The Artificial Intelligence Engineer Learning Path provides a structured route into artificial intelligence and machine learning. Through a blend of online self-paced learning, live virtual classroom sessions and project work, you'll develop the technical knowledge required to work with data, build machine learning models and create deep learning solutions. The learning path includes completion certificates and practical assignments that help you demonstrate your capabilities in professional environments.
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Artificial Intelligence Engineer Learning Path
Course 1
Introduction to Artificial Intelligence
Course 2
Applied Data Science with Python
Course 3
Machine Learning
Course 4
Deep Learning with Keras and TensorFlow
Course 5
AI Capstone Project
Elective 1
Python for Data Science
Elective 2
Advanced Deep Learning and Computer Vision
Fundamental skills for aspiring AI engineers
Designed for professionals beginning their journey into AI engineering, this learning path combines foundational theory with applied learning. Across approximately 180 hours of content, you'll explore artificial intelligence concepts, data science, machine learning and deep learning technologies. Practical projects and a capstone assignment enable you to apply what you've learned and showcase your technical capabilities when progressing into AI-focused roles.
Learning objectives
- Understand AI concepts and applications
- Apply data science techniques
- Analyse and interpret data
- Build machine learning models
- Develop deep learning solutions
- Use Python for AI development
- Explore neural network architectures
- Solve real-world AI challenges
- Apply learning through practical assignments
- Produce evidence of technical capability
Key facts
Certification
This is a skills and knowledge-based course with no formal accreditation.
Who it’s for
This learning path is suitable for professionals seeking foundational AI engineering knowledge, including analysts, developers and those moving into machine learning-focused roles.
Prerequisites
A basic understanding of mathematics and familiarity with at least one programming language is recommended before enrolling.
Exam information
There is no formal exam for this learning path. Completion criteria must be met to achieve the completion certificate – more details in the FAQs.
Optional extras
Learners gain access to hackathons, practical projects and interactions with IBM experts.
Pre-course
We recommend reviewing fundamental mathematics concepts and ensuring familiarity with at least one programming language before beginning the learning path.
FAQs
The Artificial Intelligence Engineer Learning Path provides structured learning across the key disciplines required for AI engineering. Through online learning, live virtual classroom sessions and project work, you'll gain the technical understanding needed to work with data, develop models and apply AI techniques within professional environments.
How long does the learning path take to complete?
The learning path contains approximately 180 hours of learning content. Learners have access to a 12-month licence, allowing them to progress at a pace that suits their schedule.
Who should attend this learning path?
The programme is suitable for professionals seeking to build AI engineering skills, including analysts, software developers and those transitioning into data or machine learning roles.
How is the completion certificate achieved?
To qualify for the Artificial Intelligence Engineer Learning Path completion certificate, you must meet the required completion criteria across each stage of the programme:
- For Introduction to Artificial Intelligence, this includes completing at least 85% of the online learning content and achieving 80% or higher in the assessment.
- Applied Data Science with Python requires either 85% completion of the online learning content or attendance at a live virtual classroom session, together with a minimum assessment score of 75% and successful completion of the associated project.
- For Machine Learning, you must complete 85% of the online learning content or attend a live virtual classroom session, alongside the required project work.
- The Deep Learning with Keras and TensorFlow module requires attendance at a live virtual classroom session, a minimum assessment score of 70%, and successful completion of the practical project.
- To complete the learning path, you must also attend the AI Capstone Project live virtual classroom session and successfully pass the capstone project.
Once all learning, assessment and project requirements have been met, you will be awarded the Artificial Intelligence Engineer Learning Path completion certificate.
What practical experience is included?
The learning path includes more than 15 real-life projects and an AI capstone project designed to help you apply technical concepts and produce evidence of your learning through project-based activities.
What technologies will I learn?
The learning path covers Python, NumPy, Pandas, Matplotlib, machine learning techniques, Keras, TensorFlow and natural language processing concepts.
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