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IBM AI Engineering Professional Certificate

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Total Duration
9 Months

Artificial intelligence (AI) is revolutionizing entire industries, changing the way companies across sectors leverage data to make decisions. To stay competitive, organizations need qualified AI engineers who use cutting-edge methods like machine learning algorithms and deep learning neural networks to provide data driven actionable intelligence for their businesses. This 6-course Professional Certificate is designed to equip you with the tools you need to succeed in your career as an AI or ML …

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Courses in this Learning Path
1
Machine Learning with Python
IBM Course via Coursera
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Duration : 21 hours
Level :Intermediate
Learn Type :Certification
Machine Learning with Python
IBM Course via Coursera

This course will teach you how to use Python, a familiar and simple programming language, to machine-learn.

The course covers two main components. First, you will learn about Machine Learning and how it is applied in the real world.
The second gives an overview of Machine Learning topics such as supervised vs unsupervised learning, model evaluation, and Machine Learning algorithms.

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2
Introduction to Deep Learning & Neural Networks with Keras
IBM Course via Coursera
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Duration : 8 hours
Level :Intermediate
Learn Type :Certification
Introduction to Deep Learning & Neural Networks with Keras
IBM Course via Coursera

Are you looking to make a career out of Deep Learning? You have come to the right place. This course will introduce deep learning to you and answer many of the questions people ask nowadays. Learn about deep learning models, and then build your first deep-learning model with Keras.

This course will allow learners to: * describe a neural network, what a deep-learning model is and what the …

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3
Introduction to Computer Vision and Image Processing
Coursera Course via Coursera
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Duration : 21 hours
Level :Beginner
Learn Type :Certification
Introduction to Computer Vision and Image Processing

Computer Vision is an exciting area of Machine Learning and AI. There are many applications for it, including in self-driving cars and robotics. Augmented reality is another example. This course is easy to understand and will cover the various applications of computer vision across many industries.

This course will teach you how to use Python, Pillow, OpenCV, and OpenCV to perform basic image …

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4
Deep Neural Networks with PyTorch
IBM Course via Coursera
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Duration : 31 hours
Level :Intermediate
Learn Type :Certification
Deep Neural Networks with PyTorch
IBM Course via Coursera

This course will show you how to create deep learning models with Pytorch. The course will begin with Pytorch's Tensors and Automatic differentiation packages. Each section will then cover different models, starting with Linear Regression and logistic/softmax. Then comes Feedforward deep neural network, which will cover the roles of different activation functions and normalization layers. …

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5
Building Deep Learning Models with TensorFlow
IBM Course via Coursera
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Duration : 13 hours
Level :Intermediate
Learn Type :Certification
Building Deep Learning Models with TensorFlow
IBM Course via Coursera

Most of the data in the world are unlabeled or unstructured. Deep neural networks are unable to capture the relevant structure, such as images, sounds, and textual data. These types of data are best suited for deep networks, which can discover hidden structures. This course will teach you how to use TensorFlow library for deep learning on different data types to solve real-world problems.

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6
AI Capstone Project with Deep Learning
IBM Course via Coursera
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Duration : 16 hours
Level :Advanced
Learn Type :Certification
AI Capstone Project with Deep Learning
IBM Course via Coursera

This capstone will allow learners to apply their deep learning knowledge to solve a real-world problem. To develop and test a deep-learning model, they will use a library that interests them. They will load real data, pre-process it and then build and validate the model. To demonstrate their knowledge and proficiency in Deep Learning, learners will present a project report.

Learning Outcomes