Machine Learning Engineer
Data & Artificial Intelligence
Builds machine learning pipelines and production-ready models.
Roadmap
Step 1
Learn Python and ML Libraries
Master scikit-learn, pandas, and NumPy.
Step 2
Understand ML Algorithms
Study supervised and unsupervised learning techniques.
Step 3
Practice Data Engineering
Handle large datasets and data pipelines.
Step 4
Implement ML Ops
Learn deployment and monitoring of ML models.
Step 5
Build Production Pipelines
Create scalable ML workflows.
Recommended Certificates
Machine Learning Specialization
Offered by Coursera/Stanford
Taught by Andrew Ng on ML principles.
Skills: ML Algorithms, Supervised Learning
Certified Machine Learning Engineer
Offered by DataCamp
Certification in ML development.
Skills: Python, Scikit-learn
ML Ops Certification
Offered by Udacity
Productionizing ML pipelines.
Skills: CI/CD, ML Ops