Machine learning and data science
MLOps Engineer
Also called: ML Platform Engineer, Machine Learning Operations Engineer, AI Infrastructure Engineer
Automates training, deployment, monitoring and retraining of machine-learning models so they keep working in production.
- Skill Packs
- 15
- Class hours
- 406
- At 6 hours a week
- about 17 months
- Free certifications
- 19
- Library resources
- 90
- Interview questions
- 168
✓ All 168 lessons expert reviewed
Your route. Follow the path in order and finish the capstone before you apply. Your goal is a portfolio project and interview practice you can show in the next few months.
Industry 5.0 · this path teaches 1 of 3 pillars
🤝 Human-centred + 🌱 Sustainable: add I50-SUS+ 🛡️ Resilient: add I50-RES
1. Foundation
5 packs · 142 hours
The base every pack after it builds on.
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1
Python programming FND-01 Beginner
37 hours 15 lessons 🎓 4 free certifications 📚 8 library resources ✓ Expert reviewed ❓ 18 interview questions
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2
Developer toolkit: command line, Git and AI coding assistants FND-02 Beginner
16 hours 8 lessons 🎓 1 free certification 📚 8 library resources ✓ Expert reviewed ❓ 11 interview questions
-
3
SQL and databases FND-03 Beginner
32 hours 13 lessons 🎓 3 free certifications 📚 8 library resources ✓ Expert reviewed ❓ 16 interview questions
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4
Linux and networking LNX-01 Beginner
30 hours 11 lessons 🎓 1 free certification 📚 4 library resources ✓ Expert reviewed ❓ 6 interview questions
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5
Data wrangling with NumPy and pandas DAT-02 Beginner
27 hours 11 lessons 🎓 1 free certification 📚 8 library resources ✓ Expert reviewed ❓ 11 interview questions
2. Core skills
3 packs · 80 hours
The skills the job is made of.
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6
Containers, CI/CD and cloud foundations OPS-01 Beginner
24 hours 11 lessons 🎓 1 free certification 📚 8 library resources ✓ Expert reviewed ❓ 10 interview questions
-
7
Machine learning ML-01 Beginner
32 hours 14 lessons 🎓 2 free certifications 📚 8 library resources ✓ Expert reviewed ❓ 15 interview questions
-
8
MLOps: deploying and running machine learning models OPS-02 Advanced
24 hours 11 lessons 🎓 1 free certification 📚 6 library resources ✓ Expert reviewed ❓ 9 interview questions
3. Specialise
5 packs · 134 hours
The depth that sets you apart in interviews.
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9
Feature engineering, tuning and responsible machine learning ML-02 Advanced
24 hours 10 lessons 🎓 2 free certifications 📚 8 library resources ✓ Expert reviewed ❓ 11 interview questions
-
10
Kubernetes in depth K8S-01 Advanced
32 hours 11 lessons 📚 6 library resources ✓ Expert reviewed ❓ 6 interview questions
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11
Infrastructure as code with Terraform and Ansible IAC-01 Advanced
29 hours 10 lessons 📚 6 library resources ✓ Expert reviewed ❓ 6 interview questions
-
12
Observability and site reliability OBS-01 Advanced
28 hours 10 lessons 📚 4 library resources ✓ Expert reviewed ❓ 6 interview questions
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13
Data engineering and big data DAT-06 Advanced
21 hours 9 lessons 🎓 2 free certifications 📚 8 library resources ✓ Expert reviewed ❓ 11 interview questions
4. Prove it
2 packs · 50 hours
A capstone project, then portfolio, resume and interview practice.
-
14
Capstone project CAP-01 Advanced
24 hours 9 lessons ✓ Expert reviewed ❓ 8 interview questions
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15
Career readiness: portfolio, resume and interviews CAR-01 Beginner
26 hours 15 lessons 🎓 1 free certification ✓ Expert reviewed ❓ 24 interview questions
Add your edge
Optional packs that make you the candidate for a particular sector or degree.
Your branch · Pick the one that matches your degree.
- AI for CSE and IT
- AI for electronics and communication engineering
- AI for science and other branches
Your industry · Pick the sector you want to work in.
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