IBM AI Engineering Professional Certificate

IBM AI Engineering Professional Certificate

IBM AI Engineering Professional Certificate Launch your career as an AI engineer. Learn how to provide business insights from big data using machine learning and deep learning techniques. Taught in English 22 languages available Some content may not be translated Instructors: Romeo Kienzler +6 more Close Instructors Romeo Kienzler IBM 10 Courses • 632,415 learners

Description

IBM AI Engineering Professional Certificate: A Gateway to Success in the Field of Artificial Intelligence

In today’s fast-paced and ever-evolving technological landscape, the demand for professionals with expertise in artificial intelligence (AI) is at an all-time high. Organizations across various industries are increasingly harnessing the power of AI to drive innovation, improve operational efficiency, and gain a competitive edge. As such, individuals looking to advance their careers in this field must equip themselves with the necessary skills and knowledge to thrive in this rapidly growing industry.

To meet this growing demand, IBM has developed the AI Engineering Professional Certificate, a comprehensive online training program designed to provide learners with the essential skills and understanding needed to excel in the field of AI engineering. This certificate program is tailored to individuals with varying levels of experience in AI and offers a blend

IBM AI Engineering Professional Certificate

Launch your career as an AI engineer. Learn how to provide business insights from big data using machine learning and deep learning techniques.

Taught in English

Some content may not be translated

Romeo Kienzler
Joseph Santarcangelo
Alex Aklson

Instructors: Romeo Kienzler

47,781 already enrolled

Professional Certificate – 6 course series

Earn a career credential that demonstrates your expertise

4.5

(6,012 reviews)

Intermediate level
Some related experience required
2 months at 10 hours a week
Flexible schedule
Learn at your own pace
Earn degree credit

What you’ll learn

  • Describe machine learning, deep learning, neural networks, and ML algorithms like classification, regression, clustering, and dimensional reduction 

  • Implement supervised and unsupervised machine learning models using SciPy and ScikitLearn 

  • Deploy machine learning algorithms and pipelines on Apache Spark 

  • Build deep learning models and neural networks using Keras, PyTorch, and TensorFlow 

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