
Magnus Hyttsten
Engineering Manager at Google
Dive into deep learning with this practical course on TensorFlow and the Keras API. Gain an intuitive understanding of neural networks without the dense jargon. Learn to build, train, and optimize your own networks using TensorFlow. The course also introduces transfer learning, leveraging pre-trained models for enhanced performance. Designed for swift proficiency, this course prioritizes hands-on learning and real-world applications.

Intro to TensorFlow for Deep Learning
0 prerequisites
You will need to be able to communicate fluently and professionally in written and spoken English.
3 instructors
Unlike typical professors, our instructors come from Fortune 500 and Global 2000 companies and have demonstrated leadership and expertise in their professions:

Magnus Hyttsten
Engineering Manager at Google

Juan Delgado
Computational Physicist

Paige Bailey
Developer Advocate, Google
Excellent program with real, hands-on quality. The Data Analyst Nanodegree isn't just theory: every course ends with a practical capstone project where you apply the skills to real, messy data end-to-end. In the Real-World Data Wrangling project, for example, I gathered two datasets through different methods (API and file download), assessed and cleaned quality/tidiness issues, and built visualizations to answer a real research question. That practical, project-based structure is what makes the learning stick. Highly recommended.
Jul 11, 2026
Excellent nanodegree
Jul 3, 2026
Course completed
Jun 23, 2026
This program provided clear and practical insights into stakeholder engagement, which are highly relevant for a Data Analyst role. The concepts on communication, expectation management, and collaboration can be directly applied to improve interactions with cross-functional teams and enhance data-driven decision-making.
Jun 22, 2026
Very useful
Jun 22, 2026

Intro to TensorFlow for Deep Learning