9 Sections
27 Lessons
10 Weeks
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Discover the Career
EA2C14L1 What does an MLOps Engineer do & why it matters today
2
1.1
EA2C14L2 Evolution of MLOps — from ML to Production ML
1.2
EA2C14L3 Industry Overview, Myths vs. Realities, and Market Relevance
Is This Career Right for You?
EA2C14L4 Personality Fit – Who Thrives as an MLOps Engineer
2
2.1
EA2C14L5 Analytical, Engineering, and Collaborative Aptitude Balance
2.2
EA2C14L6 Common Challenges & Rewards in MLOps Work
Your School & Subject Choices
EA2C14L7 What to Choose After 10th – Foundations in Math & CS
2
3.1
EA2C14L8 What to Choose After 12th – Streams, Coaching, and Early Coding Skills
3.2
EA2C14L9 Extracurriculars: Coding, Kaggle, AI/ML Clubs & Hackathons
Entrance Exams & Admissions
EA2C14L10 Entrance Exams Overview – JEE, SAT, BSc CS/AI Admissions
2
4.1
EA2C14L11 Top Colleges & Universities (India + Global) for AI/ML & Data Engineering
4.2
EA2C14L12 Scholarships & Alternate Learning Routes (MOOCs, Bootcamps)
Academic Journey & College Life
EA2C14L13 Course Duration, Levels, and Structure (UG, PG, Certifications)
3
5.1
EA2C14L14 Year-by-Year Subject Overview – Data Structures, ML, DevOps, Cloud
5.2
EA2C14L15 Labs, Projects & Research – How Practical Learning Happens
5.3
EA2C14L16 Assessment & Exams – Code Reviews, Practical Submissions, and Competitions
Core Technical Skills for MLOps
EA2C14L17 Foundations: Linux, Git, and Python for ML Systems
6
6.1
EA2C14L18 Cloud Platforms: AWS, GCP, Azure for ML Infrastructure
6.2
EA2C14L19 Data Pipelines: ETL, Airflow, Kafka & DataOps
6.3
EA2C14L20 Model Training: TensorFlow, PyTorch, and Experiment Tracking
6.4
EA2C14L21 CI/CD for Machine Learning – Jenkins, GitHub Actions, MLflow
6.5
EA2C14L22 Containerization & Deployment – Docker, Kubernetes, and Kubeflow
6.6
EA2C14L23 Monitoring, Logging, and Scaling ML Models in Production
Real-World Experience & Skill Development
EA2C14L24 Internships & Capstone Projects – When and How to Get Them
2
7.1
EA2C14L25 Tools & Frameworks You Must Master (MLflow, DVC, TensorBoard, etc.)
7.2
EA2C14L26 Soft Skills: Communication, Collaboration & Cross-Functional Teamwork
Career Growth, Roles & Income
EA2C14L27 Entry-Level Roles – ML Engineer, DevOps Associate, Data Engineer
4
8.1
EA2C14L28 Mid-Level Growth – MLOps Specialist, ML Platform Engineer, Architect
8.2
EA2C14L29 Leadership & Entrepreneurship – Building AI Infrastructure Startups
8.3
EA2C14L30 Salary Insights – India vs. Global Market Benchmarks
8.4
EA2C14L31 Career Maps – How Engineers Grow in 5, 10, and 20 Years
Future Trends & Personal Roadmap
EA2C14L32 Emerging Tools – LLMOps, Edge AI, and Federated Learning Pipelines
4
9.1
EA2C14L33 How AI and Automation Are Transforming MLOps
9.2
EA2C14L34 Building Your Portfolio – GitHub, Projects, and Open Source Contributions
9.3
EA2C14L35 5-Year Action Plan & Final Career Checklist
9.4
EA2C14L36 Related Careers & Pivot Paths – AI Engineer, Data Engineer, Cloud Architect
MLOps Engineer
Curriculum
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