Current
Intermediate
40% Off
ML Model Development and Tracking
Coursera · KodeKloud · Updated March 2026
Platform rating
4.4/5
AI Tutor Rating
8.2/10
Duration
1-4 weeks
Classes
36
Hands-on guide to ML model development and experiment tracking for MLOps including model evaluation and performance tuning.
What you'll get
Track experiments and manage model versions
Evaluate and tune model performance
Build reproducible ML experiments
Fit
Best for
Software Engineers
DevOps/MLOps Engineers
Data Engineers
Platform Engineers
Not ideal for
Learners seeking only entry-level overviews
Prerequisites & pricing
Prerequisites
Basic ML
Pricing
Subscription
Certification
Certificate
Growth Leverage: Completing this course positions individuals for roles such as MLOps Engineer, Data Scientist, or Machine Learning Engineer, opening doors to advanced positions in companies focused on deploying ML solutions. Certifications related to MLOps and ML project management become more attainable, enhancing career progression.
Skills Value: The skills gained enable professionals to effectively manage model experiments and ensure reproducibility, addressing critical challenges in ML deployment. Given the high demand for MLOps expertise, such roles can command salaries upwards of $120,000, reflecting the market's need for strong ML operational skills.
MLOps
Experiment Tracking
Model Evaluation
Performance Tuning