerful, and versatile, making it a great choice
for beginners and experts alike." – codeschool.com
8
print("Python" + " is " + "cool!")
9. print("Python" + " is " + "cool!")
"Python is easy to use, powerful, and versatile, making it a great choice
for beginners and experts alike." – codeschool.com
9
10. print("Python" + " is " + "cool!")
"Python is easy to use, powerful, and versatile, making it a great choice
for beginners and experts alike." – codeschool.com
10
public class Main {
public static void main(String[] args) {
System.out.println("Hello world!");
}
}
11. print("Python" + " is " + "cool!")
"Python is easy to use, powerful, and versatile, making it a great choice
for beginners and experts alike." – codeschool.com
11
public class Main {
public static void main(String[] args) {
System.out.println("Hello world!");
}
}
print("Hello world!")
12. "Python is easy to use, powerful, and versatile, making it a great choice
for beginners and experts alike." – codeschool.com
12
print("Python" + " is " + "cool!")
13. 13
print("Python" + " is " + "cool!")
"Python is easy to use, powerful, and versatile, making it a great choice
for beginners and experts alike." – codeschool.com
Big names using Python
14. "Python is easy to use, powerful, and versatile, making it a great choice
for beginners and experts alike." – codeschool.com
14
print("Python" + " is " + "cool!")
Image Processing using Python
https://opencv.org/
15. "Python is easy to use, powerful, and versatile, making it a great choice
for beginners and experts alike." – codeschool.com
15
print("Python" + " is " + "cool!")
Game Development using Python
https://www.pygame.org
16. "Python is easy to use, powerful, and versatile, making it a great choice
for beginners and experts alike." – codeschool.com
16
print("Python" + " is " + "cool!")
Data Science using Python
https://matplotlib.org/
17. "Python is easy to use, powerful, and versatile, making it a great choice
for beginners and experts alike." – codeschool.com
17
print("Python" + " is " + "cool!")
Natural Language Processing (NLP) and Text Mining using Python
https://github.com/amueller/word_cloud
19. How to install Python the Anaconda way
1. Download Anaconda (which includes Python):
https://www.anaconda.com/download/
2. Run the installer and follow the installation instructions
3. Run the Spyder editor and create your first Python program "helloworld.py"
19
Python Setup
20. • Variables store and give names to data values
• Data values can be of various types:
• int : -5, 0, 1000000
• float : -2.0, 3.14159
• bool : True, False
• str : "Hello world!", "K3WL"
• list : [1, 2, 3, 4], ["Hello", "world!"], [1, 2, "Hello"], [ ]
• And many more!
• In Python, variables do not have types!
• Data values are assigned to variables using "="
20
Variables and Data Types
x = 1 # this is a Python comment
x = x + 5
y = "Python" + " is " + "cool!"
23. • Cores of programming!
• Rely on boolean expressions which return either True or False
• 1 < 2 : True
• 1.5 >= 2.5 : False
• answer == "Computer Science" :
can be True or False depending on the value of variable answer
• Boolean expressions can be combined with: and, or, not
• 1 < 2 and 3 < 4 : True
• 1.5 >= 2.5 or 2 == 2 : True
• not 1.5 >= 2.5 : True
23
Conditionals and Loops
24. 24
Conditionals: Generic Form
if boolean-expression-1:
code-block-1
elif boolean-expression-2:
code-block-2
(as many elif's as you want)
else:
code-block-last
25. 25
Conditionals: Usia SIM (Driving license age)
age = 20
if age < 17:
print("Belum bisa punya SIM!")
else:
print("OK, sudah bisa punya SIM.")
26. 26
Conditionals: Usia SIM dengan Input
age = int(raw_input("Usia: ")) # use input() for Python 3
if age < 17:
print("Belum bisa punya SIM!")
else:
print("OK, sudah bisa punya SIM.")
28. • Useful for repeating code!
• Two variants:
28
Loops
while boolean-expression:
code-block
for element in collection:
code-block
29. 29
While Loops
while raw_input("Which is the best subject? ") != "Computer Science":
print("Try again!")
print("Of course it is!")
while boolean-expression:
code-block
30. So far, we have seen (briefly) two kinds of collections:
string and list
For loops can be used to visit each collection's element:
30
For Loops
for element in collection:
code-block
for chr in "string":
print(chr)
for elem in [1,3,5]:
print(elem)
35. • Code made by other people shall be reused!
• Two ways of importing modules (= Python files):
• Generic form: import module_name
import math
print(math.sqrt(4))
• Generic form: from module_name import function_name
from math import sqrt
print(sqrt(4))
35
Imports
37. • String is a sequence of characters, like "Python is cool"
• Each character has an index
• Accessing a character: string[index]
x = "Python is cool"
print(x[10])
• Accessing a substring via slicing: string[start:finish]
print(x[2:6])
37
String
P y t h o n i s c o o l
0 1 2 3 4 5 6 7 8 9 10 11 12 13
38. >>> x = "Python is cool"
>>> "cool" in x # membership
>>> len(x) # length of string x
>>> x + "?" # concatenation
>>> x.upper() # to upper case
>>> x.replace("c", "k") # replace characters in a string
38
String Operations
P y t h o n i s c o o l
0 1 2 3 4 5 6 7 8 9 10 11 12 13
39. >>> x = "Python is cool"
>>> x.split(" ") 39
String Operations: Split
P y t h o n i s c o o l
0 1 2 3 4 5 6 7 8 9 10 11 12 13
P y t h o n
0 1 2 3 4 5
i s
0 1
c o o l
0 1 2 3
x.split(" ")
40. >>> x = "Python is cool"
>>> y = x.split(" ")
>>> ",".join(y) 40
String Operations: Join
P y t h o n , i s , c o o l
0 1 2 3 4 5 6 7 8 9 10 11 12 13
P y t h o n
0 1 2 3 4 5
i s
0 1
c o o l
0 1 2 3
",".join(y)
42. • Working with data heavily involves reading and writing!
• Data come in two types:
• Text: Human readable, encoded in ASCII/UTF-8, example: .txt, .csv
• Binary: Machine readable, application-specific encoding,
example: .mp3, .mp4, .jpg
42
Input/Output
46. 46
Output
# write mode
x = open("carpe-diem.txt", "w")
x.write("carpendiemn")
x.close()
# append mode
x = open("carpe-diem.txt", "a")
x.write("carpendiemn")
x.close()
Write mode overwrites files,
while append mode does not overwrite files but instead appends at the end of the files' content
49. • If a string is a sequence of characters, then
a list is a sequence of items!
• List is usually enclosed by square brackets [ ]
• As opposed to strings where the object is fixed (= immutable),
we are free to modify lists (that is, lists are mutable).
49
Lists
x = [1, 2, 3, 4]
x[0] = 4
x.append(5)
print(x) # [4, 2, 3, 4, 5]
50. 50
List Operations
>>> x = [ "Python", "is", "cool" ]
>>> x.sort() # sort elements in x
>>> x[0:2] # slicing
>>> len(x) # length of string x
>>> x + ["!"] # concatenation
>>> x[2] = "hot" # replace element at index 0 with "hot"
>>> x.remove("Python") # remove the first occurrence of "Python"
>>> x.pop(0) # remove the element at index 0
51. It is basically a cool way of generating a list
51
List Comprehension
[expression for-clause condition]
Example:
[i*2 for i in [0,1,2,3,4] if i%2 == 0]
[i.replace("o", "i") for i in ["Python", "is", "cool"] if len(i) >= 3]
52. • Like a list, but you cannot modify it (= immutable)
• Tuple is usually (but not necessarily) enclosed by parentheses ()
• Everything that works with lists, works with tuples,
except functions modifying the tuples' content
• Example:
52
Tuples
x = (0,1,2)
y = 0,1,2 # same as x
x[0] = 2 # this gives an error
54. • As opposed to lists, in sets duplicates are removed and
there is no order of elements!
• Set is of the form { e1, e2, e3, ... }
• Operations include: intersection, union, difference.
• Example:
54
Sets
x = [0,1,2,0,0,1,2,2]
y = {0,1,2,0,0,1,2,2}
print(x)
print(y)
print(y & {1,2,3}) # intersection
print(y | {1,2,3}) # union
print(y - {1,2,3}) # difference
55. 55
Dictionaries
• Dictionaries map from keys to values!
• Content in dictionaries is not ordered.
• Dictionary is of the form { k1:v1, k2:v2, k3:v3, ... }
• Example:
x = {"indonesia":"jakarta", "germany":"berlin","italy":"rome"}
print(x["indonesia"]) # get value from key
x["japan"] = "tokyo" # add a new key-value pair to dictionary
print(x) # {'italy': 'rome', 'indonesia': 'jakarta', 'germany': 'berlin', 'japan': 'tokyo'}
57. • While in functions we encapsulate a set of instructions,
in classes we encapsulate objects!
• A class is a blueprint for objects, specifying:
• Attributes for objects
• Methods for objects
• A class can use other classes as a base
• Generic:
57
Classes
class class-name(base):
attribute-code-block
method-code-block
58. class Person:
def __init__(self, first, last):
self.firstname = first
self.lastname = last
def describe(self):
return self.firstname + " " + self.lastname
guido = Person("Guido","Van Rossum")
print(guido.describe())
58
Classes: Person
class class-name(base):
attribute-code-block
method-code-block
59. 59
Classes: Person & Employee
class class-name(base):
attribute-code-block
method-code-block
# first add code for class Person here
class Employee(Person):
def __init__(self, first, last, staffnum):
Person.__init__(self, first, last)
self.staffnum = staffnum
def describe(self):
return self.lastname + ", " + str(self.staffnum)
guido = Employee("Guido", "Van Rossum", 123456)
print(guido.describe())
#3: African rock pythons are the largest species of snake in Africa.
PHOTOGRAPH BY JOEL SARTORE, NATIONAL GEOGRAPHIC PHOTO ARK
https://emojiisland.com/pages/download-new-emoji-icons-in-png-ios-10
#38: start: where we start taking the substring
finish: the index one after we end the substring
#42: https://www.pexels.com/photo/alphabet-boogle-dice-enjoy-262529/
This Latin phrase, which literally means "pluck the day," was used by the Roman poet Horace to express the idea that we should enjoy life while we can. His full injunction, "carpe diem quam minimum credula postero,” can be translated as “pluck the day, trusting as little as possible in the next one,” but carpe diem alone has come to be used as shorthand for this entire idea, which is more widely known as "seize the day."
#61: https://commons.wikimedia.org/wiki/File:Blauwdruk-Ronhaar.jpg
1923 blueprint for shophouse with bakery Ronhaar at the Hammerweg in Ommen, demolished in 2007; the almost flat upper part of the mansard roof is found in the central and eastern Netherlands, but is virtually unknown in the river area and in the southern part of the Netherlands.