Introduction:

The Microsoft Azure AI Fundamentals certification (AI-900) is an entry-level qualification that introduces you to the essential concepts of Artificial Intelligence (AI), Machine Learning (ML), and their role in data science. It focuses on understanding how AI solutions are built, trained, and deployed using Microsoft Azure services, covering key areas such as AI workloads, responsible AI principles, data preprocessing, supervised and unsupervised learning, computer vision, natural language processing, and generative AI. Designed for beginners with little or no AI, data science, or cloud experience, AI-900 provides a solid grounding in how data is collected, prepared, and used to power intelligent applications—paving the way for advanced Azure AI, ML, and data science certifications.

Prerequisite:

The Introduction to AI in Azure course is for anyone who wants to learn about the kinds of solutions Artificial Intelligence (AI) can provide, and the Microsoft Azure services you can use to build them. You do not need prior experience with AI, machine learning, or Azure, but you should be generally comfortable using computers and the internet. Some topics will involve basic maths skills, such as interpreting graphs or percentages. The course also includes practical exercises with AI services and sample code, so having a basic understanding of programming will be an advantage.

1. AI-900 is an entry-level certification designed to introduce you to AI concepts and Azure AI services.
2. It is meant for beginners; you do not need prior AI, cloud, or programming experience.

What it covered in the courses?

1. AI & Responsible AI — Common AI/data science uses and ethical principles.
2. ML on Azure with Python — Features, labels, model training, evaluation, and deployment.
3. Computer Vision — Image, object, and face analysis with Azure services.
4. NLP — Text and speech analysis using Azure AI Language/Speech.
5. Generative AI — Create text, code, and images with Azure OpenAI.

Why should you do it?

Earning the AI-900: Microsoft Azure AI Fundamentals gives a structured, beginner-friendly introduction to AI, ML, and data science with Python on Azure—no prior expertise needed. It builds essential skills in a fast-growing field, enhances your CV with a globally recognised credential, and opens pathways to AI, data, and cloud roles. It also lays the groundwork for advanced certifications like Azure Data Scientist Associate, Azure AI Engineer Associate, and other ML/data analytics qualifications.

Hands on Experience:

The course features practical exercises, hands-on labs, and easy-to-understand lessons. It is designed to equip trainees with the essential knowledge and real-world skills needed to become proficient Data Scientists or AI Engineers.

SQA Framework:

This course is aligned with the Professional Development Award (PDA) in Data Science, accredited by the Scottish Qualifications Authority (SQA) at SCQF Level 8. Learners who successfully pass all relevant examinations will be awarded 40 SCQF credits.

Class Duration:

This intensive 18-week course is your ultimate fast-track to mastering everything you need to become a highly skilled and sought-after Data Scientist equipped with the knowledge and practical skills that open doors to the most exciting careers in tech.

Learning Modes:

ITPT is currently providing different method of learning opportunities to students. Many people are looking for learning diversity to enhance their qualifications, but they don’t have the time to take on full-time instructor led study or attending courses regularly at their appropriate venues.

Job Roles & Opportunities:

Upon completion of related certification exams, you will be able to fit-in the job roles such as:

1. Data Scientist (Entry Level / Junior)
2. Data Analyst
3. Junior Machine Learning Engineer
4. Deep Learning Engineer
5. AI Engineer
6. Research Scientist (AI/ML)
7. NLP Engineer
8. Data Engineer
9. ML Ops Engineer
10. Backend Developer (with ML focus)
11. Business Intelligence (BI) Developer
12. Product Analyst / Data Consultant
13. AI Product Manager (with technical background)
14. Computer Vision Engineer
15. Robotics Engineer (with ML/AI focus)
16. AI Ethics Specialist / Fairness Analyst
17. AI Developer
18. Python Developer (with Data Science)
19. Data Science Intern / Associate
20. Applied Scientist
21. Big Data Analyst

Target Audience:

Students & Graduates:

• University students from any STEM or related background
• Graduates in Computer Science, Mathematics, Engineering, Statistics, etc.
• Curious minds from any background — no prior coding experience required
• Students aiming to pursue a career that will never go out of demand

Professionals & Career Changers:

• Working professionals looking to switch to a data/AI career
• IT professionals wanting to upskill in Python, AI, or Machine Learning
• Job seekers wanting to enhance their employability in the tech industry
• Data analysts or BI professionals aiming to transition into data science or ML roles
• Researchers and academicians interested in applied AI and data analytics
• Freelancers and entrepreneurs building data-driven products or services

Aspirants & Enthusiasts:

• Aspiring Data Scientists, Machine Learning Engineers, and AI Developers
• Anyone looking to become a professional Data Scientist or ML Engineer
• Individuals eager to boost their data science skills
• Anyone with a strong interest in data, coding, and problem-solving
• Professionals or learners seeking a future-proof, high-demand career path

Funding Available:

Course Funding: SAAS PTFG: Scottish Awards Agency for Scotland

This course is funded by SAAS part time funding which is available to eligible individuals only;
SAAS General funding eligibility requirement:

1. You have to be a resident of Scotland
2. Either employed or unemployed, if working then earning must be less/equals to 25k a year
3. Have not used the SAAS funding in this Academic Year.

Other criteria:

1. Students do not need to pay it back as this is a grant not a loan.
2. This funding is different from the full-time funding which can be applied by someone who previously granted for a degree, postgrad or any other full time studies (HNC/HND) etc. but not in a same session
3. Part time funding cannot be received on a same session if one is already receiving any part/full time funding for other courses.
4. Part Time funding can only be used for one course per academic year
5. SAAS part time funding academic year starts from Aug to July.

For more information, please visit the below link 

www.saas.gov.uk/_forms/funding_guide.pdf

To check your eligibility:

Please follow the below link to check if you qualify for the course funding;

www.saas.gov.uk/part-time/undergraduate-funding

Self Funding

If you do not qualify for SAAS part-time, you have the option to self-fund the course.

Fees are payable in advance at the start of the course unless otherwise agreed.

We also provide flexible fee installments to help students in paying their fees.