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This lesson focuses on creating real-time visuals, animation, and audiovisual composition using Ableton Live together with the visual engine Videosync. It is suitable for beginners and early-intermediate users who want to explore visuals in a musical and performance-oriented context. We look at how visuals can be created, structured, and performed in relation to sound. Starting from basic setups and visual ideas, we move toward building animated and real-time visual systems that can be used for performances, installations, or audiovisual works. The emphasis is on understanding visuals as time-based systems, rather than relying on templates or ready-made effects. Depending on your interests, lessons can include: ■ working with real-time visuals and video clips ■ creating and controlling animated visuals ■ structuring visuals in relation to rhythm, timing, and musical form ■ preparing visual sessions and VJ sets for concerts ■ building audiovisual compositions and performance setups ■ creating music videos and visual content for promoting music online ■ developing visuals for art and installation projects For more experienced users, we can also explore experimental and creative approaches, including system-based animation, generative structures, unconventional audiovisual workflows and developing custom shaders. Lessons are adapted to your level and goals. No prior experience with visual tools in Ableton Live is required, and the focus is on clear concepts that can be applied across different visual approaches. Private lessons are available in my studio in Nijmegen, at your place, or online if preferred.
Digital arts · Computer graphics · Ableton live
Trusted teacher: This course is designed to take you from a complete beginner with no prior programming experience to a confident Python programmer. You'll learn not just the syntax of Python, but how to think like a programmer, solve problems, and build practical applications. Who is this course for? Absolute beginners to programming. Professionals from other fields looking to automate tasks. Students needing to learn programming for academics. Anyone interested in data science, web development, or automation. What You'll Learn (Course Objectives): By the end of this course, you will be able to: Understand and write Python code using fundamental concepts like variables, data types, and loops. Structure your code using functions, modules, and classes (Object-Oriented Programming). Read from and write to files on your computer. Handle errors and exceptions gracefully. Use essential Python libraries for tasks like web scraping, data analysis, or building simple games. Debug your code and solve complex problems by breaking them down into smaller steps. Build a portfolio of projects to showcase your skills. Course Outline: Module 1: The Python Basics Setting up your development environment (Installing Python & PyCharm/VSCode). Your first Python script: "Hello, World!". Variables, Data Types (Strings, Numbers, Booleans). Basic Operators and Input/Output. Module 2: Controlling the Flow Conditional statements (if, elif, else). Loops: for loops and while loops. Data Collections: Lists, Tuples, Sets, and Dictionaries. Module 3: Writing Clean and Reusable Code Functions: Defining and calling your own functions. Scope and namespaces. Introduction to Modules and the Python Standard Library (e.g., math, random). Module 4: Intermediate Concepts Working with Files (Reading, Writing, and Appending). Error and Exception Handling (try, except). List Comprehensions for concise code. Module 5: Introduction to Object-Oriented Programming (OOP) Classes and Objects. The __init__ method and self. Inheritance and Polymorphism. Module 6: Capstone Project Apply all your skills to build a significant project. Example Projects: A simple web scraper, a to-do list application, a basic text-based adventure game, or a data analysis script. Prerequisites: No prior programming experience is required! A computer (Windows, Mac, or Linux) with an internet connection. A willingness to learn and problem-solve.
Python
Trusted teacher: ⚙️ Step 1: Understand What AI Actually Is AI isn’t magic — it’s just pattern recognition on steroids. It learns from data, spots trends faster than humans, and automates decisions. There are three main flavors you’ll be dealing with: Machine Learning (ML) – Think “training” an AI to make predictions. (Used in trading bots, recommendations, etc.) Generative AI – Like ChatGPT or Midjourney; it creates text, code, or images. Automation AI – Uses rules + ML to perform actions automatically (Zapier, n8n, AutoGPT, etc.). 💸 Step 2: Using AI in Trading AI trading isn’t new — hedge funds have been doing it for decades. But now you can do it too. Here’s the stack you’d look at: Data Source – Pull data from APIs (like Binance, Alpha Vantage, or Polygon.io). Model – Use AI to find signals. Common tools: Python + TensorFlow/PyTorch → train models that predict price movement. GPTs → analyze news sentiment. Execution – Automate trades using APIs (like Binance or Alpaca). Testing – Backtest with historical data before going live. If you want plug-and-play options, try: Koyfin, TrendSpider, or Trade-Ideas for AI-driven analysis. Composer or Stoic.ai if you want “autopilot” portfolios. (Pro tip: the real edge isn’t in fancy models — it’s in feeding your AI clean, unique data.) 📱 Step 3: Using AI to Build Apps This is where things get fun. You don’t even need to code hardcore anymore. No-code builders: Glide, Bubble, or Adalo → use AI APIs like OpenAI, HuggingFace, or Replicate to add brains. AI dev tools: Replit Ghostwriter, GitHub Copilot, or ChatGPT’s code interpreter to write real code fast. Frameworks (if coding): Python/Flask or FastAPI for backend. React or Next.js for frontend. Firebase or Supabase for hosting & data. Hook it all together with AI APIs (like OpenAI, Anthropic, or Stability AI). 🚀 Step 4: Learn by Doing (Don’t Just Watch YouTube) The fastest way to master AI is to build real stuff: Create a sentiment analyzer that trades crypto based on tweets. Build an AI app that generates marketing copy for clients. Automate your own work — make an AI that handles your emails or schedules. 📚 Step 5: Resources That’ll Level You Up Learn ML basics: fast.ai or Google’s ML Crash Course. Build AI apps: freeCodeCamp or YouTube’s “Code with Tomi” / “Nicholas Renotte.” Trading AI: Check out “Algorithmic Trading with Python” by QuantInsti. No-code AI apps: Buildspace or FlowiseAI.
Digital arts · Computer programming
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Econometrics & Statistics - For University & School Students. SAT, IB, A-Levels, University Courses (Amsterdam)
Nick
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Nick's approach is patient and thorough, informative and imaginative as well. He always comes up with his own examples in order to test my knowledge on a given exercise and helps me get to the answer at my own pace, rather than handing it to me. He doesn't use a one-size-fits-all method, but rather tailors his lesson in order to get out my full potential, even in a field I find difficult. He makes himself available for additional questions and is overall great to work with!
Review by DENI
Microsoft Excel, Finance, Investments, Economics 🔥 🔥 🔥 (Prague)
Boris
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Thanks to Boris, I was able to pass my exam in Asset Management. Excellent in explaining and very helpful so I highly recommend. Thank you again, Boris!
Review by STEPHEN
Learn Arabic language (read, write and speak fluently) (Esch-sur-Alzette)
Abir
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I’ve enjoyed my first lesson with Abir, she’s a very pleasant person.
Review by ELINA
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