AITeky Learn

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
264 (of 406, foundation optional)
At 6 hours a week
about 11 months
Free certifications
19
Library resources
90
Interview questions
168

βœ“ All 168 lessons expert reviewed

Your route. Skip any foundation pack whose outcomes you already have at work. Start at the core skills, build the capstone on a problem from your own job, and add an industry pack for your sector.

Industry 5.0 Β· this path teaches 1 of 3 pillars

🀝 Human-centred + 🌱 Sustainable: add I50-SUS+ πŸ›‘οΈ Resilient: add I50-RES

1. Foundation

5 packs Β· 142 hours

The base every pack after it builds on. Skip a pack here if you already do this at work.

  1. 1

    Python programming FND-01 Beginner

    37 hours 15 lessons πŸŽ“ 4 free certifications πŸ“š 8 library resources βœ“ Expert reviewed ❓ 18 interview questions

  2. 2

    Developer toolkit: command line, Git and AI coding assistants FND-02 Beginner

    16 hours 8 lessons πŸŽ“ 1 free certification πŸ“š 8 library resources βœ“ Expert reviewed ❓ 11 interview questions

  3. 3

    SQL and databases FND-03 Beginner

    32 hours 13 lessons πŸŽ“ 3 free certifications πŸ“š 8 library resources βœ“ Expert reviewed ❓ 16 interview questions

  4. 4

    Linux and networking LNX-01 Beginner

    30 hours 11 lessons πŸŽ“ 1 free certification πŸ“š 4 library resources βœ“ Expert reviewed ❓ 6 interview questions

  5. 5

    Data wrangling with NumPy and pandas DAT-02 Beginner

    27 hours 11 lessons πŸŽ“ 1 free certification πŸ“š 8 library resources βœ“ Expert reviewed ❓ 11 interview questions

2. Core skills

3 packs Β· 80 hours

The skills the job is made of.

  1. 6

    Containers, CI/CD and cloud foundations OPS-01 Beginner

    24 hours 11 lessons πŸŽ“ 1 free certification πŸ“š 8 library resources βœ“ Expert reviewed ❓ 10 interview questions

  2. 7

    Machine learning ML-01 Beginner

    32 hours 14 lessons πŸŽ“ 2 free certifications πŸ“š 8 library resources βœ“ Expert reviewed ❓ 15 interview questions

  3. 8

    MLOps: deploying and running machine learning models OPS-02 Advanced

    24 hours 11 lessons πŸŽ“ 1 free certification πŸ“š 6 library resources βœ“ Expert reviewed ❓ 9 interview questions

3. Specialise

5 packs Β· 134 hours

The depth that sets you apart in interviews.

  1. 9

    Feature engineering, tuning and responsible machine learning ML-02 Advanced

    24 hours 10 lessons πŸŽ“ 2 free certifications πŸ“š 8 library resources βœ“ Expert reviewed ❓ 11 interview questions

  2. 10

    Kubernetes in depth K8S-01 Advanced

    32 hours 11 lessons πŸ“š 6 library resources βœ“ Expert reviewed ❓ 6 interview questions

  3. 11

    Infrastructure as code with Terraform and Ansible IAC-01 Advanced

    29 hours 10 lessons πŸ“š 6 library resources βœ“ Expert reviewed ❓ 6 interview questions

  4. 12

    Observability and site reliability OBS-01 Advanced

    28 hours 10 lessons πŸ“š 4 library resources βœ“ Expert reviewed ❓ 6 interview questions

  5. 13

    Data engineering and big data DAT-06 Advanced

    21 hours 9 lessons πŸŽ“ 2 free certifications πŸ“š 8 library resources βœ“ Expert reviewed ❓ 11 interview questions

4. Prove it

2 packs Β· 50 hours

A capstone project, then portfolio, resume and interview practice.

  1. 14

    Capstone project CAP-01 Advanced

    24 hours 9 lessons βœ“ Expert reviewed ❓ 8 interview questions

  2. 15

    Career readiness: portfolio, resume and interviews CAR-01 Beginner

    26 hours 15 lessons πŸŽ“ 1 free certification βœ“ Expert reviewed ❓ 24 interview questions

Add your edge

Optional packs that make you the candidate for a particular sector or degree.

Your industry Β· Pick the sector you want to work in.

See every your industry pack

Sign up free to see the free certifications and interview preparation for this role

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