AITeky Learn

Machine learning and data science

NLP Engineer

Also called: Natural Language Processing Engineer, Language AI Engineer, Text Analytics Engineer

Builds systems that read and write language: classification, extraction, search, translation and summarisation.

Skill Packs
12
Class hours
222 (of 307, foundation optional)
At 6 hours a week
about 10 months
Free certifications
15
Library resources
80
Interview questions
165

βœ“ All 141 lessons expert reviewed

Your route. Skip the foundation if you already use AI tools at work. Take the Leading with AI packs on the problems of your own organisation, and finish with the capstone AI plan that a mentor reviews with you.

Industry 5.0 Β· this path teaches 0 of 3 pillars

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

1. Foundation

3 packs Β· 85 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

    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

  3. 3

    Mathematics for machine learning MTH-01 Beginner

    21 hours 10 lessons πŸ“š 8 library resources βœ“ Expert reviewed ❓ 11 interview questions

2. Core skills

3 packs Β· 85 hours

The skills the job is made of.

  1. 4

    Machine learning ML-01 Beginner

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

  2. 5

    Deep learning DL-01 Advanced

    29 hours 12 lessons πŸŽ“ 2 free certifications πŸ“š 8 library resources βœ“ Expert reviewed ❓ 12 interview questions

  3. 6

    Natural language processing NLP-01 Advanced

    24 hours 10 lessons πŸ“š 8 library resources βœ“ Expert reviewed ❓ 10 interview questions

3. Specialise

4 packs Β· 87 hours

The depth that sets you apart in interviews.

  1. 7

    Generative AI foundations: how LLMs work and how to call them GEN-01 Beginner

    18 hours 11 lessons πŸŽ“ 2 free certifications πŸ“š 8 library resources βœ“ Expert reviewed ❓ 13 interview questions

  2. 8

    Prompt and context engineering with structured outputs GEN-02 Beginner

    21 hours 11 lessons πŸŽ“ 1 free certification πŸ“š 8 library resources βœ“ Expert reviewed ❓ 12 interview questions

  3. 9

    Generative AI with retrieval-augmented generation (RAG) and vector databases GEN-03 Advanced

    28 hours 13 lessons πŸŽ“ 2 free certifications πŸ“š 8 library resources βœ“ Expert reviewed ❓ 21 interview questions

  4. 10

    Fine-tuning, small language models and model serving GEN-04 Advanced

    20 hours 10 lessons πŸ“š 8 library resources βœ“ Expert reviewed ❓ 10 interview questions

4. Prove it

2 packs Β· 50 hours

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

  1. 11

    Capstone project CAP-01 Advanced

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

  2. 12

    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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