Getting started with TensorFlow 2

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 for learners who want to get started with TensorFlow 2. It's a non-degree program at Imperial College London that lasts several weeks and is taught in English. The main advantage is that learners can develop deep learning models with TensorFlow.

The curriculum covers a complete end-to-end workflow for developing deep learning models, including building, training, evaluating, and predicting with models. Learners will practice their skills in hands-on coding tutorials and complete automatically graded programming assignments. They will also learn about the Sequential API, validation, regularization, and callbacks.

After completing this program, learners can pursue careers as deep learning engineers, machine learning developers, or data scientists. They can work in industries such as tech, finance, or healthcare, and for employers like Google or Microsoft. Other possible job titles include AI researcher or computer vision engineer.