Diffusion Models & Image Generation

What you'll learn

• Building and evaluating ML models
• Preparing data for training
• Tuning model performance
• Deploying models to production
• Understand deep learning frameworks (TensorFlow / PyTorch)
• Understand working with Python libraries such as NumPy, pandas and scikit-learn

Planned outline shown above (sample metadata). The detailed module and lesson list for this course hasn't been published yet.

Description

Master diffusion models including Stable Diffusion, DALL-E, and Midjourney APIs. Learn to fine-tune and deploy image generation models for creative and enterprise use.

What this course covers: Diffusion Models & Image Generation works through deep learning frameworks (TensorFlow / PyTorch), working with Python libraries such as NumPy, pandas and scikit-learn, supervised and unsupervised learning and neural network architectures.

Skills you will build: preparing data for training, building and evaluating ML models and tuning model performance.

Practical applications: prediction and classification systems, computer vision and NLP applications and AI features inside products.

Who should take this course: developers, data analysts and engineering students moving into machine learning and AI. It is designed for learners with solid experience in machine learning and AI who want advanced, in-depth practice.

Learning outcomes: by the end of the course you should be able to apply deep learning frameworks (TensorFlow / PyTorch) and preparing data for training to your own work or projects, and know which areas to practise next.

Requirements

• Solid working knowledge of machine learning and AI
• Comfort with intermediate concepts
• A computer with internet access

Your instructor

• L
  Lavanya P. ★★★★★ 5.0/5 Sample review

  Good balance of theory and practice. The supervised and unsupervised learning lessons helped me apply tuning model performance in real situations. Loved that model evaluation got as much attention as model building.

• A
  Aishwarya N. ★★★★★ 4.5/5 Sample review

  Diffusion Models & Image Generation covered working with Python libraries such as NumPy, pandas and scikit-learn in more depth than I expected. The pace was right for my level. The hands-on notebooks made backpropagation finally make sense to me.

• A
  Aditya G. ★★★★★ 5.0/5 Sample review

  Clear structure from deep learning frameworks (TensorFlow / PyTorch) through to working with Python libraries such as NumPy, pandas and scikit-learn. I'd like a few more practice tasks, but overall very useful. The deployment section filled a gap most ML courses skip.

Sample reviews are illustrative demo content, not verified purchases. Ratings from learners will appear here once submitted.