Google Data Analytics Professional Certificate |
6 months (self-paced) |
Foundational analytics, spreadsheets, SQL, data visualization |
Prepares for entry-level data analyst roles |
IBM AI Engineering Professional Certificate |
5–7 months (self-paced) |
Machine learning, deep learning, AI model deployment basics |
Hands-on projects for building and deploying AI models |
Microsoft Azure AI Fundamentals |
1–2 months |
Core AI concepts, responsible AI, computer vision, NLP |
Cloud-based AI exposure for beginners |
Data Science for Everyone – DataCamp |
2–3 months |
Basic statistics, Python, data manipulation |
Foundation in data handling for analytics & ML |
AI for Everyone (Coursera, Andrew Ng) |
4 weeks |
AI concepts in simple, non-technical language |
Explore AI before technical tracks |
Simplilearn Data Analytics Certificate Program |
4–6 months |
Excel, SQL, Python, Tableau, Power BI |
Industry-aligned projects for analyst roles |
edX AI MicroMasters (Columbia Univ.) |
8–12 months |
Foundational AI principles, practical assignments |
Can be credited toward a full master’s program |