IBM AI Engineering Professional Certificate

admin@academe
Last Update March 7, 2025

About This Course

The IBM AI Engineering Professional Certificate is a structured program that covers a wide range of AI topics—from machine learning fundamentals to deep learning applications using popular frameworks. Learners engage in practical projects and exercises, ultimately building a robust portfolio that demonstrates their expertise in AI engineering and prepares them for industry roles.


Key Learning Objectives

  • Master Machine Learning Fundamentals: Understand the core concepts and algorithms, including supervised and unsupervised learning.
  • Develop Deep Learning Expertise: Gain hands-on experience with neural networks using libraries like Keras, PyTorch, and TensorFlow.
  • Explore Computer Vision: Learn essential techniques for image processing and computer vision applications.
  • Apply Advanced AI Techniques: Tackle complex problems using advanced deep learning methods.
  • Build a Real-World Portfolio: Complete an AI capstone project to showcase your ability to design, implement, and evaluate deep learning solutions.

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Learning Objectives

Upon completing the IBM AI Engineering Professional Certificate, participants will be able to:
Apply core machine learning algorithms to real-world data using Python.
Design, build, and deploy deep learning models with Keras, PyTorch, and TensorFlow.
Utilize computer vision techniques for image analysis and processing.
Successfully execute a capstone project that demonstrates their comprehensive AI skills.
Build a portfolio of AI projects that validate their readiness for roles in AI engineering.

Material Includes

  • Hands-on Labs: Engage in interactive projects using real-world datasets and popular AI frameworks.
  • Practical Exercises: Gain experience through coding challenges and scenario-based tasks.
  • Community Forums: Collaborate with peers and instructors, share insights, and receive feedback.
  • Supplementary Materials: Access study guides, video tutorials, and practice quizzes to reinforce learning.

Target Audience

  • This program is ideal for:
  • Aspiring AI Engineers looking to build a solid foundation and advance their skills in AI and deep learning.
  • Data Scientists and Developers aiming to integrate machine learning and AI into practical applications.
  • IT Professionals seeking to expand their expertise in cutting-edge AI technologies.
  • Technical Leaders wanting to drive innovation through AI and build intelligent, data-driven solutions.

Curriculum

19 Lessons

Machine Learning with Python

Supervised vs. unsupervised learning00:00
Regression, classification, and clustering algorithms00:00
Practical application of machine learning algorithms00:00

Introduction to Deep Learning & Neural Networks with Keras

Introduction to Computer Vision and Image Processing

Deep Neural Networks with PyTorch

Building Deep Learning Models with TensorFlow

AI Capstone Project with Deep Learning

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US$1,500.00

Level
Intermediate
Lectures
19 lectures

Material Includes

  • Hands-on Labs: Engage in interactive projects using real-world datasets and popular AI frameworks.
  • Practical Exercises: Gain experience through coding challenges and scenario-based tasks.
  • Community Forums: Collaborate with peers and instructors, share insights, and receive feedback.
  • Supplementary Materials: Access study guides, video tutorials, and practice quizzes to reinforce learning.

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