AI Engineer Roadmap
A detailed roadmap for AI engineering
Essential mathematics like linear algebra, calculus, statistics, probability required to understand AI algorithms.
Python is the primary language for AI development, with libraries like NumPy, Pandas, Matplotlib.
Introduction to ML concepts like supervised/unsupervised learning, evaluation, etc.
Git is a version control system for tracking changes in source code. GitHub is a platform for hosting repositories and collaborating on projects.
Introduction to deep neural networks, TensorFlow/PyTorch, etc.
A field of AI dealing with processing and understanding natural language.
A field dealing with enabling computers to "see" and understand images/videos.
Essential steps to prepare data before feeding it to models.
Models for generating content like text, images, audio, etc.
Integrating ML with operations using tools like MLflow, Kubeflow, etc.
Ethical principles in developing and deploying AI applications.
A type of ML where an agent learns by interacting with an environment.