Strong knowledge of linear algebra, calculus, and statistics is key to understanding and optimizing ML algorithms.
Python, R, TensorFlow, and PyTorch are must-haves for building and deploying efficient ML models.
Clean, transform, and manage large datasets. Better data = better predictions and AI outcomes.
Neural networks and transformers power today's AI. Learn deep learning tools for next-gen solutions.
Use AWS, GCP, Docker & Kubernetes to scale and deploy ML models in real business environments.
Understand AI ethics and bias mitigation. Responsible AI is the future.
Keep learning and adapting to stay ahead in the ML and AI revolution.