This is the presentation for the three-session intermediate Python programming course which I developed and successfully presented for the CoderDojo workshop held in Microsoft Silicon Valley in March 2016.
This document provides an introduction to the Python programming language. It discusses what Python is, its history and creator, why it is popular, who uses it, and how to get started with the syntax. Key topics covered include Python's readability, dynamic typing, standard library, and use across many industries. The document also includes code examples demonstrating basic Python concepts like variables, strings, control flow, functions, and file input/output.
Python is a multi-paradigm programming language created in 1989 by Guido van Rossum. It is based on ABC and Modula-3 and was named after Monty Python. Python has a simple syntax and dynamic typing and memory management. It can be used for web development, data science, scientific computing, and more. The core philosophy is summarized in the Zen of Python document. Python code is written, tested, and executed using integrated development environments like PyCharm or directly from the command line.
This document provides an overview of the Python programming language, including its history, key features, syntax examples, and common uses. It also discusses how Python can be used under Linux and some potential issues.
This document provides an overview of the Python programming language. It discusses what Python is, its key features like being multi-purpose, readable, and productive. It then demonstrates Hello World programs in Python, C++, Java, and PHP. The rest of the document covers Python concepts like operators, variables, strings, lists, conditions, loops, functions, object oriented programming, and design patterns like strategy, closure, generator, and decorator patterns.
This document provides an overview of NumPy, the core library for scientific computing in Python. It discusses NumPy arrays, which provide a grid of values that are all of the same type and indexed by tuples of integers. NumPy arrays can be initialized from nested lists and accessed using square brackets. NumPy also provides functions to create arrays filled with zeros, ones, random values, or a constant. The document covers slicing NumPy arrays to extract subarrays, and integer array indexing to construct arbitrary arrays from another array's data. It demonstrates how slicing returns views into the original data, while integer indexing allows selecting elements in any order.
Functional Programming & Event Sourcing - a pair made in heavenPawel Szulc
The document discusses functional programming and event sourcing. It begins with an overview of functional programming principles like avoiding side effects and variable mutation. It then provides examples of modeling user data retrieval in a functional way using classes like Cache, UserRepo, and UserFinder. The examples demonstrate functional patterns like avoiding stateful objects and embracing immutable and recursive functions. The document argues that functional programming and event sourcing are well-aligned due to their shared emphasis on immutable data models and avoidance of shared state.
It's happened to all of us: we ran away from some conversation or library because it kept on using those "weird" phrases. You know, like "type classes", "semigroups", "monoids", "applicatives". Yikes! They all seem so academic, so pointlessly detached from real-world problems. But then again, given how frequently we run into them in functional programming, are they REALLY irrelevant, or do they have real-world applications? This talk will go beyond giving you raw definitions of these terms, and show you real-world motivations behind the concepts. By attending, you'll be able to keep your skills relevant to an ever-changing industry, confuse your significant other ("You know, honey, a monad is just a monoid in the category of endofunctors!"), and sound extra smart on the next job interview!
This document provides an overview of the Python programming language. It includes several code examples and summaries of key Python concepts like strings, lists, tuples, dictionaries, files, regular expressions, and object-oriented programming. It also lists some common Python functions and modules for tasks like HTTP requests and database access. The document aims to introduce Python's main features and provide basic code samples to help new Python learners.
Python is a programming language developed in 1989 that is still actively developed. It draws influences from languages like Perl, Java, C, C++, and others. Python code is portable, free, and recommended for tasks like system administration scripts, web development, scientific computing, and rapid prototyping. It has a simple syntax and is optionally object-oriented and multi-threaded. Python has extensive libraries for tasks like string manipulation, web programming, databases, and interface design. Popular applications of Python include web development, data analysis, scientific computing, and scripting.
Scala presentation by Aleksandar ProkopecLoïc Descotte
This document provides an introduction to the Scala programming language. It discusses how Scala runs on the Java Virtual Machine, supports both object-oriented and functional programming paradigms, and provides features like pattern matching, immutable data structures, lazy evaluation, and parallel collections. Scala aims to be concise, expressive, and extensible.
The document discusses the authors' initial naive expectations for using Scala and Clojure compared to their actual experience. They initially thought the languages would solve issues like boilerplate code and Java compiler problems, but found they still had to deal with interoperability, immutability, and other functional programming concepts. In the end, Clojure met more of their needs due to its emphasis on seamless interoperability, traits, and pattern matching.
This document discusses principles of writing clean code for readability and maintainability. It defines clean code as code that is simple, direct and reads like well-written prose. Clean code should have meaningful names, small and focused functions, minimal comments, and use exceptions for error handling rather than return codes. Classes should also have a single well-described responsibility and follow the single responsibility principle. Overall, writing clean code produces benefits during development and makes the code easier to maintain going forward.
Concurrent programming with Celluloid (MWRC 2012)tarcieri
Threads versus events: which should you choose? How about both? In this talk you'll learn about the Celluloid concurrency framework, which combines OOP and the Actor Model to give you concurrent Ruby objects. You'll also learn about how Celluloid lets you combine blocking I/O and asynchronous evented I/O, offering you all the benefits of EventMachine without the restrictions of a single event loop. The talk will also provide a brief introduction to DCell, a distributed extension to Celluloid.
Odessapy2013 - Graph databases and PythonMax Klymyshyn
Page 10 "Я из Одессы я просто бухаю." translation: I'm from Odessa I just drink. Meaning his drinking a lot of "Vodka" ^_^ (@tuc @hackernews)
This is local meme - when someone asking question and you will look stupid in case you don't have answer.
Explores how to write a tic-tac-toe API that meets some interesting static typing constraints. Specifically, programs using the API may fail to compile, depending on the state of play in the game, such as trying to call move() with an already completed game board. The real theme of the presentation is not so much solving the tic-tac-toe problem but, rather, pushing static typing to its limits (and some might argue beyond its useful limits—you will have to judge for yourself).
Slides for the presentation that I made for LambdaConf 2015 in Boulder
Codebase available at http://www.slideshare.net/paulszulc/monads-asking-the-right-question
What can be done with Java, but should better be done with Erlang (@pavlobaron)Pavlo Baron
Erlang excels at building distributed, fault-tolerant, concurrent applications due to its lightweight process model and built-in support for distribution. However, Java is more full-featured and is generally a better choice for applications that require more traditional object-oriented capabilities or need to interface with existing Java libraries and frameworks. Both languages have their appropriate uses depending on the requirements of the specific application being developed.
Designing with Groovy Traits - Gr8Conf IndiaNaresha K
The document discusses using traits in Groovy to provide reusable behaviors and properties to classes without relying on inheritance. It describes how traits allow for mixing in multiple capabilities, overriding trait methods, implementing interfaces, declaring abstract methods, and having state. Traits can extend other traits and resolve conflicts using finer control. Traits also allow applying behaviors at runtime and composing common fields. Examples demonstrate composing user context, auditing objects, chaining approvals, and more.
In which Richard will tell you about some things you should never (probably ever) do to or in Python. Warranties may be voided. The recording of this talk is online at http://www.youtube.com/watch?v=H2yfXnUb1S4
Clojure for Java developers - StockholmJan Kronquist
This document provides an overview of the Clojure programming language from the perspective of a Java developer. It begins with an introduction to the presenter and an outline of what will not be covered. It then discusses some popular Clojure applications and frameworks. The core sections explain that Clojure was created in 2007, is a Lisp dialect that runs on the JVM and JavaScript, and is designed for concurrency. It provides an example of Clojure code, discusses reasons for using Clojure like its functional nature and interactive development environment. It addresses common complaints about Clojure and discusses Lisp concepts. It also covers Clojure data types, programming structures, working with Java classes using macros, editor support
The document discusses using Groovy to create a turtle graphics domain specific language (DSL). Key points:
- Turtle graphics is a vector-based graphics concept using a relative cursor called a "turtle" to draw.
- The author created a Turtle class in Groovy to allow drawing on a canvas via turtle commands. A Groovy shell is used to execute scripts with bindings to provide the Turtle object.
- Various techniques are discussed to customize the language, including adding imports, defining a base script class, and routing method calls through the Turtle object to enable turtle commands.
- The author demonstrates how to execute scripts securely by removing dangerous language features like loops or increment operators.
This document provides an overview and introduction to Python programming. It covers setting up Python, background on the language, basic syntax like printing, variables, operators, control structures, functions, and data structures. It encourages participation and practicing the concepts by following along. The goal is to teach the fundamentals of Python in an interactive class format.
Vim Script allows for programming Vim's interface through scripting. It discusses variables, functions, conditional statements, loops, built-in functions, autocommands, commands, and the runtime directory structure for plugins. The document provides an overview of Vim Script programming with examples.
Python Workshop - Learn Python the Hard WayUtkarsh Sengar
This document provides an introduction to learning Python. It discusses prerequisites for Python, basic Python concepts like variables, data types, operators, conditionals and loops. It also covers functions, files, classes and exceptions handling in Python. The document demonstrates these concepts through examples and exercises learners to practice char frequency counting and Caesar cipher encoding/decoding in Python. It encourages learners to practice more to master the language and provides additional learning resources.
This document contains a dictionary that maps nucleotide sequences to amino acids. It defines the genetic code by listing the 3-letter codon sequences and their corresponding single-letter amino acid abbreviations. The document also contains some example nucleotide sequences and a prompt to find the answer in the file ultimate-sequence.txt.
It's happened to all of us: we ran away from some conversation or library because it kept on using those "weird" phrases. You know, like "type classes", "semigroups", "monoids", "applicatives". Yikes! They all seem so academic, so pointlessly detached from real-world problems. But then again, given how frequently we run into them in functional programming, are they REALLY irrelevant, or do they have real-world applications? This talk will go beyond giving you raw definitions of these terms, and show you real-world motivations behind the concepts. By attending, you'll be able to keep your skills relevant to an ever-changing industry, confuse your significant other ("You know, honey, a monad is just a monoid in the category of endofunctors!"), and sound extra smart on the next job interview!
This document provides an overview of the Python programming language. It includes several code examples and summaries of key Python concepts like strings, lists, tuples, dictionaries, files, regular expressions, and object-oriented programming. It also lists some common Python functions and modules for tasks like HTTP requests and database access. The document aims to introduce Python's main features and provide basic code samples to help new Python learners.
Python is a programming language developed in 1989 that is still actively developed. It draws influences from languages like Perl, Java, C, C++, and others. Python code is portable, free, and recommended for tasks like system administration scripts, web development, scientific computing, and rapid prototyping. It has a simple syntax and is optionally object-oriented and multi-threaded. Python has extensive libraries for tasks like string manipulation, web programming, databases, and interface design. Popular applications of Python include web development, data analysis, scientific computing, and scripting.
Scala presentation by Aleksandar ProkopecLoïc Descotte
This document provides an introduction to the Scala programming language. It discusses how Scala runs on the Java Virtual Machine, supports both object-oriented and functional programming paradigms, and provides features like pattern matching, immutable data structures, lazy evaluation, and parallel collections. Scala aims to be concise, expressive, and extensible.
The document discusses the authors' initial naive expectations for using Scala and Clojure compared to their actual experience. They initially thought the languages would solve issues like boilerplate code and Java compiler problems, but found they still had to deal with interoperability, immutability, and other functional programming concepts. In the end, Clojure met more of their needs due to its emphasis on seamless interoperability, traits, and pattern matching.
This document discusses principles of writing clean code for readability and maintainability. It defines clean code as code that is simple, direct and reads like well-written prose. Clean code should have meaningful names, small and focused functions, minimal comments, and use exceptions for error handling rather than return codes. Classes should also have a single well-described responsibility and follow the single responsibility principle. Overall, writing clean code produces benefits during development and makes the code easier to maintain going forward.
Concurrent programming with Celluloid (MWRC 2012)tarcieri
Threads versus events: which should you choose? How about both? In this talk you'll learn about the Celluloid concurrency framework, which combines OOP and the Actor Model to give you concurrent Ruby objects. You'll also learn about how Celluloid lets you combine blocking I/O and asynchronous evented I/O, offering you all the benefits of EventMachine without the restrictions of a single event loop. The talk will also provide a brief introduction to DCell, a distributed extension to Celluloid.
Odessapy2013 - Graph databases and PythonMax Klymyshyn
Page 10 "Я из Одессы я просто бухаю." translation: I'm from Odessa I just drink. Meaning his drinking a lot of "Vodka" ^_^ (@tuc @hackernews)
This is local meme - when someone asking question and you will look stupid in case you don't have answer.
Explores how to write a tic-tac-toe API that meets some interesting static typing constraints. Specifically, programs using the API may fail to compile, depending on the state of play in the game, such as trying to call move() with an already completed game board. The real theme of the presentation is not so much solving the tic-tac-toe problem but, rather, pushing static typing to its limits (and some might argue beyond its useful limits—you will have to judge for yourself).
Slides for the presentation that I made for LambdaConf 2015 in Boulder
Codebase available at http://www.slideshare.net/paulszulc/monads-asking-the-right-question
What can be done with Java, but should better be done with Erlang (@pavlobaron)Pavlo Baron
Erlang excels at building distributed, fault-tolerant, concurrent applications due to its lightweight process model and built-in support for distribution. However, Java is more full-featured and is generally a better choice for applications that require more traditional object-oriented capabilities or need to interface with existing Java libraries and frameworks. Both languages have their appropriate uses depending on the requirements of the specific application being developed.
Designing with Groovy Traits - Gr8Conf IndiaNaresha K
The document discusses using traits in Groovy to provide reusable behaviors and properties to classes without relying on inheritance. It describes how traits allow for mixing in multiple capabilities, overriding trait methods, implementing interfaces, declaring abstract methods, and having state. Traits can extend other traits and resolve conflicts using finer control. Traits also allow applying behaviors at runtime and composing common fields. Examples demonstrate composing user context, auditing objects, chaining approvals, and more.
In which Richard will tell you about some things you should never (probably ever) do to or in Python. Warranties may be voided. The recording of this talk is online at http://www.youtube.com/watch?v=H2yfXnUb1S4
Clojure for Java developers - StockholmJan Kronquist
This document provides an overview of the Clojure programming language from the perspective of a Java developer. It begins with an introduction to the presenter and an outline of what will not be covered. It then discusses some popular Clojure applications and frameworks. The core sections explain that Clojure was created in 2007, is a Lisp dialect that runs on the JVM and JavaScript, and is designed for concurrency. It provides an example of Clojure code, discusses reasons for using Clojure like its functional nature and interactive development environment. It addresses common complaints about Clojure and discusses Lisp concepts. It also covers Clojure data types, programming structures, working with Java classes using macros, editor support
The document discusses using Groovy to create a turtle graphics domain specific language (DSL). Key points:
- Turtle graphics is a vector-based graphics concept using a relative cursor called a "turtle" to draw.
- The author created a Turtle class in Groovy to allow drawing on a canvas via turtle commands. A Groovy shell is used to execute scripts with bindings to provide the Turtle object.
- Various techniques are discussed to customize the language, including adding imports, defining a base script class, and routing method calls through the Turtle object to enable turtle commands.
- The author demonstrates how to execute scripts securely by removing dangerous language features like loops or increment operators.
This document provides an overview and introduction to Python programming. It covers setting up Python, background on the language, basic syntax like printing, variables, operators, control structures, functions, and data structures. It encourages participation and practicing the concepts by following along. The goal is to teach the fundamentals of Python in an interactive class format.
Vim Script allows for programming Vim's interface through scripting. It discusses variables, functions, conditional statements, loops, built-in functions, autocommands, commands, and the runtime directory structure for plugins. The document provides an overview of Vim Script programming with examples.
Python Workshop - Learn Python the Hard WayUtkarsh Sengar
This document provides an introduction to learning Python. It discusses prerequisites for Python, basic Python concepts like variables, data types, operators, conditionals and loops. It also covers functions, files, classes and exceptions handling in Python. The document demonstrates these concepts through examples and exercises learners to practice char frequency counting and Caesar cipher encoding/decoding in Python. It encourages learners to practice more to master the language and provides additional learning resources.
This document contains a dictionary that maps nucleotide sequences to amino acids. It defines the genetic code by listing the 3-letter codon sequences and their corresponding single-letter amino acid abbreviations. The document also contains some example nucleotide sequences and a prompt to find the answer in the file ultimate-sequence.txt.
This document provides an overview of Python for bioinformatics. It discusses what Python is, why it is useful for bioinformatics, and how to get started with Python. It also covers Python IDEs like Eclipse and PyDev, code sharing with Git and GitHub, strings, regular expressions, and other Python concepts.
This document discusses Kotlin coroutines and how they can be used with the Spring Framework. It provides an overview of coroutines, explaining concepts like fibers, green threads, and suspendable computations. It also covers using coroutines with Spring features like the @Async annotation and asynchronous MVC return types. The document provides code examples of coroutines concepts like channels, jobs, and yielding in sequences.
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.
The basics of Python are rather straightforward. In a few minutes you can learn most of the syntax. There are some gotchas along the way that might appear tricky. This talk is meant to bring programmers up to speed with Python. They should be able to read and write Python.
Basic Python Programming: Part 01 and Part 02Fariz Darari
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.
Crystal is a compiled language that aims to provide Ruby-like syntax with static typing. It compiles to native code, allowing for performance comparable to C/C++. Crystal uses LLVM as a backend, providing type inference, concurrency support, bindings to native libraries, and metaprogramming capabilities. The language is still in active development but has growing adoption, with over 1500 libraries and 80 sponsors supporting continued development.
This document contains notes from a Python class covering functions, lists, strings, and their methods. It discusses built-in functions like len(), range(), and type conversions. It also covers control flow structures like if/else, for loops, exceptions, modules, and functions in more detail including defining functions, parameters, arguments, returning values, docstring, and variable scopes. Assignments include writing functions to process lists and check for palindromes in strings.
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.
This document provides an introduction to the Python programming language over 30 slides. It covers key Python concepts like variables, data types, conditionals, loops, functions, imports, strings, lists, tuples, sets, dictionaries, classes and input/output. Examples are given for each concept to demonstrate how it works in Python. The document concludes by encouraging the reader to continue learning Python through online documentation and resources.
The document provides information about the Go programming language. It discusses the history and creators of Go, key features of the language such as concurrency and garbage collection, basic Go code examples, and common data types like slices and maps. It also covers Go tools, environments, benchmarks showing Go's performance, and examples of companies using Go in production.
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.
Clojure is a LISP-like programming language that runs on the Java Virtual Machine. It was created in 2007 by Rich Hickey and is currently at version 1.1. Clojure is a functional, immutable, and concurrency-oriented language. It features LISP syntax, macros, immutability, functional programming, and easy interoperability with Java. Data structures in Clojure are code, allowing homoiconicity. Clojure also supports lazy sequences, STM-based concurrency without locks, and dynamic behavior via its REPL.
GE8151 Problem Solving and Python ProgrammingMuthu Vinayagam
The document provides information about various Python concepts like print statement, variables, data types, operators, conditional statements, loops, functions, modules, exceptions, files and packages. It explains print statement syntax, how variables work in Python, built-in data types like numbers, strings, lists, dictionaries and tuples. It also discusses conditional statements like if-else, loops like while and for, functions, modules, exceptions, file handling operations and packages in Python.
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.
The document discusses several key points about Python:
1. It summarizes praise for Python from programmers and companies like Google, NASA, and CCP Games, highlighting Python's simplicity, compactness, and ability to quickly develop applications.
2. It introduces common Python concepts like strings, lists, sequences, namespaces, polymorphism, and duck typing. Strings can be manipulated using slicing and methods. Lists and other sequences support indexing, slicing, and iteration.
3. Python uses name-based rather than type-based polymorphism through duck typing - an object's capabilities are defined by its methods and properties rather than its class.
This presentation about Python Interview Questions will help you crack your next Python interview with ease. The video includes interview questions on Numbers, lists, tuples, arrays, functions, regular expressions, strings, and files. We also look into concepts such as multithreading, deep copy, and shallow copy, pickling and unpickling. This video also covers Python libraries such as matplotlib, pandas, numpy,scikit and the programming paradigms followed by Python. It also covers Python library interview questions, libraries such as matplotlib, pandas, numpy and scikit. This video is ideal for both beginners as well as experienced professionals who are appearing for Python programming job interviews. Learn what are the most important Python interview questions and answers and know what will set you apart in the interview process.
Simplilearn’s Python Training Course is an all-inclusive program that will introduce you to the Python development language and expose you to the essentials of object-oriented programming, web development with Django and game development. Python has surpassed Java as the top language used to introduce U.S. students to programming and computer science. This course will give you hands-on development experience and prepare you for a career as a professional Python programmer.
What is this course about?
The All-in-One Python course enables you to become a professional Python programmer. Any aspiring programmer can learn Python from the basics and go on to master web development & game development in Python. Gain hands on experience creating a flappy bird game clone & website functionalities in Python.
What are the course objectives?
By the end of this online Python training course, you will be able to:
1. Internalize the concepts & constructs of Python
2. Learn to create your own Python programs
3. Master Python Django & advanced web development in Python
4. Master PyGame & game development in Python
5. Create a flappy bird game clone
The Python training course is recommended for:
1. Any aspiring programmer can take up this bundle to master Python
2. Any aspiring web developer or game developer can take up this bundle to meet their training needs
Learn more at https://www.simplilearn.com/mobile-and-software-development/python-development-training
Increasing Retail Store Efficiency How can Planograms Save Time and Money.pptxAnoop Ashok
In today's fast-paced retail environment, efficiency is key. Every minute counts, and every penny matters. One tool that can significantly boost your store's efficiency is a well-executed planogram. These visual merchandising blueprints not only enhance store layouts but also save time and money in the process.
Generative Artificial Intelligence (GenAI) in BusinessDr. Tathagat Varma
My talk for the Indian School of Business (ISB) Emerging Leaders Program Cohort 9. In this talk, I discussed key issues around adoption of GenAI in business - benefits, opportunities and limitations. I also discussed how my research on Theory of Cognitive Chasms helps address some of these issues
The Evolution of Meme Coins A New Era for Digital Currency ppt.pdfAbi john
Analyze the growth of meme coins from mere online jokes to potential assets in the digital economy. Explore the community, culture, and utility as they elevate themselves to a new era in cryptocurrency.
Quantum Computing Quick Research Guide by Arthur MorganArthur Morgan
This is a Quick Research Guide (QRG).
QRGs include the following:
- A brief, high-level overview of the QRG topic.
- A milestone timeline for the QRG topic.
- Links to various free online resource materials to provide a deeper dive into the QRG topic.
- Conclusion and a recommendation for at least two books available in the SJPL system on the QRG topic.
QRGs planned for the series:
- Artificial Intelligence QRG
- Quantum Computing QRG
- Big Data Analytics QRG
- Spacecraft Guidance, Navigation & Control QRG (coming 2026)
- UK Home Computing & The Birth of ARM QRG (coming 2027)
Any questions or comments?
- Please contact Arthur Morgan at [email protected].
100% human made.
Role of Data Annotation Services in AI-Powered ManufacturingAndrew Leo
From predictive maintenance to robotic automation, AI is driving the future of manufacturing. But without high-quality annotated data, even the smartest models fall short.
Discover how data annotation services are powering accuracy, safety, and efficiency in AI-driven manufacturing systems.
Precision in data labeling = Precision on the production floor.
TrustArc Webinar: Consumer Expectations vs Corporate Realities on Data Broker...TrustArc
Most consumers believe they’re making informed decisions about their personal data—adjusting privacy settings, blocking trackers, and opting out where they can. However, our new research reveals that while awareness is high, taking meaningful action is still lacking. On the corporate side, many organizations report strong policies for managing third-party data and consumer consent yet fall short when it comes to consistency, accountability and transparency.
This session will explore the research findings from TrustArc’s Privacy Pulse Survey, examining consumer attitudes toward personal data collection and practical suggestions for corporate practices around purchasing third-party data.
Attendees will learn:
- Consumer awareness around data brokers and what consumers are doing to limit data collection
- How businesses assess third-party vendors and their consent management operations
- Where business preparedness needs improvement
- What these trends mean for the future of privacy governance and public trust
This discussion is essential for privacy, risk, and compliance professionals who want to ground their strategies in current data and prepare for what’s next in the privacy landscape.
UiPath Community Berlin: Orchestrator API, Swagger, and Test Manager APIUiPathCommunity
Join this UiPath Community Berlin meetup to explore the Orchestrator API, Swagger interface, and the Test Manager API. Learn how to leverage these tools to streamline automation, enhance testing, and integrate more efficiently with UiPath. Perfect for developers, testers, and automation enthusiasts!
📕 Agenda
Welcome & Introductions
Orchestrator API Overview
Exploring the Swagger Interface
Test Manager API Highlights
Streamlining Automation & Testing with APIs (Demo)
Q&A and Open Discussion
Perfect for developers, testers, and automation enthusiasts!
👉 Join our UiPath Community Berlin chapter: https://community.uipath.com/berlin/
This session streamed live on April 29, 2025, 18:00 CET.
Check out all our upcoming UiPath Community sessions at https://community.uipath.com/events/.
Big Data Analytics Quick Research Guide by Arthur MorganArthur Morgan
This is a Quick Research Guide (QRG).
QRGs include the following:
- A brief, high-level overview of the QRG topic.
- A milestone timeline for the QRG topic.
- Links to various free online resource materials to provide a deeper dive into the QRG topic.
- Conclusion and a recommendation for at least two books available in the SJPL system on the QRG topic.
QRGs planned for the series:
- Artificial Intelligence QRG
- Quantum Computing QRG
- Big Data Analytics QRG
- Spacecraft Guidance, Navigation & Control QRG (coming 2026)
- UK Home Computing & The Birth of ARM QRG (coming 2027)
Any questions or comments?
- Please contact Arthur Morgan at [email protected].
100% human made.
How Can I use the AI Hype in my Business Context?Daniel Lehner
𝙄𝙨 𝘼𝙄 𝙟𝙪𝙨𝙩 𝙝𝙮𝙥𝙚? 𝙊𝙧 𝙞𝙨 𝙞𝙩 𝙩𝙝𝙚 𝙜𝙖𝙢𝙚 𝙘𝙝𝙖𝙣𝙜𝙚𝙧 𝙮𝙤𝙪𝙧 𝙗𝙪𝙨𝙞𝙣𝙚𝙨𝙨 𝙣𝙚𝙚𝙙𝙨?
Everyone’s talking about AI but is anyone really using it to create real value?
Most companies want to leverage AI. Few know 𝗵𝗼𝘄.
✅ What exactly should you ask to find real AI opportunities?
✅ Which AI techniques actually fit your business?
✅ Is your data even ready for AI?
If you’re not sure, you’re not alone. This is a condensed version of the slides I presented at a Linkedin webinar for Tecnovy on 28.04.2025.
Dev Dives: Automate and orchestrate your processes with UiPath MaestroUiPathCommunity
This session is designed to equip developers with the skills needed to build mission-critical, end-to-end processes that seamlessly orchestrate agents, people, and robots.
📕 Here's what you can expect:
- Modeling: Build end-to-end processes using BPMN.
- Implementing: Integrate agentic tasks, RPA, APIs, and advanced decisioning into processes.
- Operating: Control process instances with rewind, replay, pause, and stop functions.
- Monitoring: Use dashboards and embedded analytics for real-time insights into process instances.
This webinar is a must-attend for developers looking to enhance their agentic automation skills and orchestrate robust, mission-critical processes.
👨🏫 Speaker:
Andrei Vintila, Principal Product Manager @UiPath
This session streamed live on April 29, 2025, 16:00 CET.
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9. Boolean Operators
• These are logic checks that you can use to
determine when actions should happen
• and, or, != (not equal), == (equal to),
> (greater than), < (less than), >= (greater than
or equal to), <= (less than or equal to), and
True/False
10. Important
• In computers the equal sign can mean
different things!!!
• In Python
= assignment (let var a take the value b)
== comparison (if var a equals var b)
12. What can we compare?
• Numbers ( 2, 3, 5, 5.5, 7.5, 8 )
• Strings (“alex”, “bert”, “cindy”)
• Dates and times
(for all orderable types – two values)
• Numbers and strings?
• Numbers and dates/times?
13. If/Else Statement
• A statement that will run one set of code if a
condition is met, and the other set of code if a
condition is not met.
• Condition is written as a Boolean expression
that returns True or False
21. STRINGS AND COLLECTIONS
Session 2
https://github.com/alaudo/coderdojo-python
http://enigmacode.azurewebsites.net/
22. Recap from last session
age = input("What is your age? ")
if age =< 10:
print("You are below 10!")
if age = 10:
print("You are exactly 10!")
if age => 10:
print("Your are above 10!")
How many errors can you find here?
23. Recap from last session
m = 3
s = 0
for i in range (1,m):
s = s + i
print(s)
What number will this program print?
30. How to test for empty string?
text = input("Enter something ")
if (text):
print("This text is not empty")
else:
print("This text is EMPTY")
What about just spaces in the string?
31. How find how long a string is?
text = input("Enter something ")
print (len(text))
But how to print the text WITH numbers?
32. Pretty printing in Python?
print("My length is " + str(len("My length is")))
print("My favorite programming language is %s " % "python")
print("{} and {} are best friends".format("me", "my papa"))
print("My name is {name} and I am {age} years old".format(name = "Alex", age = 37))
34. Pretty printing in Python?
print("I am a good programmer".replace("good","not really good"))
print("<***>".join(["one","two","three","four"]))
print(''.join(reversed("I am a good string")))
print("I am a good athlete".split(" "))
35. Lists
• A list is a container that holds other
objects/values
• A list can be as large as you need it to be
• You can access the values inside a list at any
time as long as you have the list
36. Hidden lists
for i in range(0,10):
print(i)
print(list(range(0,10)))
txt = "pizza is no longer hot"
for i in txt:
print(i)
print(list(txt))
Lists, they are everywhere…
37. Browsing lists
a = "Jingle bells, Jingle bells
Jingle all the way Oh what fun it
is to ride"
print(a[0])
print(a[1])
print(a[0:10])
print(a[0:10:2])
print(a[::3])
print(a[::-1])
38. Browsing lists (2)
a = "Jingle bells, Jingle bells
Jingle all the way Oh what fun it
is to ride“
a = a.split(“ “)
print(a[0])
print(a[1])
print(a[0:10])
print(a[0:10:2])
print(a[::3])
print(a[::-1])
40. ASCII manipulations
a = "Jingle bells, Jingle bells Jingle all the way
Oh what fun it is to ride"
l = []
for i in a:
l.append(ord(i))
print(l)
m = []
for t in l:
m.append(t + 2)
print(m)
v = []
for k in m:
v.append(chr(k))
print(''.join(v))
41. List comprehensions
a = "Jingle bells, Jingle bells Jingle all the way
Oh what fun it is to ride"
l = [ord(i) for i in a]
print(l)
m = [t + 2 for t in l]
print(m)
v = [chr(k) for k in m]
print(''.join(v))
45. Trying to decode…
PPhhoottoonnss hhaavvee nneeiitthheerr mmoorraallss nnoorr
vviissaass..
text = "PPhhoottoonnss hhaavvee nneeiitthheerr mmoorraallss nnoorr vviissaass.."
print(text[::2])
46. Trying to decode…
What about this?
IIIInnnnssssiiiiddddeeee eeeevvvveeeerrrryyyy ssssmmmmaaaalll
lllll pppprrrroooobbbblllleeeemmmm iiiissss aaaa bbbbiiiigggg
oooonnnneeee ttttrrrryyyyiiiinnnngggg ttttoooo ggggeeeetttt
ggggoooovvvveeeerrrrnnnnmmmmeeeennnntttt ffffuuuunnnnddd
diiiinnnngggg....
47. Trying to decode…
How can we skip the burden of writing the same code again and again?
IIIInnnnssssiiiiddddeeee eeeevvvveeeerrrryyyy ssssmmmmaaaalll
lllll pppprrrroooobbbblllleeeemmmm iiiissss aaaa bbbbiiiigggg
oooonnnneeee ttttrrrryyyyiiiinnnngggg ttttoooo ggggeeeetttt
ggggoooovvvveeeerrrrnnnnmmmmeeeennnntttt ffffuuuunnnnddd
diiiinnnngggg....
text =
"IIIInnnnssssiiiiddddeeee eeeevvvveeeerrrryyyy ssssmmmmaaaallllllll pppprrrroooobbbbl
llleeeemmmm"
print(text[::4])
48. Functions
• Functions are like tools: you can re-use the same tool
in many situations to solve similar problems
• Functions take input – something they are applied to
– and return the result back
• In addition to input the functions can also take any
number of parameters to specify what and how the
function should be applied
49. Functions as reusable components
PPhhoottoonnss hhaavvee nneeiitthheerr mmoorraallss nnoorr
vviissaass..
We parameterize functions instead of re-writing code
def dedouble(text, count):
return text[::count]
print(dedouble(“PPhhoottoonnss hhaavvee”,2))
print(dedouble(“IIIInnnnssssiiiiddddeeee”,4))
50. Further decoding
.ti esu ot tnaw lliw toidi na ylno dna esu nac
toidi na metsys a ngiseD
What about this?
51. Further decoding
.ti esu ot tnaw lliw toidi na ylno dna esu nac
toidi na metsys a ngiseD
def palindrome(text):
return text[::-1]
52. More advanced
it. invent is do can we All all. at future the predict really can't We
What about this?
53. More advanced
it. invent is do can we All all. at future the predict really can't We
Well done!!
def yoda(text):
return " ".join(text.split(" ")[::-1])
57. Further and further
s'tI suoregnad ot eb thgir nehw eht tnemnrevog si .gnorw
def mirror(text):
words = text.split(" ")
nwords = []
for w in words:
nw = w[::-1]
nwords.append(nw)
return " ".join(nwords)
58. Mastering the Ceasar shift cipher
kpfkhhgtgpeg yknn egtvckpna dg vjg fqyphcnn qh ocpmkpf, dwv yjq ectgu?
How to crack this?
59. In-place condition aka ternary operator
• If takes a complete line – sometimes it is too
much
• You can reverse it for in-place condition
a = 4
b = 3
print (a if a > b else b)
60. Mastering the Ceasar shift cipher
kpfkhhgtgpeg yknn egtvckpna dg vjg fqyphcnn qh ocpmkpf, dwv yjq ectgu?
stoplist = [ ' ', ',', '?']
def ceasar(text, shift):
return "".join([t if (t in stoplist) else chr(ord('a') + (ord(t) - ord('a') + shift + 26) % 26 ) for t in text])
62. Dictionary
• Like a usual dictionary
– Has a key – e.g. the glossary word we look for
– Contains value – e.g. the explanation for word
• It helps to associate things pairwise
• Most often used to find a value for a key, but
can be reversed if needed (costy!)
• Other names: hash, hashtable, map
66. Decoding assistant
> message .eldi si hcihw ,noitaluceps ton ,noitca
rof snoitseuq era esehT
Message [0]: “.eldi si hcihw ,noitaluceps ton
,noitca rof snoitseuq era esehT”
>apply palindrome 0
Message [0]: “sdsdf”
Applied k