IBM AI Engineering Professional Certificate

Course Cover
compare button icon
Offer Percent Icon

1 Coupon Available

Login To View All

Course Features

icon

Duration

9 months

icon

Delivery Method

Online

icon

Available on

Limited Access

icon

Accessibility

Desktop, Laptop

icon

Language

English

icon

Subtitles

English

icon

Level

Intermediate

icon

Effort

3 hours per week

icon

Teaching Type

Self Paced

Course Description

Artificial intelligence (AI), which is revolutionizing entire industries and changing the way businesses use data to make business decisions, has changed how companies across all sectors leverage data. Organizations need AI engineers with cutting-edge skills such as deep learning neural networks and machine learning algorithms to deliver data-driven actionable intelligence that will help them stay competitive. This 6-course Professional Certificate will equip you with all the necessary tools to excel in your career as an AI/ML engineer. With Python programming languages, you will learn the fundamentals of machine learning and deeplearning. Popular machine learning and deep-learning libraries like SciPy and ScikitLearn, Keras and PyTorch will be applied to solve industry problems such as image processing, object recognition, text analytics (NLP), recommender system, and other types classifiers. You'll learn the skills necessary to scale machine learning algorithms using Apache Spark through hands-on projects. You will learn how to build, train and deploy various deep architectures including convolutional neural networks and recurrent networks. You will receive an IBM digital badge that recognizes your expertise in AI engineering, along with a Coursera Professional Certificate.

Course Overview

projects-img

International Faculty

projects-img

Post Course Interactions

projects-img

Instructor-Moderated Discussions

Skills You Will Gain

What You Will 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

Course Instructors

Author Image

SAEED AGHABOZORGI

Ph.D., Sr. Data Scientist

Saeed Aghabozorgi, PhD is a Sr. Data Scientist in IBM with a track record of developing enterprise level applications that substantially increases clients’ ability to turn data into actionable knowle...
Author Image

Joseph Santarcangelo

Ph.D., Data Scientist at IBM

Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.
Author Image

Alex Aklson

Ph.D., Data Scientist

Alex Aklson, Ph.D., is a data scientist in the Digital Business Group at IBM Canada. Alex has been intensively involved in many exciting data science projects such as designing a smart system that co...
Author Image

Aije Egwaikhide

Senior Data Scientist

Aije Egwaikhide is a Data Scientist at IBM who holds a degree in Economics and Statistics from the University of Manitoba and a Post-grad in Business Analytics from St. Lawrence College, Kingston. Sh...
Course Cover
Offer Percent Icon

1 Coupon Available
Get upto 100% - 0% Discount