What you will learn in Microsoft AI & ML Engineering Professional Certificate Course
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This program offers a structured pathway into AI and machine learning engineering, particularly using Microsoft Azure.
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Learners will gain proficiency in designing and managing AI infrastructure, including data pipelines and deployment systems.
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The course covers foundational and advanced ML algorithms such as supervised, unsupervised, deep learning, and reinforcement learning.
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Hands-on labs and projects provide practical experience with tools like Azure Machine Learning and AutoML.
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The curriculum emphasizes real-world application, preparing learners for industry roles with tangible skills.
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Completion of the program earns a recognized Microsoft certificate that validates AI & ML expertise.
Program Overview
Foundations of AI and Machine Learning
⏱️ 3–4 weeks
- Learn the core components of AI/ML pipelines and infrastructure.
- Understand data pipelines, model development, and deployment strategies.
- Develop an engineering mindset towards building scalable ML systems.
- Get introduced to tools and practices commonly used in AI projects.
Microsoft Azure for AI and Machine Learning
⏱️3–5 weeks
- Use Microsoft Azure services to develop and deploy AI solutions.
- Learn how to build end-to-end ML workflows in the cloud.
- Optimize models and manage data across Azure platforms.
- Gain hands-on experience with Azure ML tools.
Artificial Intelligence on Microsoft Azure
⏱️ 4-6 weeks
- Explore applications like computer vision, NLP, anomaly detection, and conversational AI.
- Learn ethical considerations and the principles of responsible AI.
- Use Azure AI to create intelligent agents and analytics tools.
- Build projects aligned with enterprise needs.
Microsoft Azure Machine Learning
⏱️ 4-6 weeks
- Train, tune, and deploy predictive models with Azure Machine Learning Studio.
- Utilize AutoML to reduce development time.
- Monitor and retrain models to ensure performance.
- Finalize models for real-world implementation.
Get certificate
Job Outlook
- The AI and ML job market is expected to grow over 20% annually through 2030.
- Demand is high for roles such as AI Engineer, ML Engineer, Data Scientist, and AI Consultant.
- Microsoft Azure experience is highly valued by employers seeking cloud-based ML skills.
- Salaries for AI professionals range from $90K to $150K+, depending on experience.
- This certificate boosts visibility for tech roles on LinkedIn and major job platforms.
- Builds a strong foundation for further specialization in AI or cloud computing.
- Aligns with industry trends like automation, generative AI, and data-driven products.
- Suitable for both career changers and upskillers aiming for technical roles.
Explore More Learning Paths
Elevate your expertise in artificial intelligence and machine learning with these carefully selected programs designed to deepen your technical knowledge and accelerate your journey toward becoming an advanced AI engineer.
Related Courses
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IBM Generative AI Engineering Professional Certificate Course – Master the foundations of generative AI, including LLM development, prompt engineering, and applied AI workflows.
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Generative AI Engineering with LLMs Specialization Course – Learn to design, tune, and deploy large language model–powered applications for real-world use cases.
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IBM AI Engineering Professional Certificate Course – Build strong AI engineering skills through hands-on learning with deep learning, machine learning algorithms, and model deployment techniques.
Related Reading
Deepen your understanding of how AI and data models support modern analytics and engineering workflows:
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What Does a Data Engineer Do? – Explore how data engineers build pipelines and systems that power AI, analytics, and large-scale machine learning environments.
