Data Augmentation Courses and Certifications

Aladdin Persson

Albumentations Tutorial for Data Augmentation - PyTorch Focused

Learn to use Albumentations for image augmentation in classification, segmentation, and detection workflows with PyTorch.

• YouTube
• 31 minutes
• Self-Paced
• Free Video

Valerio Velardo - The Sound of AI

How to Implement Audio Data Augmentation in Python

Implement audio data augmentation in Python with noise addition, time stretching, pitch scaling, polarity inversion, and random gain.

• YouTube
• 21 minutes
• Self-Paced
• Free Video

Coursera

Preparing Images for AI Models

Source, clean, and augment image datasets for diffusion model training: evaluate LAION and ImageNet, apply resizing, normalization, and metadata checks, then MixUp, CutMix, and style transfer.

• Coursera
• 4 weeks, 2 hours a week
• Self-Paced
• Paid Course

James Briggs

Making the Most of Data - Augmented SBERT

Learn how in-domain data augmentation with augmented SBERT can generate or label training data for NLP in niche, low-resource domains.

• YouTube
• 55 minutes
• Self-Paced
• Free Video

Data Council

Continuous Data Pipeline for Real-Time Benchmarking and Data Set Augmentation

Generate datasets and real-time precision/recall splits to detect data shifts, prioritize data collection, and retrain models for improved ML system accuracy and performance.

• YouTube
• 15 minutes
• Self-Paced
• Free Video

Optimized Data Preparation for Large-Scale LLMs

Learn to prepare scalable, high-quality datasets for large language model training through efficient storage, deduplication, toxicity filtering, and text augmentation.

• CodeSignal
• 1 hour
• Self-Paced
• Free Certificate

Data Preparation for Drawing Recognition

Prepare drawing-recognition datasets through inspection, labeling, normalization, visualization, and image augmentation.

• CodeSignal
• 2 hours
• Self-Paced
• Free Certificate

Stanford Seminar - Intelligence Augmentation Through the Lens of Interactive Data Visualization

Explore interactive data visualization's role in human-machine partnerships, bridging mental models with machine learning, and addressing epistemological challenges in the era of generative AI.

• YouTube
• 1 hour
• Self-Paced
• Free Video

Generative AI for Data Engineering and Data Professionals

3816 ratings at Udemy

Work Faster with Practical Gen AI for Data Engineering | For all Data Professionals (Engineers, Analysts, Scientists)

• Udemy
• 5 hours 40 minutes
• Self-Paced
• Paid Course

Generative AI: Elevate Your Data Science Career

284 ratings at Coursera

Apply generative AI across the data science lifecycle: generate and augment data, engineer features, speed visualizations, build predictive models, and weigh ethics considerations.

• Coursera
• 3 weeks, 5 hours a week
• Self-Paced
• Paid Course

Coursera

Deep Learning with PyTorch : Object Localization

49 ratings at Coursera

Build an object localization model in PyTorch: write a custom image–bounding box dataset, augment with albumentations, fine-tune a pretrained timm CNN, and predict boxes.

• Coursera
• 1 hour 56 minutes
• Self-Paced
• Paid Course

Coursera

Aerial Image Segmentation with PyTorch

32 ratings at Coursera

Segment roads in aerial imagery with PyTorch: write a custom image-mask dataset, augment with albumentations, fine-tune a pretrained Unet, and run inference.

• Coursera
• 2 hours 4 minutes
• Self-Paced
• Paid Course

MathWorks

Advanced Deep Learning Techniques for Computer Vision

16 ratings at Coursera

Train anomaly detection models to spot defects in images, generate synthetic images with data augmentation, auto-label data with AI-assisted annotation, and import PyTorch models.

• Coursera
• 4 weeks, 2 hours a week
• Self-Paced
• Paid Course

Coursera

Classify Radio Signals with PyTorch

13 ratings at Coursera

Fine-tune a pretrained CNN in PyTorch to classify radio signal spectrogram images into Squiggle, Noise and Narrowband classes, applying spectrogram augmentation and writing train/eval loops.

• Coursera
• 1 hour 45 minutes
• Self-Paced
• Paid Course

Coursera

Optimizing and Deploying Computer Vision Models

Optimize and ship vision models: analyze and augment datasets, diagnose vanishing gradients with TensorBoard, containerize a /predict inference API, and run ablation studies for reproducible results.

• Coursera
• 8 weeks, 1 hour a week
• Self-Paced
• Paid Course