IBM
IBM AI Engineering Professional Certificate
IBM

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.

Wojciech 'Victor' Fulmyk
Ricky Shi
Romeo Kienzler

Instructors: Wojciech 'Victor' Fulmyk

Sponsored by Veterans Transition Support

106,186 already enrolled

Earn a career credential that demonstrates your expertise
4.5

(6,749 reviews)

Intermediate level
Some related experience required
Flexible schedule
3 months, 10 hours a week
Learn at your own pace
Build toward a degree
Earn a career credential that demonstrates your expertise
4.5

(6,749 reviews)

Intermediate level
Some related experience required
Flexible schedule
3 months, 10 hours a week
Learn at your own pace
Build toward a degree

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 

Details to know

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Taught in English

See how employees at top companies are mastering in-demand skills

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Advance your career with in-demand skills

  • Receive professional-level training from IBM
  • Demonstrate your technical proficiency
  • Earn an employer-recognized certificate from IBM
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Professional Certificate - 6 course series

Machine Learning with Python

Course 113 hours4.7 (16,374 ratings)

What you'll learn

  • Describe the various types of Machine Learning algorithms and when to use them 

  • Compare and contrast linear classification methods including multiclass prediction, support vector machines, and logistic regression 

  • Write Python code that implements various classification techniques including K-Nearest neighbors (KNN), decision trees, and regression trees 

  • Evaluate the results from simple linear, non-linear, and multiple regression on a data set using evaluation metrics 

Skills you'll gain

Category: Machine Learning

Introduction to Deep Learning & Neural Networks with Keras

Course 28 hours4.7 (1,636 ratings)

What you'll learn

Skills you'll gain

Category: Algorithms
Category: Artificial Neural Networks
Category: Deep Learning
Category: Human Learning
Category: Machine Learning
Category: Machine Learning Algorithms
Category: Network Model
Category: Applied Machine Learning
Category: Network Architecture
Category: Python Programming

Introduction to Computer Vision and Image Processing

Course 321 hours4.3 (1,281 ratings)

What you'll learn

  • Describe the applications of computer vision across different industries.

  • Apply image processing and analysis techniques to computer vision problems.

  • Utilize Python, Pillow, and OpenCV for basic image processing and perform image classification and object detection.

  • Create an image classifier using Supervised learning techniques.

Skills you'll gain

Category: Computer Vision
Category: Deep Learning
Category: Machine Learning
Category: Machine Learning Algorithms
Category: Artificial Neural Networks
Category: Algorithms
Category: Applied Machine Learning
Category: Python Programming
Category: Computer Programming

Introduction to Neural Networks and PyTorch

Course 417 hours4.4 (1,724 ratings)

What you'll learn

  • Job-ready PyTorch skills employers need in just 6 weeks

  • How to implement and train linear regression models from scratch using PyTorch’s functionalities

  • Key concepts of logistic regression and how to apply them to classification problems

  • How to handle data and train models using gradient descent for optimization 

Skills you'll gain

Category: Human Learning
Category: Machine Learning
Category: Deep Learning
Category: Python Programming
Category: Artificial Neural Networks
Category: Machine Learning Algorithms
Category: Applied Machine Learning
Category: Algorithms
Category: Regression

Deep Learning with Keras and Tensorflow

Course 523 hours4.4 (863 ratings)

What you'll learn

  • Create custom layers and models in Keras and integrate Keras with TensorFlow 2.x

  • Develop advanced convolutional neural networks (CNNs) using Keras

  • Develop Transformer models for sequential data and time series prediction

  • Explain key concepts of Unsupervised learning in Keras, Deep Q-networks (DQNs), and reinforcement learning

Skills you'll gain

Category: Artificial Neural Networks
Category: Deep Learning
Category: Human Learning
Category: Machine Learning
Category: Applied Machine Learning
Category: Machine Learning Algorithms
Category: Network Model
Category: Python Programming

AI Capstone Project with Deep Learning

Course 616 hours4.5 (582 ratings)

What you'll learn

  • Build a deep learning model to solve a real problem.

  • Execute the process of creating a deep learning pipeline.

  • Apply knowledge of deep learning to improve models using real data.

  • Demonstrate ability to present and communicate outcomes of deep learning projects.

Skills you'll gain

Category: Deep Learning
Category: Machine Learning
Category: Python Programming
Category: Artificial Neural Networks
Category: Machine Learning Algorithms
Category: Applied Machine Learning
Category: Data Analysis
Category: Data Visualization

Instructors

Wojciech 'Victor' Fulmyk
IBM
4 Courses33,886 learners
Ricky Shi
IBM
1 Course32,684 learners
Romeo Kienzler
IBM
10 Courses698,677 learners

Offered by

IBM

Build toward a degree

When you complete this Professional Certificate, you may be able to have your learning recognized for credit if you are admitted and enroll in one of the following online degree programs.¹

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¹Career improvement (i.e. promotion, raise) based on Coursera learner outcome survey responses, United States, 2021.