You should have at least 2 years of experience in software development or data science, proficiency in Python programming, a foundational understanding of statistics and linear algebra, and basic familiarity with at least one cloud platform (AWS, Azure, or GCP). This is an intermediate-to-advanced program designed for professionals looking to specialize in AI architecture.

The curriculum covers the full AI stack: classical machine learning, deep learning (CNNs, RNNs, transformers), generative AI with large language models, retrieval-augmented generation (RAG), AI agent design and orchestration, scalable AI system architecture, MLOps and CI/CD for model deployment, cloud-based AI infrastructure on AWS, Azure, and GCP, and AI governance and responsible AI practices.

Over the 24-week program, you should plan for approximately 15-20 hours per week, which includes live sessions, self-paced learning modules, hands-on labs, and capstone project work. The schedule is designed to accommodate working professionals while ensuring deep engagement with the material.

You will build three industry-relevant projects: a credit risk assessment system using ensemble ML techniques, a conversational AI agent with RAG for enterprise customer support, and an end-to-end predictive maintenance AI system for manufacturing. Each project involves real-world data, production deployment, and monitoring — mirroring the work of an AI architect.

Graduates are prepared for high-demand roles including AI Architect, AI Solutions Consultant, Machine Learning Engineer, Generative AI Developer, AI Product Manager, and AI Strategy & Governance Lead. The program's emphasis on system design, cloud deployment, and AI strategy equips you to lead AI transformations at the organizational level, significantly increasing your market value.

You will work extensively with Python, TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers, and LangChain for model building and AI agent development. For deployment and MLOps, you'll use Docker, Kubernetes, MLflow, FastAPI, and CI/CD pipelines. Cloud platforms include AWS SageMaker, Azure ML, and GCP Vertex AI. You'll also use Pinecone for vector databases and Prometheus and Grafana for monitoring.

The Micro Degree course is an online LIVE course, where LIVE sessions will be conducted online on our Classroom platform. Prior to the start of the course, you'll receive preparatory material in the form of recorded content which can be access on the same platform.

In this course instructors will use English language for teaching.

Upon successful registration, you will receive a confirmation email on your registered email ID. In this email you will receive login details for your newly created account on the Edyoda Classroom platform (https://classroom.edyoda.com). Additionally, you will receive a PDF guide containing step-by-step instructions on how to utilize the platform to access live sessions and learning materials.

Our instructors are the industry experts with a minimum working experience of 10 years with a strong technical and teaching background. They bring industry knowledge and practical expertise to the course.

Yes, the course includes online assignments, quizzes, and a final project to reinforce your learning and assess your proficiency in AI Architect Job Program.

Yes, you can interact with instructors and fellow students through discussion forums, live Q&A sessions. We encourage a supportive learning community.

We offer a 100% money-back guarantee to ensure your complete satisfaction. If you're not satisfied, you can request a full refund within 3 days of purchase or before the second session, whichever comes earlier. Simply contact our support team(support@edyoda.com) with your purchase details, such as the order ID or email address, and share your reason for the refund. Requests made after 3 days or after the second session will not be eligible for a refund. There are no hidden charges, you will receive the full amount paid. Refunds are processed within 7–10 business days and credited back to your original payment method.