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Hands-on artificial intelligence

Certificación Profesional en
Deep Learning
IBM

Lo que aprenderás

  • Fundamental concepts of Deep Learning, including various Neural Networks for supervised and unsupervised learning.
  • 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.
  • Use of popular Deep Learning libraries such as Keras, PyTorch, and Tensorflow applied to industry problems.

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.

Capacitación de la mano de expertos
6 cursos de capacitación
A tu ritmo
Avanza a tu ritmo
7 meses
2 - 4 horas por semana
Precio con descuento: 525,60 US$
Precio original: 584 US$
Para obtener la experiencia completa del programa

Cursos en este programa

  1. Certificación Profesional en Deep Learning de IBM

  2. 2–4 horas por semana durante 5 semanas

    New 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 thepopular Keras library.

  3. 3–4 horas por semana durante 3 semanas

    Learn about computer vision, one of the most exciting fields in machine learning. artificial intelligence and computer science.

  4. 4–5 horas por semana durante 5 semanas

    This course is the first part in a two part course and will teach you the fundamentals of PyTorch. In this course you will implement classic machine learning algorithms, focusing on how PyTorch creates and optimizes models. You will quickly iterate through different aspects of PyTorch giving you strong foundations and all the prerequisites you need before you build deep learning models.

  5. 2–4 horas por semana durante 6 semanas

    This course is the second part of a two-part course on how to develop Deep Learning models using Pytorch.

  6. 2–4 horas por semana durante 5 semanas

    Much of theworld'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.

  7. 2–4 horas por semana durante 5 semanas

    In 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

Conoce a tus instructores

de IBM
Aije Egwaikhide
Senior Data Scientist
IBM
Romeo Kienzler
Chief Data Scientist
IBM
Samaya Madhavan
Advisory Software Engineer
IBM
Saeed Aghabozorgi
PhD, Sr. Data Scientist
IBM
Joseph Santarcangelo
PhD., Data Scientist
IBM
Alex Aklson
Ph.D., Data Scientist
IBM

Expertos de IBM comprometidos con el aprendizaje en línea

Inscríbete ahora

Precio con descuento: 525,60 US$
Precio original: 584 US$
6 cursos en 7 meses
Inscríbete en el programa

Inspiradores

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