• Anytime
    Application Deadline
  • 7 months
    Duration
EdX is an online learning platform trusted by over 12 million users offering the Deep Learning Professional Certificate in collaboration with IBMx. This hands-on program will prepare and equip you with the in-demand skills required to become a successful AI practitioner and start a career in the growing and lucrative field of deep learning.
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Overview

The Deep Learning Professional Certificate from EdX is offered in partnership with IBMx.

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.

Detailed Programme Facts

  • Deadline and start date A student can apply at any time for this programme, there is no deadline.
  • Programme intensity Part-time
    • Average part-time duration 7 months
    • Part-time variant
      Flexible
    • Duration description

      2-4 weeks per course

  • Languages
    • English
  • Delivery mode
    Online
    • Time flexibility
      Self-paced
  • More information Go to the programme website

Programme Structure

What You'll 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.

English Language Requirements

This programme may require students to demonstrate proficiency in English.

Tuition Fee

  • International

    495 USD/full
    Tuition Fee
    Based on the original amount of 495 USD for the full programme and a duration of 7 months.
  • National

    495 USD/full
    Tuition Fee
    Based on the original amount of 495 USD for the full programme and a duration of 7 months.
We've labeled the tuition fee that applies to you because we think you are from and prefer over other currencies.

5% discount coupon: Z7LZNQ4TN3B2JTWU valid for any free course + certificate upgrade

Funding

Check the programme website for information about funding options.

Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.

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