Computer-Vision-Kurse können Ihnen helfen zu lernen, wie visuelle Daten verarbeitet, erkannt und interpretiert werden. Sie können Fähigkeiten in Bildanalyse, Objekterkennung, Modelltraining und Evaluationsmethoden aufbauen. Viele Kurse stellen Python-Bibliotheken, Frameworks und Tools vor, die das Entwickeln und Testen visueller Modelle unterstützen.

Coursera
Kompetenzen, die Sie erwerben: PyTorch (Machine Learning Library), Convolutional Neural Networks, Model Training, Image Analysis, Machine Learning Methods, Classification Algorithms, Model Evaluation, Deep Learning, Computer Vision
★ 3.8 (13) · Mittel · angeleitetes Projekt · Weniger als 2 Stunden

Kompetenzen, die Sie erwerben: Embeddings, Natural Language Processing, Keras (Neural Network Library), Generative AI, Convolutional Neural Networks, Transfer Learning, Recurrent Neural Networks (RNNs), Model Evaluation, Generative Model Architectures, Image Analysis, Model Training, Artificial Neural Networks, Computer Vision, Model Optimization, Data Preprocessing, Tensorflow, Deep Learning, Applied Machine Learning, AI Workflows, Model Deployment
★ 5 (15) · Anfänger · Spezialisierung · 1–3 Monate

Kompetenzen, die Sie erwerben: Model Optimization, Image Analysis, Transfer Learning, Fine-tuning, Multimodal Prompts, Model Evaluation, Technical Documentation, Data Preprocessing, Debugging, Computer Vision, PyTorch (Machine Learning Library), Feature Engineering, Tensorflow, Algorithms, Model Training, Embeddings, Systems Design, Ethical Standards And Conduct, Root Cause Analysis, Deep Learning
Mittel · Spezialisierung · 3–6 Monate

Kompetenzen, die Sie erwerben: Model Training, Artificial Intelligence and Machine Learning (AI/ML), Computer Vision, Artificial Intelligence, Image Analysis, Machine Learning Methods, AWS SageMaker, Responsible AI, Model Optimization, Natural Language Processing, Generative AI, Machine Learning, AI powered creativity, Prompt Engineering, Amazon Web Services, Large Language Modeling, Model Deployment, AI Workflows, Cloud Deployment, Data Science
★ 4.7 (17) · Anfänger · Spezialisierung · 1–3 Monate

Kompetenzen, die Sie erwerben: Model Training, Fine-tuning, Model Evaluation, Model Optimization, Machine Learning Methods, Predictive Modeling, Tensorflow, Statistical Machine Learning, MLOps (Machine Learning Operations), Computer Vision, Applied Machine Learning, Performance Testing, Transfer Learning, Benchmarking, Feature Engineering, Scikit Learn (Machine Learning Library), Verification And Validation, Network Architecture, Deep Learning, PyTorch (Machine Learning Library)
Mittel · Spezialisierung · 1–3 Monate

Kompetenzen, die Sie erwerben: Verantwortungsvolle AI, Künstliche Intelligenz, Computer Vision, Maschinelles Lernen, Unüberwachtes Lernen, AWS SageMaker, Modell Ausbildung, Schnelles Engineering, AI-Arbeitsabläufe, Reinforcement Learning, Bewertung des Modells, Modell-Einsatz, Methoden des maschinellen Lernens, Künstliche Intelligenz und maschinelles Lernen (AI/ML), Modell-Optimierung, Amazon Web Services, Überwachtes Lernen
★ 4.8 (15) · Anfänger · Kurs · 1–4 Wochen

DeepLearning.AI
Kompetenzen, die Sie erwerben: Prompt Engineering Tools, Computer Vision, Schnelles Engineering, Feinabstimmung, Generative KI, AI-Personalisierung
★ 4.9 (7) · Anfänger · Projekt · Weniger als 2 Stunden

DeepLearning.AI
Kompetenzen, die Sie erwerben: Deep Learning, Artificial Neural Networks, Convolutional Neural Networks, Supervised Learning, Applied Machine Learning, Model Optimization, Artificial Intelligence, Computer Vision, Recurrent Neural Networks (RNNs), Model Training, Network Architecture, NumPy
★ 5 (6) · Mittel · Kurs · 1–4 Wochen

Kompetenzen, die Sie erwerben: Tensorflow, Computer Vision, Model Evaluation, Convolutional Neural Networks, Deep Learning, Amazon Elastic Compute Cloud, Cloud Deployment, Model Training, Transfer Learning, Model Deployment, Amazon Web Services, Artificial Neural Networks, Keras (Neural Network Library), Fine-tuning, Application Deployment, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Algorithms, Model Optimization, Software Installation
★ 5 (25) · Anfänger · Spezialisierung · 1–3 Monate

Pearson
Kompetenzen, die Sie erwerben: Large Language Modeling, Deep Learning, Image Analysis, Model Deployment, Recurrent Neural Networks (RNNs), PyTorch (Machine Learning Library), Convolutional Neural Networks, Model Optimization, Tensorflow, LLM Application, Computer Vision, Responsible AI, Natural Language Processing, Embeddings, Artificial Neural Networks, Model Training, Time Series Analysis and Forecasting, Network Architecture
Mittel · Spezialisierung · 1–4 Wochen

Kompetenzen, die Sie erwerben: Model Optimization, MLOps (Machine Learning Operations), Systems Architecture, Model Evaluation, Feature Engineering, AI Integrations, Model Training, Model Deployment, Extract, Transform, Load, Systems Design, Data Pipelines, Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Apache Spark, Natural Language Processing, Pandas (Python Package), Cloud Deployment, Machine Learning, Computer Vision, Computational Thinking
Mittel · Berufsbezogenes Zertifikat · 3–6 Monate

KodeKloud
Kompetenzen, die Sie erwerben: LLM-Bewerbung, Verantwortungsvolle AI, Künstliche Intelligenz, Computer Vision, Schnelles Engineering, OpenAI-API, Feinabstimmung, OpenAI, Generative KI, Einbettungen
Anfänger · Kurs · 1–3 Monate