Machine Learning (ML) – Think “training” an AI to make predictions. (Used in trading bots, recommendations, etc.)Generative AI

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Machine Learning (ML) – Think “training” an AI to make predictions. (Used in trading bots, recommendations, etc.)Generative AI – Like ChatG

From 22 £ /h

⚙️ 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.

Extra information

laptap

Location

Online from Belgium

Age

Teenagers (13-17 years old)

Adults (18-64 years old)

Seniors (65+ years old)

Student level

Beginner

Intermediate

Advanced

Duration

45 minutes

60 minutes

90 minutes

The class is taught in

Dutch

English

Persian

Skills

Digital arts

Computer programming

Availability of a typical week

(GMT -04:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

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Variables

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Practical projects for implementation

💡 How does the course work?

Clear explanations to understand the programming logic

Targeted exercises adapted to your level

Concrete projects to create your own applications

🎯 My goal:

Helping you understand the logic behind the code

Progress at your own pace

Create your own projects in Python and gain independence

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Understanding what Object-Oriented Programming really is (and when to use it)
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Mastering this, the prototype, and the instantiation logic
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Understanding the concept, objectives and benefits of OOP.
2. Procedural Programming vs. OOP
Why unstructured code quickly becomes unmanageable.
3. Objects in JavaScript
Properties, methods and representation of the real world.
4. The keyword this
Understanding the execution context (often poorly understood).
5. Limitations of simple objects
Why duplicating code is a bad idea.
6. Constructive functions
Create multiple objects from the same model.
7. The keyword new
What it's actually doing under the hood.
8. The prototype
Sharing methods and memory optimization.
9. ES6 Classes
Modern syntax and best practices.
10. The builder
Proper initialization of objects.
11. Data Encapsulation
Protect the internal state of objects.
12. Inheritance between classes
Reusing code intelligently.
13. The keyword super
Communication between parent and child in the classroom.
14. Polymorphism
The same behavior, several forms.
15. Composition vs. Inheritance
Choosing the right architecture.
16. Best practices in OOP
Write readable, scalable, and maintainable code.
17. Common mistakes made by beginners
Pitfalls to absolutely avoid.
18. Guided practical exercise
Creation of a concrete class (product, user, etc.).
19. Assessment Quiz (Multiple Choice Questions)
To validate the actual understanding of the concepts.

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Concrete examples from real projects
Simple but effective exercises
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2- When to use it
3- and when not to use it

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