Advanced Certificate in DevOps Configuration for Data Science

Tuesday, 10 February 2026 01:06:41

International applicants and their qualifications are accepted

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Overview

Overview

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DevOps Configuration for Data Science is an advanced certificate designed for data scientists and engineers.


Master essential DevOps practices for efficient data science workflows.


This program covers CI/CD pipelines, infrastructure as code, and containerization.


Learn to automate deployments, improve collaboration, and enhance data science project management.


Gain practical skills in configuration management tools like Ansible and Terraform.


The DevOps Configuration for Data Science certificate boosts your career prospects significantly.


Enroll now and transform your data science workflow!

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DevOps Configuration for Data Science: Master the art of efficient data science deployments with our Advanced Certificate. This intensive program equips you with crucial skills in CI/CD pipelines, infrastructure as code (IaC), and containerization for data science projects, boosting your career prospects in cloud computing and data engineering. Learn best practices for automating workflows and scaling data science solutions. Gain hands-on experience with real-world tools and techniques, setting you apart in the competitive data science job market. Secure your future in this in-demand field.

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 Data Science:** Introduction to DevOps principles, Agile methodologies, and their application in data science workflows.
• **Infrastructure as Code (IaC) for Data Scientists:** Utilizing tools like Terraform and Ansible to automate infrastructure provisioning and management for data science projects.
• **Containerization and Orchestration (Docker & Kubernetes):** Building and deploying data science applications using Docker containers and managing them with Kubernetes for scalability and efficiency.
• **CI/CD Pipelines for Data Science:** Implementing Continuous Integration and Continuous Delivery pipelines for data science projects using tools like Jenkins, GitLab CI, or GitHub Actions.
• **Monitoring and Logging in Data Science DevOps:** Implementing robust monitoring and logging solutions (e.g., Prometheus, Grafana, ELK stack) to track performance, identify issues, and ensure data pipeline reliability.
• **Data Security and Access Control in DevOps:** Implementing security best practices throughout the DevOps lifecycle for data science, including access control, encryption, and vulnerability management.
• **Version Control and Collaboration (Git):** Mastering Git for efficient code management, collaboration, and version control within data science teams.
• **DevOps for Cloud Platforms (AWS, Azure, GCP):** Deploying and managing data science workflows on major cloud platforms, leveraging their managed services for scalability and cost-effectiveness.

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

Role Description
DevOps Engineer (Data Science) Automates infrastructure and CI/CD pipelines for data science projects, ensuring efficient data flow and model deployment. High demand for cloud expertise (AWS, Azure, GCP).
Data Science DevOps Architect Designs and implements scalable, secure, and reliable DevOps infrastructure for large-scale data science initiatives. Key skills include containerization (Docker, Kubernetes) and infrastructure as code.
Cloud Data Engineer (DevOps Focused) Manages and optimizes cloud-based data infrastructure using DevOps principles, including automation and monitoring. Expertise in big data technologies is crucial.
MLOps Engineer Focuses on the deployment and monitoring of machine learning models in production environments using DevOps practices. Strong programming skills and experience with ML frameworks are essential.
Data Scientist (with DevOps Skills) Combines data science expertise with DevOps knowledge to build and deploy models independently. Strong understanding of CI/CD is vital.

Key facts about Advanced Certificate in DevOps Configuration for Data Science

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An Advanced Certificate in DevOps Configuration for Data Science equips you with the crucial skills to streamline your data science workflows. You'll master the art of automating deployments, infrastructure management, and continuous integration/continuous delivery (CI/CD) pipelines specifically tailored for data science projects.


Learning outcomes include proficiency in configuring and managing cloud infrastructure (AWS, Azure, GCP), implementing CI/CD for data science applications using tools like Jenkins and GitLab CI, and deploying machine learning models into production environments. You'll also gain experience with containerization technologies like Docker and Kubernetes, vital for scalability and reproducibility.


The program duration typically ranges from several weeks to a few months, depending on the intensity and structure of the chosen course. A flexible learning format often accommodates busy professionals.


This certificate is highly relevant to the current job market. Data scientists and machine learning engineers with DevOps expertise are in high demand. The ability to efficiently manage the entire lifecycle of a data science project, from development to deployment, significantly increases your value to potential employers. This advanced training in DevOps configuration for data science makes you a more competitive and versatile candidate in today's rapidly evolving tech landscape.


The curriculum integrates practical projects and real-world case studies, enhancing your understanding of Agile methodologies, monitoring tools, and security best practices within the context of data science DevOps. This hands-on approach ensures you're prepared for the challenges of a dynamic data science role.

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Why this course?

An Advanced Certificate in DevOps Configuration for Data Science is increasingly significant in today's UK market. The demand for skilled professionals capable of streamlining data science workflows through efficient DevOps practices is rapidly growing. According to a recent survey (hypothetical data for illustrative purposes), 75% of UK data science companies report a skills gap in DevOps integration. This highlights the urgent need for professionals proficient in automating data pipelines, infrastructure management, and continuous integration/continuous delivery (CI/CD) within data science projects.

Skill Demand
CI/CD Pipeline Automation High
Containerization (Docker, Kubernetes) High
Infrastructure as Code (IaC) Medium

This DevOps configuration expertise bridges the gap between data scientists and IT operations, leading to faster deployment cycles, improved collaboration, and ultimately, increased business value. Securing an Advanced Certificate signifies a commitment to mastering these crucial skills, making graduates highly competitive in the UK's dynamic data science landscape.

Who should enrol in Advanced Certificate in DevOps Configuration for Data Science?

Ideal Candidate Profile Skills & Experience Benefits
Data Scientists seeking to enhance their infrastructure management skills. Experience with data analysis tools (e.g., Python, R); familiarity with cloud platforms (AWS, Azure, GCP) is beneficial, but not required. Basic understanding of Linux command line is a plus. Accelerate data science project delivery; enhance collaboration within data science teams; improve data infrastructure management. UK data science roles are projected to grow by X% by [Year] (Source: [insert UK stat source]).
Machine Learning Engineers aiming for full-stack capabilities. Proven experience in model development and deployment; comfortable with version control (Git) and CI/CD pipelines; a strong grasp of scripting languages. Expand skillset to manage the entire data science lifecycle; command higher salaries; become a more versatile and valuable asset. The average salary for a Machine Learning Engineer in the UK is £[insert UK stat source].
Data Engineers looking to specialize in DevOps. Solid understanding of database technologies and big data platforms; experience with automation tools; familiarity with containerization (Docker, Kubernetes). Become a highly sought-after DevOps specialist in the data science field; contribute significantly to improved data pipeline efficiency and reliability; access specialized job roles with significantly higher earning potential.