AI Engineer Career Path
Building products on deep learning, LLMs and agents.
- Tracks
- 7
- Modules
- 39
- Lessons
- 122
- Total time
- 36h 1m
7 tracks worth $63, 40% off. Paid once, yours for life.
Seven tracks for people who want to build AI systems, not just use them: Python, deep learning, LLMs and prompt engineering, AI agents, MLOps, computer vision and NLP. From how a single neuron works to an agent that calls tools safely in production.
Where this path takes you
- Build and train neural networks in PyTorch
- Build LLM applications with RAG and evaluation
- Design AI agents with tools, memory and guardrails
- Deploy vision and NLP models to production
The tracks inside, in order
7 tracksTake them in this order — each builds on the one before. Every track is yours for life, including lessons added later.
- 1
1. Python for Data Science
$9The language as a data practitioner uses it, not as a software engineer does.
3 modules4 lessons - 2
2. Introduction to Deep Learning & Neural Networks
$9Neural networks, from a single neuron to the transformer.
6 modules21 lessons - 3
3. LLMs, Prompt Engineering & Context Engineering
$9How LLMs work, how to instruct them, and how to fill their context.
6 modules22 lessons - 4
4. Building AI Agents: Harness Engineering
$9When the model is allowed to do things, not only to answer.
6 modules20 lessons - 5
5. MLOps: Deploying Machine Learning & Deep Learning Models
$9A model that only lives in a notebook is not finished.
6 modules19 lessons
- +1
- 6
6. Computer Vision with Deep Learning
$9Teaching machines to see: from pixels to object detection.
6 modules17 lessons - 7
7. Natural Language Processing (NLP)
$9From bags of words to embeddings and transformers.
6 modules19 lessons
- 7 tracks bought one by one
- $63
- Bundle discount (40%)
- −$25
- Bundle price
- $38