Notes

Key areas of knowledge for an AI engineer include:

• Machine Learning Fundamentals:

  • Supervised learning (regression, classification)

  • Unsupervised learning (clustering)

  • Reinforcement learning

  • Neural networks

  • Decision trees

• Programming Languages:

  • Python (most widely used)

  • R

  • Java

• Deep Learning Frameworks:

  • TensorFlow

  • PyTorch

  • Keras

• Mathematics:

  • Linear algebra

  • Calculus

  • Probability and statistics

• Data Handling:

  • Data cleaning and preprocessing

  • Feature engineering

  • Data visualization

• Cloud Computing:

  • AWS

  • Azure

  • Google Cloud Platform

• Specific AI Fields:

  • Natural Language Processing (NLP)

  • Computer Vision

  • Robotics

Other important skills for an AI engineer include:

• Problem-solving abilities

• Critical thinking

• Communication skills

• Collaboration with other teams (data scientists, software developers)

• Ethical considerations in AI development

• Staying updated with the latest advancements in AI