KodeKloud Unveils Free 100 Days of MLOps Challenge to Operationalize AI at Scale

KodeKloud has officially launched its “100 Days of MLOps” challenge, a free, hands-on program designed to address the burgeoning demand for MLOps expertise in the technology sector. Released mid-2026, this initiative targets professionals in cloud, DevOps, and AI fields, aiming to bridge the critical gap in operationalizing machine learning models. MLOps is a rapidly expanding domain, projected to grow at nearly 37% year-over-year, essential for reliably deploying, scaling, and maintaining ML models in production—a significant challenge for many organizations currently building AI solutions. This new challenge builds on the success of KodeKloud’s previous “100 Days of DevOps” and “100 Days of Cloud” programs, which collectively engaged over 44,000 engineers across 104 countries, known for their structured approach to real-world scenarios and increasing difficulty.

The “100 Days of MLOps” program features 100 practical tasks spanning 12 distinct tool categories, culminating in a capstone project. Participants will gain engineering confidence across crucial MLOps tools such as Kubernetes, DVC (Data Version Control), ML Flow, FastAPI, BentoML, Evidently (for data/model drift detection), CI/CD pipelines, Argo, and Prefect for complex ML workflow orchestration at scale. The challenge provides a unique learning environment by provisioning actual cloud-native environments, eliminating associated cloud bills or the need to sign up for multiple ML services. Upon completion, participants will possess a public MLOps portfolio showcasing 100 completed hands-on tasks and earn a KodeKloud verified badge, serving as official recognition of their practical MLOps journey. KodeKloud recommends this challenge for experienced cloud/DevOps engineers transitioning to AI or ML practitioners struggling with model deployment, while newcomers to cloud and DevOps are encouraged to complete the foundational challenges first.