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    AI Bootcamp

    Dive deep into AI and Machine Learning in this expert-level one-day bootcamp. Build real models, analyze data together, and get personalized guidance. Covers the full ML pipeline from data preprocessing through model training to evaluation — with hands-on exercises on real datasets.

    4 Modules
    16 Lessons
    1 Tag
    AI Bootcamp – 1 Tag Machine Learning course at apigenio

    Skills You'll Learn

    ML pipeline & workflow
    Data preprocessing & feature engineering
    Supervised learning algorithms
    Model evaluation & metrics
    scikit-learn & Python ML stack

    Course Modules & Lessons

    1

    ML Foundations

    Types of learning, the ML pipeline, and setting up your Python ML environment

    2h
    Was ist Machine Learning?

    Supervised, Unsupervised und Reinforcement Learning unterscheiden

    25min
    Die ML-Pipeline im Überblick

    Von Rohdaten zur Vorhersage: der komplette Workflow

    25min
    Python ML-Umgebung einrichten

    Jupyter, NumPy, Pandas und scikit-learn installieren

    25min
    Erstes ML-Experiment

    Hands-on: Ein einfaches Klassifikationsmodell trainieren

    25min
    2

    Data Preprocessing

    Data cleaning, feature engineering, encoding, scaling, and train/test splitting

    2h
    Daten laden & explorieren

    CSV/JSON einlesen, describe(), info() und erste Visualisierungen

    25min
    Missing Values & Outlier

    Fehlende Werte behandeln und Ausreisser erkennen

    20min
    Feature Engineering

    Neue Features erstellen, Encoding und Skalierung

    25min
    Train/Test Split & Pipelines

    Daten aufteilen und sklearn Pipelines aufbauen

    25min
    3

    Model Building & Training

    Supervised learning algorithms, hyperparameter tuning, and model selection

    2h
    Lineare & logistische Regression

    Grundlegende Modelle verstehen und anwenden

    25min
    Decision Trees & Random Forest

    Baumbasierte Modelle und Ensemble-Methoden

    25min
    Hyperparameter Tuning

    GridSearchCV und RandomizedSearchCV in der Praxis

    25min
    Modellvergleich & -auswahl

    Verschiedene Modelle systematisch vergleichen

    20min
    4

    Evaluation & Deployment

    Metrics, cross-validation, model interpretation, and saving models for production

    2h
    Metriken verstehen

    Accuracy, Precision, Recall, F1-Score und wann was zählt

    25min
    Kreuzvalidierung

    K-Fold Cross-Validation für robuste Bewertung

    20min
    Modellinterpretation

    Feature Importance und SHAP-Werte verstehen

    20min
    Modelle speichern & deployen

    joblib, pickle und einfache API mit FastAPI

    25min

    Prerequisites

    • Python proficiency
    • Statistics knowledge
    • Linear algebra basics

    Ready to start?

    Join thousands of students already learning.

    Your Trainer

    David Pinezich

    David Pinezich

    Experienced IT architect and trainer specializing in Python, Cloud Architecture, and Enterprise Solutions. Certified TOGAF, CISSP, and AWS professional with years of hands-on training experience.

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