Global Certificate Course in DevOps Analysis for Data Science

Wednesday, 25 February 2026 11:24:39

International applicants and their qualifications are accepted

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Overview

Overview

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DevOps Analysis for Data Science: This Global Certificate Course empowers data scientists to optimize their workflows.


Learn to leverage CI/CD pipelines and automation for efficient data science projects.


Master cloud platforms like AWS and Azure for seamless deployment and scaling of data science models.


This DevOps Analysis for Data Science course is perfect for data scientists, machine learning engineers, and anyone seeking to improve their data science DevOps skills.


Gain practical experience with real-world case studies and hands-on exercises. DevOps Analysis for Data Science is your key to faster, more reliable data science deployments.


Explore the course details and register today! Unlock your data science potential with efficient DevOps practices.

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DevOps Analysis for Data Science: Master the crucial intersection of DevOps and data science with our Global Certificate Course. Gain practical skills in CI/CD pipelines, automation, and cloud technologies specifically tailored for data science workflows. This comprehensive course enhances your career prospects as a Data Scientist or DevOps Engineer by equipping you with in-demand expertise. Learn from industry experts through interactive modules and real-world case studies. Boost your salary and unlock exciting opportunities in a rapidly growing field. Secure your future with this globally recognized certificate.

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

• **Introduction to DevOps Principles for Data Science**
• **Version Control and Collaboration (Git & GitHub)**
• **Containerization and Orchestration (Docker & Kubernetes) for Data Science Pipelines**
• **CI/CD for Data Science: Automating Model Deployment**
• **Infrastructure as Code (IaC) for Data Science Environments**
• **Monitoring and Logging in Data Science DevOps**
• **DevOps Security Best Practices for Data Science**
• **Cloud Platforms for Data Science DevOps (AWS, Azure, GCP)**

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

Career Role (DevOps & Data Science UK) Description
DevOps Engineer (Data Science Focus) Automates data pipelines, manages cloud infrastructure, ensures data security and high availability for data science projects. High demand for CI/CD expertise.
Data Scientist with DevOps Skills Develops and deploys machine learning models, collaborates with DevOps teams to automate model deployment and monitoring. Strong analytical and scripting abilities crucial.
MLOps Engineer Focuses on the lifecycle management of machine learning models, encompassing development, deployment, monitoring, and scaling using DevOps practices. In high demand in UK.
Cloud Data Engineer (DevOps) Builds and manages data infrastructure on cloud platforms, utilizing DevOps principles for automation and scalability. Excellent knowledge of cloud technologies needed.

Key facts about Global Certificate Course in DevOps Analysis for Data Science

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A Global Certificate Course in DevOps Analysis for Data Science equips participants with the crucial skills to streamline data science workflows. This involves understanding and implementing DevOps principles within the context of data science projects, leading to faster iteration and more efficient deployment of data-driven solutions.


Learning outcomes include mastering CI/CD pipelines for data science, proficiently using containerization technologies like Docker and Kubernetes for data science applications, and gaining expertise in infrastructure as code (IaC) for managing data science environments. Students will also develop skills in monitoring and logging data science processes, improving collaboration and communication within data science teams.


The course duration typically ranges from 4 to 8 weeks, depending on the program's intensity and structure. This timeframe allows for a comprehensive exploration of DevOps methodologies and their specific application in a data science context, incorporating both theoretical understanding and practical hands-on experience.


This Global Certificate Course in DevOps Analysis for Data Science holds significant industry relevance. The demand for data scientists who can efficiently manage and deploy their models is rapidly increasing. Graduates will be well-prepared for roles such as DevOps Engineer for Data Science, Data Science Ops Engineer, or Machine Learning Engineer, all of which require expertise in agile development, continuous integration and continuous delivery (CI/CD), and cloud computing – skills directly addressed within the curriculum.


The program's focus on automation, scalability, and reliability within data science projects makes it a highly valuable asset for aspiring and current professionals aiming to advance their careers in this rapidly evolving field. The course is designed to make you a highly sought-after data scientist, proficient in both analytical and deployment aspects of the data science lifecycle.

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Why this course?

Global Certificate Course in DevOps Analysis for Data Science is increasingly significant in today's UK market. The burgeoning data science sector demands efficient and reliable data pipelines, making DevOps skills crucial. A recent study indicates a 25% year-on-year growth in DevOps-related job postings within UK data science companies.

Skill Demand
CI/CD Pipelines High
Cloud Platforms (AWS, Azure) Very High
Containerization (Docker, Kubernetes) High

This Global Certificate Course in DevOps Analysis for Data Science bridges the gap between data science and operations, equipping professionals with the skills to manage and deploy data science models efficiently. The program addresses industry needs by focusing on practical application and real-world scenarios. Graduates are well-positioned for roles requiring expertise in both data science and DevOps within the UK's rapidly evolving technological landscape.

Who should enrol in Global Certificate Course in DevOps Analysis for Data Science?

Ideal Audience for Global Certificate Course in DevOps Analysis for Data Science
This DevOps Analysis for Data Science course is perfect for data scientists and engineers in the UK seeking to enhance their skills in automating data pipelines and improving the efficiency of their data workflows. With over 100,000 data science professionals in the UK (according to *insert source here*), many are looking to advance their careers by mastering DevOps principles. The course targets individuals with some experience in data science, software engineering, or IT operations, seeking to improve data infrastructure management, deployment automation, and monitoring. This includes roles like Data Engineers, Machine Learning Engineers, and Data Analysts eager to improve data delivery and collaboration within their teams. The practical DevOps skills gained will make you highly competitive, ensuring smoother transitions between data analysis stages and production deployment for both cloud and on-premise environments.