MLOps Engineer
Description
Curriculum
- 9 Sections
- 27 Lessons
- 10 Weeks
Expand all sectionsCollapse all sections
- Discover the CareerEA2C14L1 What does an MLOps Engineer do & why it matters today2
- Is This Career Right for You?EA2C14L4 Personality Fit – Who Thrives as an MLOps Engineer2
- Your School & Subject ChoicesEA2C14L7 What to Choose After 10th – Foundations in Math & CS2
- Entrance Exams & AdmissionsEA2C14L10 Entrance Exams Overview – JEE, SAT, BSc CS/AI Admissions2
- Academic Journey & College LifeEA2C14L13 Course Duration, Levels, and Structure (UG, PG, Certifications)3
- Core Technical Skills for MLOpsEA2C14L17 Foundations: Linux, Git, and Python for ML Systems6
- 6.1EA2C14L18 Cloud Platforms: AWS, GCP, Azure for ML Infrastructure
- 6.2EA2C14L19 Data Pipelines: ETL, Airflow, Kafka & DataOps
- 6.3EA2C14L20 Model Training: TensorFlow, PyTorch, and Experiment Tracking
- 6.4EA2C14L21 CI/CD for Machine Learning – Jenkins, GitHub Actions, MLflow
- 6.5EA2C14L22 Containerization & Deployment – Docker, Kubernetes, and Kubeflow
- 6.6EA2C14L23 Monitoring, Logging, and Scaling ML Models in Production
- Real-World Experience & Skill DevelopmentEA2C14L24 Internships & Capstone Projects – When and How to Get Them2
- Career Growth, Roles & IncomeEA2C14L27 Entry-Level Roles – ML Engineer, DevOps Associate, Data Engineer4
- Future Trends & Personal RoadmapEA2C14L32 Emerging Tools – LLMOps, Edge AI, and Federated Learning Pipelines4
Instructor
2238 Students567 Courses
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Online and at your own pace.
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