Frequently Asked Questions

We offer a full refund if requested within 3 days of starting the course. No questions asked.

It is a self-paced course.

The curriculum covers Python for data science, machine learning foundations, deep learning, natural language processing, computer vision, generative AI, model deployment, MLOps, and practical AI engineering projects with real-world applications.

Students should expect to commit 15-20 hours per week for the program. This includes 8 hours of live instruction, 5-7 hours of hands-on projects, and 2-5 hours of self-paced learning activities.

The program is primarily remote and online, allowing for flexible participation.

No, you don't need prior machine learning experience. We've designed our curriculum to take experienced software engineers from ML fundamentals to advanced AI applications. We do expect strong programming skills and computer science fundamentals.

The program primarily uses Python and its major AI/ML libraries including PyTorch, TensorFlow, Scikit-learn, Hugging Face transformers, and various data processing libraries. We also cover deployment technologies including Docker, FastAPI, and cloud services.

You'll need a relatively modern computer with at least 8GB of RAM and a stable internet connection. For deep learning exercises, we provide cloud-based GPU resources, so you won't need specialized hardware. All necessary software is open-source or provided by us.

Yes, you'll complete 5-7 projects throughout the program, culminating in a capstone project that demonstrates your AI engineering skills. All projects will be added to your portfolio, and you'll have the opportunity to showcase them to potential employers during our demo days.