Deep Learning: Mastering Neural Networks
Expand your skill set and help your organization make data-informed predictions.
Deep learning has transformed how organizations analyze data and make data-driven decisions, making it crucial for professionals to gain AI-related skills to stay competitive. This 8-week course from MIT xPRO offers you a comprehensive introduction to this field, combining theory and hands-on practice. You will gain skills and tools like Python to design and optimize neural networks for classification, regression, and sequential data processing. Also, master techniques like transfer learning, convolutional (CNN) and recurrent neural networks (RNN).
Throughout this course, you will
- Explore the core mathematical and conceptual ideas underlying deep neural networks.
- Experiment with deep learning models and algorithms using available machine learning toolkits.
- Examine application approaches and case studies where deep learning is being used throughout a variety of industries.
- Understand advanced neural network architectures for application in software products.
- Gain strategic insights into AI and its potential impact on business models.

This course is aimed at
- Software engineers and developers aiming to build and optimize AI-driven applications.
- Data scientists and analysts looking to deepen their expertise in AI and machine learning.
- AI & ML professionals seeking to leverage neural network techniques to solve complex problems with innovative solutions.
- Technology professionals eager to explore cutting-edge advancements in AI and deep learning.
Certificate
Meet your instructor

Duane S. Boning
Clarence J. LeBel Professor of Electrical Engineering | Professor de Electrical Engineering y Computer Science en el departamento EECS de MIT.
Program Highlights
Neural Networks building
Python tools and libraries to build training neural networks
Cutting-edge techniques
Deep Neural Networks: GANs and Transformers
Contextualized learning
Guided cases studies about Deep Neural Networks
Hands-on learning
Learning methodology that allows participants to practice their newly acquired skills, with one live session every two weeks for guidance and Q&A.
Networking and exchange
Networking with fellow participants to share experiences and build collaborative relations
Prestigious certificate
Certificate in Deep Learning in addition to 4.8 Continuing Education Unit (MIT CEUs)
What is the course comprised of?
- Multiple-choice activities
- Interactive contents
- Projects to be developed as a team, adding value to your experience
- Action Plan Activities (Designed to Apply What You Have Learned to Your Own Company)
- Video content taught by mit faculty and experts from different industries
- Live webinars to clear up doubts and discuss what you have learned
- Additional recommended resources
