Launch Your Data Science Career with Digitalearn
Azure AI Data Scientist Engineering
- Master AI-driven data solutions with hands-on Azure projects.
- 40-Hour Live Instructor Training
- Hands-on AI & ML Projects
- Exam Simulation & Certification Prep
- Career Guidance & Mentorship
- Small Interactive Learning Batches
450K+
Professionals trained
250+
Workshops Every Month
100+
Agile transformations
AWS Cloud Course Highlights
- Individual Doubt Clearing Sessions
- Recorded Classes for Anytime Access
- Market Trend Updated Content
- Personalized Class Feedback Support
- Internship Benefits with Tools
- Resume & Job Application Guide
- Mock Interviews – Technical + HR
- Personality Development Classes
- E-books & Learning Materials
The Digitalearn Advantage
- Globally Recognized Certification
- Enhanced Employability Skills
- Industry-Aligned Tools & Techniques
- Portfolio-Ready Projects
- Hands-on Practical Sessions
- Hands-on Practical Sessions
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
Digitalearn AWS FAQ
What is this course about?
This training helps you master data science workflows using Azure AI tools – from data preparation and modeling to deployment.
Who should join this course?
Ideal for IT professionals, aspiring data scientists, analysts, and anyone aiming to build a career in AI & data science.
What are the prerequisites?
It’s a 40-hour live training program, usually spread over 6–8 weeks.
What certifications do I get?
You’ll receive Digitalearn Azure AI Data Scientist Certification and guidance for Microsoft Azure Data Scientist Associate (DP-100).
Is this course hands-on?
Yes, with live projects, case studies, and labs to ensure real-world learning.
Azure AI Data Scientist Engineering Prerequisites and Eligibility
Prerequisites
-
Basic computer knowledge (Windows/Linux, internet usage)
-
Familiarity with IT concepts or networking is helpful but not mandatory
-
No coding skills required (optional for advanced modules)
Eligibility
-
IT Professionals looking to upskill in cloud computing
-
System Administrators & Developers wanting AWS expertise
-
Freshers & Students aspiring for a cloud career
-
Professionals from non-IT backgrounds interested in cloud technology
Curriculum Modules - Azure AI Data Scientist Engineering
Module 1: Introduction to Data Science with Azure
- Basics of AI, ML, and Data Science
- Exploratory Data Analysis (EDA)
- Experimentation and workspace setup
Module 2: Data Preparation & Exploration
- Importing and cleaning datasets
- Azure Data Factory for data pipelines
- Exploratory Data Analysis (EDA)
Module 3: Azure Machine Learning Basics
- Introduction to Azure ML Studio
- Building ML models with low-code tools
- Experimentation and workspace setup
