Best Aspects: High-Quality Education: With your master's in Data Science and AI, the exposure to cutting-edge research, practical projects, and experienced faculty must be a huge highlight. Diverse Campus Community: The chance to connect with people from different cultures must’ve made your experience rich and inspiring. Practical Projects: Working on datasets like the Palmer Penguins or CRISP-DM in R must've sharpened your hands-on skills. Location: Newcastle is a vibrant city, full of life, with great student activities and access to scenic places like the Quayside. Career Opportunities: Networking events, career fairs, and a globally recognized degree must’ve opened up great prospects. Worst Aspects: Weather: Adjusting to Newcastle’s often rainy and chilly weather after coming from a warm climate like Chennai could’ve been tough. Homesickness: Being far from home and adapting to cultural differences might’ve been challenging. Intense Workload: Balancing demanding coursework, projects, and possibly a part-time job could've been overwhelming at times. Cost of Living: Living in the UK is expensive, and managing finances as a student might’ve been a stressor. Adapting to New Systems: Adjusting to different academic methods, such as independent learning or group projects, might’ve been a learning curve.

Best Aspects Cutting-Edge Curriculum: You learn the latest techniques in AI and data science, from machine learning and deep learning to big data analytics and cloud computing. Courses often combine theoretical knowledge with hands-on projects, which helps solidify concepts. Interdisciplinary Opportunities: The field combines computer science, statistics, and domain expertise, allowing you to work in various industries like healthcare, finance, and technology. Practical Skills Development: Emphasis on tools like Python, R, TensorFlow, and cloud platforms (AWS, Azure). Real-world datasets are often used in projects, preparing you for job roles. Networking: The opportunity to collaborate with peers and professors from diverse backgrounds fosters innovation and creates valuable professional networks. High Employability: With the growing demand for data scientists and AI professionals, the course opens doors to roles like data analyst, machine learning engineer, and AI researcher. Research and Innovation: Many programs include research components or thesis projects, letting students explore niche topics like NLP, computer vision, or reinforcement learning. Worst Aspects Intensive Workload: Balancing coursework, assignments, projects, and research can be overwhelming, especially for students transitioning from different fields. Steep Learning Curve: If you're not from a coding or mathematics background, subjects like linear algebra, calculus, and programming can feel daunting. Overemphasis on Tools: Some courses focus more on software and tools rather than foundational concepts, which can limit deeper understanding. Lack of Personalization: With so many students enrolled, individualized support from professors can be limited. Outdated Modules: Some universities may not update their curriculum frequently, leading to a gap between what’s taught and what the industry demands. Expensive Fees: International students often face high tuition fees, and the cost of living in some locations (like the UK) adds financial pressure. Unrealistic Expectations: Some students expect immediate results post-graduation, but breaking into top AI roles often requires additional experience and specialization.

What I like most: Convenience & Proximity: Many halls are close to the university campus and the city center, making it easy to attend lectures and access shops, restaurants, and nightlife. Community Feel: Living in halls is a great way to meet other students and make friends, especially for first-year students or international students looking to settle in. Inclusive Bills: Rent often includes utilities like water, electricity, and Wi-Fi, so there's no need to worry about extra costs. Support Services: Staff are usually available on-site to help with maintenance or any personal issues students might face. Diverse Options: There's a variety of accommodations (shared, en-suite, or studio) to suit different budgets and preferences. What I like least: Cost: Some halls can be expensive compared to private housing, especially for en-suite or studio options. Noise Levels: Shared living often comes with noise, especially during weekends or exam periods, which might not be ideal for studying or relaxing. Lack of Privacy: Sharing kitchens, bathrooms (in non-en-suite halls), and common spaces can feel intrusive at times. Maintenance Delays: While support is available, maintenance requests can sometimes take a while to be resolved. Limited Space: Rooms are often compact, and storage can be a challenge for students with a lot of belongings.

great environment and location. Campus is clean and well kept. Close to trains station as well as a variety of different shops. Events are constantly on at the SU

lots of 24 hour centres

not had any need for it as of yet

nice environment to chill, drink and eat

fantastic range of bars and clubs all really affordable

not personally involved but people that are say they are good and host some great nights out

most are friendly and willing to help

my course is unique and very few universities do it and they have lots of connections

accommodation is poor but the people you live wit are more down to earth