AI-Powered Software Engineer

Build, deploy, and scale intelligent applications using modern AI frameworks, APIs, and cloud infrastructure.

4Modules

16 WeeksWeeks Duration

$110kAvg. Salary

90%Job Placement

Current cohort

Enroll now

16 Saturdays • 16 Thursdays

Thursday 7pm–9PM (GMT+1) | Saturday: 8AM–12PM / 3PM–6PM WAT

4 Modules · 16 Weeks

Next cohort

16 Saturdays • 16 Thursdays

Thursday 7pm–9PM (GMT+1) | Saturday: 8AM–12PM / 3PM–6PM WAT

OUR GRADUATES ARE HIRED BY

About this course

The AI-Powered Software Engineer Accelerator trains developers to build, deploy, and scale intelligent applications using modern AI frameworks, APIs, and cloud infrastructure. Over 16 weeks you will master software engineering fundamentals, LLM integration, AI application development, and MLOps — graduating with a production-ready AI portfolio.

You'll have access to:

6 Live Sessions

16 Audio Lessons

Book Summaries

Coding Projects

AI Labs

GitHub Portfolio

AI Software Engineer Certificate

Duration: 16 Weeks (4 Months)

Choose Your Learning Path

$400

Standard Bundle

Tools You'll Learn

Python

OpenAI / Anthropic APIs

LangChain / LlamaIndex

FastAPI

Docker / Kubernetes

AWS / GCP / Azure AI

GitHub / CI/CD

PostgreSQL / Pinecone

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

Choose Your Plan

16 WEEKS · PLAN

AI-Powered Software Engineer

16 Weeks

Payment Options

Standard Bundle

$400

Single payment – full access

Complete course access
All modules & tools included
Certificate of completion

16 WEEKS · PLAN

3-Month Installment Plan

16 Weeks

Payment Options

Installments (3 × $133)

$133/mo

3 monthly installments

$133 monthly payment

3 installments: $133 monthly payment

Complete course access
All modules & tools included
Certificate of completion

Single payment – full access
3 monthly payments

Our proven approach to student success

Maybe you’ve tried YouTube or a low-cost web development course. If you have, you know learning on your own can only take you so far. Humans learn best from other humans.
Ustack’s proven human-centric approach means you have a team behind you from day one.

Mastery from your mentor

Build software engineering skills faster with an expert in your corner. Your mentor will keep you accountable and give you an insider's view.

Counsel from your career coach

Get prepared for the job search. Your career coach will help you gain confidence and know-how to land the role.

Support from your student advisor

Stay on track and achieve your goals. Your student advisor has your back and will keep you on track to graduation.

Build a portfolio that proves your skills to hiring managers

In this bootcamp, you’ll work on six hands-on mini projects and five full portfolio projects, including a capstone product you can proudly showcase. By the end, you’ll have an interview-ready portfolio that proves your skills to hiring managers—and sets you apart from the crowd.

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.