TensorFlow 2 for Deep Learning

Imperial College London is a world-leading science and engineering university located in the heart of London. Founded in 1907, it is renowned for excellence in research, innovation and teaching across STEM fields. With over 20,000 students, including more than 8,300 international students, Imperial offers a global, diverse community and strong industry connections that enhance learning and employability.

Imperial’s academic portfolio spans research-led undergraduate and postgraduate programs across science, engineering, medicine and business, with some 102 programs available to students. The college’s reputation is reflected in exceptionally high ratings for teaching and classes, modern facilities and strong student satisfaction. Research centres and partnerships with industry provide practical experience, internships and access to cutting-edge laboratories that prepare graduates for leadership roles.

Life at Imperial combines intense academic focus with the cultural and professional opportunities of London. Campus facilities, accommodation options and student services support wellbeing and career development, while extracurricular clubs and societies foster community and leadership. For international students seeking rigorous STEM training, Imperial delivers world-class instruction, extensive research opportunities and a powerful alumni network that supports global careers.

This program is a non-degree course for machine learning researchers and practitioners, taught in English at Imperial College London. It's 3 courses long and helps you build practical skills in deep learning with TensorFlow.

The curriculum covers fundamental concepts, including building and training deep learning models, using lower-level APIs, and developing complex model architectures. You'll also learn about sequence models and probabilistic models with TensorFlow, using the TensorFlow Probability library.

After completing this program, you can pursue careers as a Machine Learning Engineer, Deep Learning Researcher, AI Developer, Data Scientist, or Computer Vision Engineer, working in industries like tech, healthcare, or finance, for employers like Google, Microsoft, or NVIDIA.