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Future-Ready Program
AI & ML Engineering
Master deep learning, NLP, and agentic multi-agent orchestration systems
Go beyond API wrapping. Dive deep into supervised learning, neural network architectures, fine-tuning large language models, and building multi-agent graph workflows with LangGraph.
Learning outcomes
- Build and train neural network models with PyTorch and TensorFlow
- Fine-tune pretrained transformers using Hugging Face tools
- Implement stateful, multi-agent cooperative workflows using LangGraph and LangChain
- Optimize LLM deployments using quantization and custom inference runtimes
Prerequisites
- Strong foundations in linear algebra, probability, and Python
- A laptop with 16GB+ RAM (GPU recommended)
Curriculum
A complete, week-by-week roadmap.
From fundamentals to production deployment.
01
ML Foundations
- Linear Regression
- Decision Trees
- Scikit-learn
02
Deep Learning
- Neural Networks
- PyTorch
- Backpropagation
03
NLP & Transformers
- Attention Mechanisms
- Hugging Face
- Fine-Tuning
04
Agentic Multi-Agent Systems
- LangGraph
- State Graphs
- Tool Call loops
Real-world projects
Ship applications you can actually walk an interviewer through.
- Custom fine-tuned specialized medical QA LLM
- LangGraph-powered automated research agent team
Career opportunities
Roles this program prepares you for.
Machine Learning Engineer AI Researcher NLP Engineer Agentic Architect
Agentic AI workflows
AI automation in this course
Practical agentic AI use cases woven directly into your weekly builds.
Use case 01
Program cooperative multi-agent architectures
Use case 02
Implement auto-evaluators to rate agent performance
Use case 03
Deploy custom memory management for conversational bots
Ready to start AI & ML Engineering?
Enroll online and access the full curriculum in your learner dashboard.
Enroll — Free