Frequently Asked Questions

The course requires a basic understanding of public health concepts, fundamental statistics knowledge, and basic computer literacy. While programming experience is helpful, it's not required as we'll teach Python from the ground up. We recommend familiarity with research methods and some background in epidemiology or biostatistics, but motivated students from various backgrounds are welcome.

No prior programming experience is required! We start with Python basics and gradually build up to more advanced concepts. However, students with some programming background in any language will find it easier to follow along. We provide extensive support through teaching assistants and office hours for students new to programming.

All required software is free and open-source. You'll need Python (we'll help you install it), Jupyter Notebooks, and various libraries like pandas, scikit-learn, and TensorFlow. We also use cloud platforms like Google Colab for some exercises, which requires only a web browser. A detailed setup guide will be provided before the course starts.

The course is offered in a hybrid format. All sessions are recorded for later review.

Plan to spend approximately 8-10 hours per week on this course. This includes 4 hours of class time, 2 hours of lab sessions, and 2-4 hours of homework and project work. During project weeks, you may need to dedicate additional time, especially for the final capstone project.

Registration is handled through your institution's standard enrollment system. The course code is AI4PH01: AI for Public Health. If you're not currently enrolled at our institution, please contact our admissions office about special student status or continuing education options.

Yes, we limit enrollment to 100 students to ensure quality instruction and adequate support. Registration is on a first-come, first-served basis. We recommend registering early as the course typically fills up quickly due to high demand.

Auditing is allowed with instructor permission, subject to space availability. Auditors can attend lectures and access course materials but cannot submit assignments or receive grades. Please contact the course director if you're interested in auditing.

Tuition for this course is ৳15,000 and may vary slightly depending on your enrollment status. There are no additional lab fees, and all required software is freely available.

Grading is based on weekly assignments (30%), group projects (40%), and a final capstone project (30%). We use a standard letter grading scale. Late submissions are penalized 10% per day unless prior arrangements are made. Participation in discussions and peer reviews is also considered.

No traditional exams. Assessment is entirely project-based and practical. You'll work on real-world problems using actual health datasets. This approach better reflects how you'll apply these skills in professional settings and allows for more meaningful learning experiences.

Weekly assignments are individual work, but we encourage study groups and peer discussion. Group projects are explicitly collaborative (3-4 students per group). The final capstone is individual work. We'll provide guidelines on collaboration vs. individual work for each assignment.

Don't panic! Reach out to the teaching team immediately. We offer extensive office hours, study groups, and one-on-one support. All lectures are recorded, and we provide additional resources for students who need extra help. Early communication is key to getting back on track.

Any modern laptop or desktop computer will work. Minimum requirements: 4GB RAM, 10GB free storage, and a reliable internet connection. We recommend 8GB+ RAM for better performance with larger datasets. Both Windows and Mac are supported. Chromebooks can work using cloud platforms.

We provide comprehensive technical support through multiple channels: dedicated IT support hours, peer tutoring, online forums, and detailed troubleshooting guides. Most common issues are resolved quickly. For persistent problems, we can arrange one-on-one technical assistance.

Yes, with instructor approval! We encourage students to work with datasets relevant to their research or professional interests. However, ensure you have proper permissions and that the data meets privacy/ethical requirements. We can help you evaluate dataset suitability.

Yes! Students who successfully complete the course receive an official certificate of completion. This certificate is recognized by many employers and can be used for continuing education credits. We also provide detailed transcripts showing specific skills and competencies gained.

This course provides highly sought-after skills in the growing field of health AI. Graduates have found opportunities in public health agencies, healthcare organizations, tech companies, research institutions, and consulting firms. We also provide career guidance and networking opportunities with industry professionals.

Absolutely! We offer advanced courses, research opportunities, and maintain an active alumni network. Many students continue with independent study projects, internships, or thesis work with our faculty. We also host regular seminars and workshops on emerging topics in health AI.