How to Become a Machine Learning Engineer (Step-by-Step)

Becoming a machine learning engineer requires a structured learning path starting with foundational maths and statistics, including linear algebra, calculus, and probability. The next step involves mastering Python, the primary language for ML, along with essential libraries like NumPy, Pandas, and Scikit-learn. Proficiency in SQL is also critical, as a significant portion of the job involves data manipulation and dataset creation. The curriculum then covers core machine learning algorithms, evaluation metrics, and concepts like the bias-variance tradeoff before advancing to deep learning topics such as neural networks and CNNs.