AI Engineering Specialization course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
This AI Engineering Specialization offers a comprehensive, hands-on curriculum designed to equip learners with practical skills for real-world AI engineering roles. Spanning approximately 12–16 weeks with a recommended 6–8 hours per week, the program covers foundational machine learning, deep learning, model deployment, and culminates in a capstone project. Learners will gain experience in building, evaluating, and deploying AI systems using industry-standard tools and cloud platforms, preparing them for production-level AI development.
Module 1: Foundations of AI & Machine Learning
Estimated time: 90 hours
- Understand supervised and unsupervised learning
- Explore regression and classification models
- Learn Python-based ML tools
- Evaluate model performance metrics
Module 2: Deep Learning & Neural Networks
Estimated time: 90 hours
- Build neural network architectures
- Apply convolutional neural networks (CNNs)
- Understand backpropagation and optimization
- Train and fine-tune deep learning models
Module 3: Model Deployment & AI Applications
Estimated time: 90 hours
- Deploy models using APIs
- Integrate AI systems into applications
- Use cloud-based AI services
- Monitor deployed model performance
Module 4: Capstone Project
Estimated time: 60 hours
- Develop an end-to-end AI solution
- Train, test, and deploy a model
- Apply best practices in AI engineering
- Demonstrate production-ready AI workflows
Prerequisites
- Basic knowledge of Python programming
- Familiarity with fundamental machine learning concepts
- Comfort with technical and fast-paced content
What You'll Be Able to Do After
- Design and train machine learning models using Python and industry-standard libraries
- Build and optimize deep learning models including neural networks and CNNs
- Deploy AI models into production using APIs and cloud platforms
- Evaluate and monitor model performance in real-world environments
- Develop end-to-end AI systems aligned with industry engineering standards