July 2019
Beginner to intermediate
34h 31m
English
Closed Captioning available in English
Overview
In this 34 hr course, you will gain essential knowledge and skills in deep learning. The course covers neural network architectures, key techniques like regularization and transfer learning, and includes hands-on projects using Python. You'll not only learn theoretical concepts but also apply them to solve real-world problems.
What I will be able to do after this course
- Develop a solid understanding of deep learning and its foundational mathematics.
- Learn to implement neural networks, including CNNs and RNNs, in Python for solving complex problems.
- Master key optimization techniques like backpropagation and regularization to enhance machine learning models.
- Build and train models for applications like image classification and natural language processing.
- Gain practical experience by completing real-world projects to solidify your deep learning skills.
Course Instructor(s)
The course is taught by a team of IIT professionals with expertise in mathematics and data science. They have extensive experience in teaching and apply proven methods to explain complex topics effectively. Their hands-on approach includes real-world projects to help learners relate theoretical concepts to practical applications.
Who is it for?
This course is ideal for beginners in Python or programming who aim to learn deep learning from scratch. It also benefits data analysts and machine learning practitioners looking to upgrade their skills. Experienced professionals considering a transition to data science or AI-focused roles will find this course extremely beneficial.
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