Build AI-driven solutions with Microsoft Azure and advance your career in data science.
Azure AI Data Scientist Engineering
- 40-Hour Live Instructor Training
- Access to Recorded Sessions Anytime
- 5+ Real-World AI Projects
- Exam Simulation for Certification Prep
- Career Mentorship and Resume Guidance
450K+
Professionals trained
250+
Workshops Every Month
100+
Agile transformations
Azure AI Data Scientist Engineering Course Highlights
- 40-Hour Live Training
- 5+ Real-World AI Projects
- Micro Batches (10 Students)
- Individual Doubt Sessions
- Updated Content (Market Trends)
- Resume Building & Job Prep
- Personality Development & E-books
- Ongoing Career Mentorship
- Certification Exam Simulation
The Digitalearn Advantage
- Mock Interviews & Job Guidance
- Internship Benefits with Azure Tools
- Hands-on Practical AI Learning
- Hands-on Practical AI Learning
10000
+
Happy Students / Learners
120
+
Courses Completed
50
+
Industry Tie-ups
25
+
Expert Trainers / Mentors
95
%
Placement Success Rate
500
+ Real world
Live Projects Completed
Azure AI Data Scientist Engineering FAQ
What is Azure AI Data Scientist Engineering?
A course that teaches building, analyzing, and deploying AI solutions using Microsoft Azure.
Who should take this course?
Beginners, IT professionals, data analysts, and aspiring AI engineers.
What are the prerequisites?
No strict requirements, but programming basics (Python/SQL) help.
How long does training take?
Typically 6–8 weeks, with live + project-based learning.
What job roles can I get after training?
Data Scientist, AI Engineer, Machine Learning Engineer, Data Analyst.
Azure AI Data Scientist Engineering Prerequisites and Eligibility
-
No strict prerequisites.
-
Helpful: basic knowledge of data analysis, Python, or SQL.
-
Ideal for beginners, IT professionals, data analysts, developers, and students.
Curriculum Modules - Azure AI Data Scientist Engineering
Introduction to AI & Azure
- What is AI & Data Science
- Azure AI Tools & Setup
- Azure Notebooks for AI Projects
Machine Learning with Azure
- Supervised & Unsupervised Learning
- Neural Networks & Deep Learning
- Model Evaluation & Improvement
Deployment & Responsible AI
- Azure AI Model Deployment
- AI Ethics & Responsible Use
- Final Project & Certification Prep
