AI certifications range from genuinely valuable to overpriced. Tier 1 (Worth It): 1) Google Professional Machine Learning Engineer - most respected in industry, covers ML problem framing, data prep, model development, and MLOps. Requires real hands-on experience to pass. 2) AWS Machine Learning Specialty - highly valued at companies on AWS, covers data engineering + modeling + ML implementations in AWS services. 3) DeepLearning.AI courses (Coursera) - Andrew Ng courses are foundational, not certifications per se but widely recognized as rigorous learning. Tier 2 (Situational): 4) Microsoft Azure AI Engineer Associate - valuable if working in Microsoft-heavy environments. 5) Databricks ML Professional - good if your work involves Databricks/Spark. Tier 3 (Limited Value): Generic AI "certificates" from bootcamps promising job guarantees. The honest truth: certifications signal you can learn and are motivated, but hiring managers prioritize portfolios and demonstrated skills. A strong GitHub portfolio beats any certification. Use certifications to structure learning and signal commitment, not as substitute for practical experience.