📐 ML Fundamentals

Neural networks, backpropagation, gradient descent — the maths behind AI

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ML Fundamentals

ML Model Deployment: Build a Production API with FastAPI

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ML Fundamentals

Visual Perception and the Brain

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ML Fundamentals

Supervised Machine Learning

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ML Fundamentals

Reproducible Training Data and ML-Ready Data Pipelines

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ML Fundamentals

Active Machine Learning with Python

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ML Fundamentals

Golang: Foundations and Variables

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ML Fundamentals

Generative AI for NLP with PyTorch Capstone Project

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ML Fundamentals

Practical Machine Learning on Databricks

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ML Fundamentals

Deep Learning Model Engineering and Optimization

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ML Fundamentals

Mastering Tabular ML: Feature Engineering to Production

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ML Fundamentals

Transfer Learning Foundations for AI Models

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ML Fundamentals

Projects, Dialogs, and Electron Features

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ML Fundamentals

Model Deployment and Monitoring

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ML Fundamentals

Data Engineering and Spark Foundations for AI and ML

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ML Fundamentals

Golang: Logic Flow and Data Collections

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ML Fundamentals

Viscoelasticidad en materiales poliméricos. Modelización

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ML Fundamentals

Deploying Fine-Tuned AI Models

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ML Fundamentals

Introduction to Vehicle Dynamics

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ML Fundamentals

Agentic AI Architectures with Patterns, Frameworks and MCP

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ML Fundamentals

Advanced Java APIs and Functional Programming

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ML Fundamentals

Generative AI for Developers - How To Use AI In Your Workday

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Forecasting & Scenario Development with AI

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ML Fundamentals

Unstructured Data Engineering for AI

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ML Fundamentals

Build & Deploy AI with Hugging Face - Hands-On

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MLOps Foundations

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ML Fundamentals

Generative AI Fundamentals for Beginners

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ML Fundamentals

Core Machine Learning Algorithms and Model Validation

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Custom Deep Learning Model Architecture

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ML Fundamentals

Deep Reinforcement Learning: From Theory to Practice

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Mastering Classic Reinforcement Learning Algorithms

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ML Fundamentals

Java Foundations Bootcamp - Learn by Coding & Quizzes - 2026

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ML Fundamentals

Machine Learning: Real-World Applications

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ML Fundamentals

Dikkat Mekanizması

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ML Fundamentals

BiteSize Stats: Probability Rules and Bayes Theorem 

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Java Concurrency, Performance, and Networking

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Modern Java Fundamentals & Data Structures

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Time Series Forecasting with Python: Models to Production

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Capstone: Build and Operate an AI-Native Data Platform

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Building and Scaling ML Pipelines

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Mastering Python for Data Science

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Convolutional Neural Networks

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Python: Implement & Evaluate Random Forests for ML

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Auto Machine Learning (AutoML) Using AutoGluon

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ML Fundamentals

Applied Unsupervised Learning in Python

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Advanced AI and Machine Learning Techniques and Capstone

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ML Fundamentals

Machine Learning

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ML Fundamentals

Hyperparameter Tuning with Keras Tuner

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ML Fundamentals

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

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