School of Business | UstackSchool

AI-Powered Software Engineer — Hybrid Program

Topics Breakdown

Week 1

Python for AI Development

Key Points

• Python data structures: lists, dicts, sets, tuples
• Object-oriented programming: classes, inheritance, polymorphism
• File handling, JSON parsing, and data serialisation
• HTTP requests and REST API consumption
• Virtual environments and dependency management with pip
• Code quality: PEP 8, linting, type hints
• Writing unit tests with pytest for AI applications

Summary

Establish a professional Python engineering foundation for AI development. Build clean, well-tested Python applications, handle APIs, and adopt software engineering best practices from day one.

Skills Developed

Python programming

OOP principles

API integration

Testing with pytest

Code quality

Week 2

Data Engineering for AI

Key Points

• Data ingestion patterns: batch, streaming, real-time
• Data cleaning and preprocessing pipelines
• SQL databases: schema design and query optimisation
• NoSQL databases: document and key-value stores
• Vector databases: Pinecone, Weaviate, Chroma
• Data versioning with DVC
• ETL and ELT pipeline design patterns

Summary

Build the data infrastructure that powers AI applications. Design data pipelines, configure vector databases, and implement data versioning practices essential for production-grade AI systems.

Skills Developed

Data pipelines

Vector databases

Data engineering

SQL / NoSQL

ETL design

Week 3

Machine Learning Fundamentals

Key Points

• Supervised learning: regression and classification
• Unsupervised learning: clustering and dimensionality reduction
• Model training, validation, and test split strategy
• Evaluation metrics: accuracy, F1, AUC-ROC, RMSE
• Feature engineering and feature selection
• Overfitting, underfitting, and regularisation
• Scikit-learn pipeline construction and cross-validation

Summary

Develop applied machine learning skills to train, evaluate, and deploy predictive models. Build end-to-end ML pipelines using Scikit-learn and practise feature engineering techniques.

Skills Developed

Machine learning

Model evaluation

Feature engineering

Scikit-learn

Cross-validation

Week 4

APIs, Microservices & Backend Architecture

Key Points

• RESTful API design principles and best practices
• Building APIs with FastAPI and Pydantic
• Microservices architecture patterns and trade-offs
• API authentication: JWT tokens and OAuth 2.0
• Rate limiting, caching, and API security
• OpenAPI / Swagger documentation generation
• Async programming with Python asyncio

Summary

Build robust backend systems and APIs that serve AI capabilities. Design and deploy REST APIs, implement authentication, and architect microservices systems using industry-standard frameworks.

Skills Developed

API development

Microservices

Backend architecture

FastAPI

OAuth / JWT

Best Value

12 WEEKS · BEST VALUE

Full Bundle

12 weeks training + 8 weeks simulated internship

Payment Options

One-time or subscription

$3,000

$550

Save $2,450

One time payment before cohort starts

12 weeks live training
8 weeks simulated internship
Hands-on projects & scenario labs
Mentor & career coaching
Accredited certificate
CV, LinkedIn & interview prep
30–60 days post-program support

First-come, first-served · Only 17 seats

12 WEEKS · TRAINING

Training Only

12 weeks live instruction, no internship

Payment Options

One-time or subscription

$2,000

$300

Save $1,700

One time payment before cohort starts

12 weeks live instruction
All course materials & tools
Scenario labs & templates
Mentor sessions
Accredited certificate

First-come, first-served · Only 17 seats

8 WEEKS · ADD-ON

Career Experience

8 weeks simulated internship — post-training

Payment Options

One-time or subscription

$1,000

$250

Save $750

One time payment before the experience starts

8 weeks simulated internship
Real project briefs & deliverables
Expert feedback & mentoring
Portfolio-ready output
Reference letter

First-come, first-served · Only 17 seats

Projects by our Graduating Students

Effective Compliance Training with VR

While other companies use lengthy, monotonous compliance training, SISU VR’s product uses virtual reality to make this a more immersive and educative experience. They deliver compliance and prevention training with the competitive edge of Virtual Reality with immersive, realistic situations.