AI Model Deployment at Scale

What you'll learn

• Building and evaluating ML models
• Preparing data for training
• Tuning model performance
• Deploying models to production
• Understand transformers and large language models
• 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

A comprehensive course on ai model deployment at scale, covering core concepts, practical applications, and industry best practices.

What this course covers: AI Model Deployment at Scale works through transformers and large language models, working with Python libraries such as NumPy, pandas and scikit-learn, neural network architectures and model training and evaluation.

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

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 transformers and large language models and building and evaluating ML models to your own work or projects, and know which areas to practise next.

Language: this course is taught in Hindi.

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

  I joined to get better at preparing data for training. The practical exercises on neural network architectures were exactly what I needed. The deployment section filled a gap most ML courses skip.

• S
  Shreya C. ★★★★★ 5.0/5 Sample review

  Well organised. Revisiting the neural network architectures part a second time really helped it click. The hands-on notebooks made backpropagation finally make sense to me.

• H
  Harsh L. ★★★★★ 4.5/5 Sample review

  AI Model Deployment at Scale covered transformers and large language models in more depth than I expected. The pace was right for my level. Loved that model evaluation got as much attention as model building.

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