What you will learn
- Fundamental concepts of Deep Learning, including various Neural Networks for supervised and unsupervised learning.
- Use of popular Deep Learning libraries such as Keras, PyTorch, and Tensorflow applied to industry problems.
- Build, train, and deploy different types of Deep Architectures, including Convolutional Networks, Recurrent Networks, and Autoencoders.
- Application of Deep Learning to real-world scenarios such as object recognition and Computer Vision, image and video processing, text analytics, Natural Language Processing, recommender systems, and other types of classifiers.
- Master Deep Learning at scale with accelerated hardware and GPUs.
AI is revolutionizing the way we live, work and communicate. At the heart of AI is Deep Learning. Once a domain of researchers and PhDs only, Deep Learning has now gone mainstream thanks to its practical applications and availability in terms of consumable technology and affordable hardware.
The demand for Data Scientists and Deep Learning professionals is booming, far exceeding the supply of personnel skilled in this field. The industry is clearly embracing AI, embedding it within its fabric. The demand for Deep Learning skills by employers -- and the job salaries of Deep Learning practitioners -- are only bound to increase over time, as AI becomes more pervasive in society. Deep Learning is a future-proof career.
Within this series of courses, you’ll be introduced to concepts and applications in Deep Learning, including various kinds of Neural Networks for supervised and unsupervised learning. You’ll then delve deeper and apply Deep Learning by building models and algorithms using libraries like Keras, PyTorch, and Tensorflow. You’ll also master Deep Learning at scale by leveraging GPU accelerated hardware for image and video processing, as well as object recognition in Computer Vision.
Throughout this program you will practice your Deep Learning skills through a series of hands-on labs, assignments, and projects inspired by real world problems and data sets from the industry. You’ll also complete the program by preparing a Deep Learning capstone project that will showcase your applied skills to prospective employers.
This program is intended to prepare learners and equip them with skills required to become successful AI practitioners and start a career in applied Deep Learning.
Courses in this program
IBM's Deep Learning Professional Certificate
- 2–4 hours per week, for 5 weeksNew to deep learning? Start with this course, that will not only introduce you to the field of deep learning but give you the opportunity to build your first deep learning model using the popular Keras library.
- 2–4 hours per week, for 6 weeksLearn how to use Python and its popular libraries such as NumPy and Pandas, as well as the PyTorch Deep Learning library. You'll then apply them to build Neural Networks and Deep Learning models.
- 2–4 hours per week, for 5 weeksMuch of the world's data is unstructured. Think images, sound, and textual data. Learn how to apply Deep Learning with TensorFlow to this type of data to solve real-world problems.
- 2–4 hours per week, for 5 weeksTraining complex deep learning models with large datasets takes a long time. In this course, you will learn how to use accelerated GPU hardware to overcome the scalability problem in deep learning.
- 2–4 hours per week, for 5 weeksIn this capstone project, you'll use either Keras or PyTorch to develop, train, and test a Deep Learning model. Load and preprocess data for a real problem, build the model and then validate it.
- Annual demand for the fast-growing new roles of data scientist, data developers, and data engineers will reach nearly 700,000 openings by 2020. (Source: Burning Glass Technologies, Business-Higher Education Forum (BHEF), and IBM)
- Average salary for a Machine Learning Engineer is $136,054 (Source: Indeed.com)
- Career prospects include Deep Learning & Computer Vision Engineer, Machine Learning Engineer, Data Scientist, Data Analyst, Data Engineer, AI / Deep Learning Scientist and Data Science Instructor
Unfortunately, learners from Iran and Cuba will not be able to register for this course. While edX has received a licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer courses to learners from these countries, our licenses do not cover this course. EdX truly regrets that US sanctions prevent us from offering all of our courses to everyone, no matter where they live.