Chatbot Development with LLMs

What you'll learn

• Building and evaluating ML models
• Preparing data for training
• Tuning model performance
• Deploying models to production
• Understand feature engineering and data preparation
• Understand supervised and unsupervised learning

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

Description

This course dives deep into chatbot development with llms, equipping you with the skills and confidence to apply your knowledge in real scenarios.

What this course covers: Chatbot Development with LLMs works through feature engineering and data preparation, supervised and unsupervised learning, transformers and large language models and model training and evaluation.

Skills you will build: building and evaluating ML models, preparing data for training and deploying models to production.

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 suits learners who already know the basics of machine learning and AI and want to go deeper.

Learning outcomes: by the end of the course you should be able to apply feature engineering and data preparation and building and evaluating ML models to your own work or projects, and know which areas to practise next.

Requirements

• Basic knowledge of machine learning and AI
• A computer with internet access
• Willingness to complete practice tasks

Your instructor

• S
  Swathi G. ★★★★★ 4.5/5 Sample review

  I joined to get better at deploying models to production. The practical exercises on transformers and large language models were exactly what I needed. The hands-on notebooks made backpropagation finally make sense to me.

• N
  Naveen K. ★★★★★ 4.5/5 Sample review

  Chatbot Development with LLMs covered supervised and unsupervised learning in more depth than I expected. The pace was right for my level. The deployment section filled a gap most ML courses skip.

• G
  Gautam V. ★★★★★ 5.0/5 Sample review

  Good balance of theory and practice. The feature engineering and data preparation lessons helped me apply building and evaluating ML models in real situations. 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.