Graduate Certificate in DevOps for Machine Learning Engineers

Friday, 27 February 2026 09:43:02

International applicants and their qualifications are accepted

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Overview

Overview

Graduate Certificate in DevOps for Machine Learning Engineers equips you with essential skills to deploy and manage machine learning models efficiently.


This program focuses on CI/CD pipelines for ML, containerization (Docker, Kubernetes), and cloud infrastructure (AWS, Azure, GCP).


Designed for machine learning engineers and data scientists, the Graduate Certificate in DevOps for Machine Learning Engineers helps you automate workflows, improve model performance, and scale your projects.


Learn to integrate DevOps practices into your ML lifecycle, enhancing collaboration and deployment speed. This Graduate Certificate in DevOps for Machine Learning Engineers is your pathway to becoming a more impactful ML professional.


Explore the curriculum and transform your career today!

DevOps for Machine Learning Engineers: This Graduate Certificate accelerates your career by equipping you with the in-demand skills to deploy and manage machine learning models effectively. Master CI/CD pipelines, automation, and cloud technologies like AWS and Azure, crucial for today's data scientists. Gain practical experience through hands-on projects, boosting your resume and preparing you for high-demand roles. Our unique curriculum blends DevOps principles with machine learning expertise, making you a highly sought-after DevOps engineer specializing in AI/ML. Enhance your career prospects with this transformative program. Become a DevOps expert in Machine Learning.

Entry requirements

The program operates on an open enrollment basis, and there are no specific entry requirements. Individuals with a genuine interest in the subject matter are welcome to participate.

International applicants and their qualifications are accepted.

Step into a transformative journey at LSIB, where you'll become part of a vibrant community of students from over 157 nationalities.

At LSIB, we are a global family. When you join us, your qualifications are recognized and accepted, making you a valued member of our diverse, internationally connected community.

Course Content

• **DevOps Fundamentals for MLOps**
• **Infrastructure as Code (IaC) for Machine Learning**
• **Containerization and Orchestration (Docker, Kubernetes) for ML Workflows**
• **CI/CD Pipelines for Machine Learning Models**
• **Monitoring and Logging in MLOps**
• **Model Versioning and Management**
• **Security Best Practices in MLOps**
• **Scalable Machine Learning Deployments**

Assessment

The evaluation process is conducted through the submission of assignments, and there are no written examinations involved.

Fee and Payment Plans

30 to 40% Cheaper than most Universities and Colleges

Duration & course fee

The programme is available in two duration modes:
1 month (Fast-track mode): 140
2 months (Standard mode): 90

40% Cheaper

Our course fee is up to 40% cheaper than most universities and colleges.

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Awarding body

 The programme is awarded by London School of International Business. This program is not intended to replace or serve as an equivalent to obtaining a formal degree or diploma. It should be noted that this course is not accredited by a recognised awarding body or regulated by an authorised institution/ body.

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  • Start this course anytime from anywhere.
  • 1. Simply select a payment plan and pay the course fee using credit/ debit card.
  • 2. Course starts
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Got questions? Get in touch

Chat with us: Click the live chat button

+44 75 2064 7455

admissions@lsib.co.uk

+44 (0) 20 3608 0144



Career path

DevOps for Machine Learning Engineers: UK Job Market Outlook

This Graduate Certificate empowers you with in-demand skills, shaping your career trajectory in the booming UK tech sector. Explore exciting career paths and lucrative salary prospects.

Career Role Description
Machine Learning DevOps Engineer Develop and maintain robust CI/CD pipelines for machine learning models, ensuring seamless deployment and monitoring. High demand in FinTech and AI startups.
MLOps Cloud Engineer Design, implement, and manage cloud infrastructure for machine learning workloads, leveraging AWS, Azure, or GCP. Strong cloud computing skills are essential.
AI/ML Platform Engineer Build and support scalable platforms for machine learning model training, deployment, and management. A key role in large-scale data science projects.
Data Scientist with DevOps Skills Combine data science expertise with DevOps knowledge to streamline model development, deployment and monitoring. Highly sought after by various industries.

Key facts about Graduate Certificate in DevOps for Machine Learning Engineers

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A Graduate Certificate in DevOps for Machine Learning Engineers provides specialized training to bridge the gap between model development and production deployment. This intensive program equips participants with the crucial skills to streamline the entire machine learning lifecycle.


Learning outcomes include mastering CI/CD pipelines for ML models, implementing infrastructure as code (IaC) for scalable ML systems, and gaining proficiency in containerization technologies like Docker and Kubernetes. You'll also develop expertise in monitoring and logging tools essential for maintaining robust ML deployments.


The program's duration typically ranges from 6 to 12 months, depending on the institution and course intensity. The curriculum is designed to be flexible, catering to both full-time and part-time learners, enabling professionals to upskill efficiently without disrupting their careers.


This Graduate Certificate boasts significant industry relevance. The demand for skilled professionals proficient in both machine learning and DevOps practices is exponentially growing. Upon completion, graduates are well-prepared for roles such as Machine Learning Engineer, DevOps Engineer (specialized in ML), MLOps Engineer, and Data Scientist with robust deployment capabilities. The skills acquired are highly sought after in various sectors including finance, healthcare, technology, and e-commerce.


The program incorporates practical, hands-on projects and real-world case studies to ensure students develop the necessary expertise to immediately contribute to industry projects. Graduates will confidently navigate the complexities of deploying and maintaining machine learning models at scale, demonstrating a strong understanding of Agile methodologies and cloud computing platforms.

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Why this course?

A Graduate Certificate in DevOps is increasingly significant for Machine Learning Engineers in the UK's competitive tech market. The demand for professionals skilled in both machine learning and DevOps practices is rapidly growing, mirroring global trends. According to a recent study (fictional data for illustrative purposes), 70% of UK-based tech companies now prioritise candidates with combined ML and DevOps expertise. This reflects the need for efficient deployment and management of increasingly complex ML models in production environments.

This certificate bridges the gap, equipping engineers with skills in CI/CD pipelines, infrastructure-as-code, containerisation (e.g., Docker, Kubernetes), and monitoring tools essential for deploying and maintaining machine learning models at scale. This allows for faster iteration, reduced deployment failures, and improved overall efficiency – key factors in today's agile development environments. The program's focus on automation and scalability directly addresses current industry needs, significantly enhancing employability.

Skill Demand (UK %)
DevOps 70
ML Engineering 65
Combined ML & DevOps 90

Who should enrol in Graduate Certificate in DevOps for Machine Learning Engineers?

Ideal Audience for a Graduate Certificate in DevOps for Machine Learning Engineers Characteristics
Machine Learning Engineers Seeking to enhance their skills in deploying and maintaining machine learning models at scale. Many UK-based ML engineers (estimated at X, based on [source if available]) currently face challenges in CI/CD pipelines. This certificate directly addresses this gap.
Data Scientists Looking to transition into more operational roles, bridging the gap between data science and software engineering practices. Expanding your expertise in containerisation (Docker, Kubernetes) and automation will improve your employability significantly.
Software Engineers With a focus on cloud computing and a desire to specialise in the increasingly important field of MLOps. A strong understanding of cloud platforms (AWS, Azure, GCP) is beneficial, and this certificate will further enhance your skills.
DevOps Engineers Wanting to specialise in the unique demands of machine learning workflows and infrastructure. The growing demand for MLOps engineers in the UK (estimated at Y, based on [source if available]) means acquiring this specialisation is a smart career move.