Welcome to the MLOps Specialization Course at the School of Core AI — designed to help you master the end-to-end ML lifecycle. Learn how to version data, track experiments, build CI/CD workflows, and scale models in production environments.
Gain hands-on experience with top tools like Docker, MLflow, Jenkins, GitHub Actions, Ray, Kubeflow, and cloud platforms including AWS SageMaker, Vertex AI, and Azure ML.
Skills you'll gain in MLOP's course
MLOP's Program Overview
Machine Learning Specialization course offered by the School of Core AI immerses learners in the essential principles and advanced machine learning practices. This comprehensive course covers fundamental concepts, including data preprocessing and feature engineering, vital for transforming raw data into actionable insights. Learners will gain the expertise to leverage machine learning techniques across a broad spectrum of applications, fostering their ability to innovate and drive progress within the artificial intelligence domain.
As the demand for skilled professionals in machine learning continues to rise, this specialization provides the critical education needed to excel in this dynamic and rapidly advancing field. Participants will emerge with the knowledge and capabilities to effectively navigate and contribute to the evolving landscape of AI.
Who Is This Program For?
Aspirational candidates with zero experience who are willing to jumpstart their careers in data science with machine learning.
Anyone who wants to get acquainted with machine learning and data science as a software developer.
People who are looking to switch career paths for an AI and machine learning career.
Data analysts who wish to superimpose data science with machine learning into their career.
Line managers who wish to learn more about the opportunities that exists in AI and data science with an application of machine learning for the improvement of their teams.
Future managers willing to deepen their knowledge in the field of AI and machine learning.
Academic as the data science and AI in their field of specialty
Anyone interested in data science with machine learning and needs more information on the same
Course Learning Objectives in MLOP's
What Sets Us Apart?
| Feature | Our Program | Other Courses |
|---|---|---|
| Expert-Led Sessions | ✔ 24 weeks of instruction from top-tier professionals with industry experience | ✘ Often lack guidance from seasoned experts, relying on less experienced instructors |
| Flexible Learning Options | ✔ Accessible 24/7 with over 150 hours of on-demand content | ✘ Limited accessibility and rigid learning schedules |
| Practical Assessments | ✔ 15 practical assessments for hands-on practice | ✘ Minimal practical exposure and hands-on opportunities |
| Real-World Assignments | ✔ Engage in 14+ real-world assignments directly linked to industry challenges | ✘ Minimal practical exposure and hands-on opportunities |
| Live Doubt-Clearing Sessions | ✔ 11 live sessions with experts for doubt resolution | ✘ Limited opportunities for real-time support and query resolution |
| Capstone Projects | ✔ 2-3 capstone projects applying skills to real-world problems | ✘ Few or no chances to work on substantial, real-world projects |
| Live Interviews | ✔ 5 mock interviews to prepare you for the real world | ✘ Lack of structured live interview preparation |
| Mock Interviews | ✔ 10 mock interviews to prepare for real job scenarios | ✘ Lack of structured mock interview preparation |
| Career and Placement Support | ✔ Comprehensive support for job placements, including resume reviews and salary negotiation tips | ✘ Often lack continuous support for career advancement and placement |
Hiring Partners
MLOps Course Fees
- Refund up to 70% if not placed within 10 months (maximum refund ₹52,499).
Additional Benefits:
- Job Assistance: Full support until you secure a role.
- Real-World Projects: Work on industry-grade use cases.
- Comprehensive Curriculum: Includes CI/CD pipelines, Docker, MLflow, Ray, and cloud deployment tools like SageMaker and Vertex AI.
Testimonials of our Successful Learners
What our learners have to say
Frequently Asked Questions
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